diff --git a/.github/FUNDING.yml b/.github/FUNDING.yml
new file mode 100644
index 000000000..3fa04cb6f
--- /dev/null
+++ b/.github/FUNDING.yml
@@ -0,0 +1,3 @@
+# These are supported funding model platforms
+
+github: [xmatthias]
diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md
index dacd9e673..54c9eab50 100644
--- a/.github/ISSUE_TEMPLATE/bug_report.md
+++ b/.github/ISSUE_TEMPLATE/bug_report.md
@@ -9,7 +9,7 @@ assignees: ''
 <!-- 
 Have you searched for similar issues before posting it?
 
-If you have discovered a bug in the bot, please [search our issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue). 
+If you have discovered a bug in the bot, please [search the issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue). 
 If it hasn't been reported, please create a new issue.
 
 Please do not use bug reports to request new features.
diff --git a/.github/ISSUE_TEMPLATE/question.md b/.github/ISSUE_TEMPLATE/question.md
index fd3d7df93..4b02e5f19 100644
--- a/.github/ISSUE_TEMPLATE/question.md
+++ b/.github/ISSUE_TEMPLATE/question.md
@@ -22,4 +22,4 @@ Please do not use the question template to report bugs or to request new feature
   
 ## Your question
 
-*Ask the question you have not been able to find an answer in our [Documentation](https://www.freqtrade.io/en/latest/)*
+*Ask the question you have not been able to find an answer in the [Documentation](https://www.freqtrade.io/en/latest/)*
diff --git a/.github/dependabot.yml b/.github/dependabot.yml
index 44ff606b4..4d1f28a0d 100644
--- a/.github/dependabot.yml
+++ b/.github/dependabot.yml
@@ -5,9 +5,17 @@ updates:
   schedule:
     interval: daily
   open-pull-requests-limit: 10
+
 - package-ecosystem: pip
   directory: "/"
   schedule:
     interval: weekly
   open-pull-requests-limit: 10
   target-branch: develop
+
+- package-ecosystem: "github-actions"
+  directory: "/"
+  schedule:
+    interval: "weekly"
+  open-pull-requests-limit: 10
+  target-branch: develop
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 228a60389..b8df7ab10 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -3,9 +3,9 @@ name: Freqtrade CI
 on:
   push:
     branches:
-      - master
       - stable
       - develop
+      - ci/*
     tags:
   release:
     types: [published]
@@ -20,26 +20,26 @@ jobs:
     strategy:
       matrix:
         os: [ ubuntu-18.04, ubuntu-20.04 ]
-        python-version: [3.7, 3.8, 3.9]
+        python-version: ["3.8", "3.9", "3.10"]
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
 
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
 
     - name: Cache_dependencies
-      uses: actions/cache@v2
+      uses: actions/cache@v3
       id: cache
       with:
         path: ~/dependencies/
         key: ${{ runner.os }}-dependencies
 
     - name: pip cache (linux)
-      uses: actions/cache@v2
-      if: startsWith(matrix.os, 'ubuntu')
+      uses: actions/cache@v3
+      if: runner.os == 'Linux'
       with:
         path: ~/.cache/pip
         key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
@@ -50,8 +50,9 @@ jobs:
         cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
 
     - name: Installation - *nix
+      if: runner.os == 'Linux'
       run: |
-        python -m pip install --upgrade pip
+        python -m pip install --upgrade pip wheel
         export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
         export TA_LIBRARY_PATH=${HOME}/dependencies/lib
         export TA_INCLUDE_PATH=${HOME}/dependencies/include
@@ -69,7 +70,7 @@ jobs:
       if: matrix.python-version == '3.9'
 
     - name: Coveralls
-      if: (startsWith(matrix.os, 'ubuntu-20') && matrix.python-version == '3.8')
+      if: (runner.os == 'Linux' && matrix.python-version == '3.8')
       env:
         # Coveralls token. Not used as secret due to github not providing secrets to forked repositories
         COVERALLS_REPO_TOKEN: 6D1m0xupS3FgutfuGao8keFf9Hc0FpIXu
@@ -101,42 +102,39 @@ jobs:
       run: |
         mypy freqtrade scripts
 
-    - name: Slack Notification
-      uses: lazy-actions/slatify@v3.0.0
+    - name: Discord notification
+      uses: rjstone/discord-webhook-notify@v1
       if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
-        type: ${{ job.status }}
-        job_name: '*Freqtrade CI ${{ matrix.os }}*'
-        mention: 'here'
-        mention_if: 'failure'
-        channel: '#notifications'
-        url: ${{ secrets.SLACK_WEBHOOK }}
+          severity: error
+          details: Freqtrade CI failed on ${{ matrix.os }}
+          webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
 
   build_macos:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
         os: [ macos-latest ]
-        python-version: [3.7, 3.8, 3.9]
+        python-version: ["3.8", "3.9", "3.10"]
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
 
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
 
     - name: Cache_dependencies
-      uses: actions/cache@v2
+      uses: actions/cache@v3
       id: cache
       with:
         path: ~/dependencies/
         key: ${{ runner.os }}-dependencies
 
     - name: pip cache (macOS)
-      uses: actions/cache@v2
-      if: startsWith(matrix.os, 'macOS')
+      uses: actions/cache@v3
+      if: runner.os == 'macOS'
       with:
         path: ~/Library/Caches/pip
         key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
@@ -147,10 +145,11 @@ jobs:
         cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
 
     - name: Installation - macOS
+      if: runner.os == 'macOS'
       run: |
         brew update
         brew install hdf5 c-blosc
-        python -m pip install --upgrade pip
+        python -m pip install --upgrade pip wheel
         export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
         export TA_LIBRARY_PATH=${HOME}/dependencies/lib
         export TA_INCLUDE_PATH=${HOME}/dependencies/include
@@ -162,7 +161,7 @@ jobs:
         pytest --random-order --cov=freqtrade --cov-config=.coveragerc
 
     - name: Coveralls
-      if: (startsWith(matrix.os, 'ubuntu-20') && matrix.python-version == '3.8')
+      if: (runner.os == 'Linux' && matrix.python-version == '3.8')
       env:
         # Coveralls token. Not used as secret due to github not providing secrets to forked repositories
         COVERALLS_REPO_TOKEN: 6D1m0xupS3FgutfuGao8keFf9Hc0FpIXu
@@ -194,17 +193,13 @@ jobs:
       run: |
         mypy freqtrade scripts
 
-    - name: Slack Notification
-      uses: lazy-actions/slatify@v3.0.0
+    - name: Discord notification
+      uses: rjstone/discord-webhook-notify@v1
       if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
-        type: ${{ job.status }}
-        job_name: '*Freqtrade CI ${{ matrix.os }}*'
-        mention: 'here'
-        mention_if: 'failure'
-        channel: '#notifications'
-        url: ${{ secrets.SLACK_WEBHOOK }}
-
+          severity: info
+          details: Test Succeeded!
+          webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
 
   build_windows:
 
@@ -212,19 +207,18 @@ jobs:
     strategy:
       matrix:
         os: [ windows-latest ]
-        python-version: [3.7, 3.8]
+        python-version: ["3.8", "3.9", "3.10"]
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
 
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
 
     - name: Pip cache (Windows)
-      uses: actions/cache@preview
-      if: startsWith(runner.os, 'Windows')
+      uses: actions/cache@v3
       with:
         path: ~\AppData\Local\pip\Cache
         key: ${{ matrix.os }}-${{ matrix.python-version }}-pip
@@ -257,28 +251,25 @@ jobs:
       run: |
         mypy freqtrade scripts
 
-    - name: Slack Notification
-      uses: lazy-actions/slatify@v3.0.0
+    - name: Discord notification
+      uses: rjstone/discord-webhook-notify@v1
       if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
-        type: ${{ job.status }}
-        job_name: '*Freqtrade CI windows*'
-        mention: 'here'
-        mention_if: 'failure'
-        channel: '#notifications'
-        url: ${{ secrets.SLACK_WEBHOOK }}
+          severity: error
+          details: Test Failed
+          webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
 
   docs_check:
     runs-on: ubuntu-20.04
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
 
     - name: Documentation syntax
       run: |
         ./tests/test_docs.sh
 
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: 3.8
 
@@ -288,14 +279,13 @@ jobs:
         pip install mkdocs
         mkdocs build
 
-    - name: Slack Notification
-      uses: lazy-actions/slatify@v3.0.0
+    - name: Discord notification
+      uses: rjstone/discord-webhook-notify@v1
       if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
-        type: ${{ job.status }}
-        job_name: '*Freqtrade Docs*'
-        channel: '#notifications'
-        url: ${{ secrets.SLACK_WEBHOOK }}
+          severity: error
+          details: Freqtrade doc test failed!
+          webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
 
   cleanup-prior-runs:
     runs-on: ubuntu-20.04
@@ -306,7 +296,7 @@ jobs:
       env:
         GITHUB_TOKEN: "${{ secrets.GITHUB_TOKEN }}"
 
-  # Notify on slack only once - when CI completes (and after deploy) in case it's successfull
+  # Notify only once - when CI completes (and after deploy) in case it's successfull
   notify-complete:
     needs: [ build_linux, build_macos, build_windows, docs_check ]
     runs-on: ubuntu-20.04
@@ -320,14 +310,13 @@ jobs:
       env:
         GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
-    - name: Slack Notification
-      uses: lazy-actions/slatify@v3.0.0
+    - name: Discord notification
+      uses: rjstone/discord-webhook-notify@v1
       if: always() && steps.check.outputs.has-permission && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
-        type: ${{ job.status }}
-        job_name: '*Freqtrade CI*'
-        channel: '#notifications'
-        url: ${{ secrets.SLACK_WEBHOOK }}
+          severity: info
+          details: Test Completed!
+          webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
 
   deploy:
     needs: [ build_linux, build_macos, build_windows, docs_check ]
@@ -336,10 +325,10 @@ jobs:
     if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
 
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v3
       with:
         python-version: 3.8
 
@@ -385,7 +374,7 @@ jobs:
 
     - name: Set up Docker Buildx
       id: buildx
-      uses: crazy-max/ghaction-docker-buildx@v1
+      uses: crazy-max/ghaction-docker-buildx@v3.3.1
       with:
         buildx-version: latest
         qemu-version: latest
@@ -400,17 +389,13 @@ jobs:
       run: |
         build_helpers/publish_docker_multi.sh
 
-
-    - name: Slack Notification
-      uses: lazy-actions/slatify@v3.0.0
+    - name: Discord notification
+      uses: rjstone/discord-webhook-notify@v1
       if: always() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
-        type: ${{ job.status }}
-        job_name: '*Freqtrade CI Deploy*'
-        mention: 'here'
-        mention_if: 'failure'
-        channel: '#notifications'
-        url: ${{ secrets.SLACK_WEBHOOK }}
+          severity: info
+          details: Deploy Succeeded!
+          webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
 
 
   deploy_arm:
@@ -420,7 +405,7 @@ jobs:
     if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
 
     - name: Extract branch name
       shell: bash
diff --git a/.github/workflows/docker_update_readme.yml b/.github/workflows/docker_update_readme.yml
index 95e69be2a..822533ee2 100644
--- a/.github/workflows/docker_update_readme.yml
+++ b/.github/workflows/docker_update_readme.yml
@@ -8,9 +8,9 @@ jobs:
   dockerHubDescription:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v1
+    - uses: actions/checkout@v3
     - name: Docker Hub Description
-      uses: peter-evans/dockerhub-description@v2.1.0
+      uses: peter-evans/dockerhub-description@v3
       env:
         DOCKERHUB_USERNAME: ${{ secrets.DOCKER_USERNAME }}
         DOCKERHUB_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
diff --git a/.gitignore b/.gitignore
index 16df71194..97f77f779 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,6 +1,8 @@
 # Freqtrade rules
 config*.json
 *.sqlite
+*.sqlite-shm
+*.sqlite-wal
 logfile.txt
 user_data/*
 !user_data/strategy/sample_strategy.py
@@ -10,6 +12,9 @@ freqtrade-plot.html
 freqtrade-profit-plot.html
 freqtrade/rpc/api_server/ui/*
 
+# Macos related
+.DS_Store
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 000000000..31af5b7c7
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,21 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+-   repo: https://github.com/pycqa/flake8
+    rev: '4.0.1'
+    hooks:
+    -   id: flake8
+        # stages: [push]
+
+-   repo: https://github.com/pre-commit/mirrors-mypy
+    rev: 'v0.942'
+    hooks:
+    -   id: mypy
+        # stages: [push]
+
+-   repo: https://github.com/pycqa/isort
+    rev: '5.10.1'
+    hooks:
+      - id: isort
+        name: isort (python)
+        # stages: [push]
diff --git a/.travis.yml b/.travis.yml
deleted file mode 100644
index 15c174bfe..000000000
--- a/.travis.yml
+++ /dev/null
@@ -1,55 +0,0 @@
-os:
-- linux
-dist: bionic
-language: python
-python:
-- 3.8
-services:
-  - docker
-env:
-  global:
-    - IMAGE_NAME=freqtradeorg/freqtrade
-install:
-- cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies; cd ..
-- export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
-- export TA_LIBRARY_PATH=${HOME}/dependencies/lib
-- export TA_INCLUDE_PATH=${HOME}/dependencies/include
-- pip install -r requirements-dev.txt
-- pip install -e .
-jobs:
-
-  include:
-    - stage: tests
-      script:
-      - pytest --random-order --cov=freqtrade --cov-config=.coveragerc
-      # Allow failure for coveralls
-      # - coveralls || true
-      name: pytest
-    - script:
-      - cp config_examples/config_bittrex.example.json config.json
-      - freqtrade create-userdir --userdir user_data
-      - freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
-      name: backtest
-    - script:
-      - cp config_examples/config_bittrex.example.json config.json
-      - freqtrade create-userdir --userdir user_data
-      - freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily
-      name: hyperopt
-    - script: flake8
-      name: flake8
-    - script:
-      # Test Documentation boxes -
-      # !!! <TYPE>: is not allowed!
-      # !!! <TYPE> "title" - Title needs to be quoted!
-      - grep -Er '^!{3}\s\S+:|^!{3}\s\S+\s[^"]' docs/*; test $? -ne 0
-      name: doc syntax
-    - script: mypy freqtrade scripts
-      name: mypy
-
-notifications:
-  slack:
-    secure: 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
-cache:
-  pip: True
-  directories:
-    - $HOME/dependencies
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index c4ccc1b9f..b4e0bc024 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -56,6 +56,13 @@ To help with that, we encourage you to install the git pre-commit
 hook that will warn you when you try to commit code that fails these checks. 
 Guide for installing them is [here](http://flake8.pycqa.org/en/latest/user/using-hooks.html).
 
+##### Additional styles applied
+
+* Have docstrings on all public methods
+* Use double-quotes for docstrings
+* Multiline docstrings should be indented to the level of the first quote
+* Doc-strings should follow the reST format (`:param xxx: ...`, `:return: ...`, `:raises KeyError: ... `)
+
 ### 3. Test if all type-hints are correct
 
 #### Run mypy
diff --git a/Dockerfile b/Dockerfile
index f7e26efe3..8f5b85698 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,4 +1,4 @@
-FROM python:3.9.7-slim-buster as base
+FROM python:3.9.9-slim-bullseye as base
 
 # Setup env
 ENV LANG C.UTF-8
diff --git a/MANIFEST.in b/MANIFEST.in
index adbcd2e30..a14965c09 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -2,5 +2,6 @@ include LICENSE
 include README.md
 recursive-include freqtrade *.py
 recursive-include freqtrade/templates/ *.j2 *.ipynb
+include freqtrade/exchange/binance_leverage_tiers.json
 include freqtrade/rpc/api_server/ui/fallback_file.html
 include freqtrade/rpc/api_server/ui/favicon.ico
diff --git a/README.md b/README.md
index 01effd7bc..679dbcab0 100644
--- a/README.md
+++ b/README.md
@@ -5,10 +5,14 @@
 [![Documentation](https://readthedocs.org/projects/freqtrade/badge/)](https://www.freqtrade.io)
 [![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
 
-Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
+Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
 
 ![freqtrade](https://raw.githubusercontent.com/freqtrade/freqtrade/develop/docs/assets/freqtrade-screenshot.png)
 
+## Sponsored promotion
+
+[![tokenbot-promo](https://raw.githubusercontent.com/freqtrade/freqtrade/develop/docs/assets/TokenBot-Freqtrade-banner.png)](https://tokenbot.com/?utm_source=github&utm_medium=freqtrade&utm_campaign=algodevs)
+
 ## Disclaimer
 
 This software is for educational purposes only. Do not risk money which
@@ -26,11 +30,13 @@ hesitate to read the source code and understand the mechanism of this bot.
 
 Please read the [exchange specific notes](docs/exchanges.md) to learn about eventual, special configurations needed for each exchange.
 
-- [X] [Binance](https://www.binance.com/) ([*Note for binance users](docs/exchanges.md#binance-blacklist))
+- [X] [Binance](https://www.binance.com/)
 - [X] [Bittrex](https://bittrex.com/)
-- [X] [Kraken](https://kraken.com/)
-- [X] [FTX](https://ftx.com)
+- [X] [FTX](https://ftx.com/#a=2258149)
 - [X] [Gate.io](https://www.gate.io/ref/6266643)
+- [X] [Huobi](http://huobi.com/)
+- [X] [Kraken](https://kraken.com/)
+- [X] [OKX](https://okx.com/) (Former OKEX)
 - [ ] [potentially many others](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
 
 ### Community tested
@@ -44,34 +50,28 @@ Exchanges confirmed working by the community:
 
 We invite you to read the bot documentation to ensure you understand how the bot is working.
 
-Please find the complete documentation on our [website](https://www.freqtrade.io).
+Please find the complete documentation on the [freqtrade website](https://www.freqtrade.io).
 
 ## Features
 
-- [x] **Based on Python 3.7+**: For botting on any operating system - Windows, macOS and Linux.
+- [x] **Based on Python 3.8+**: For botting on any operating system - Windows, macOS and Linux.
 - [x] **Persistence**: Persistence is achieved through sqlite.
 - [x] **Dry-run**: Run the bot without paying money.
 - [x] **Backtesting**: Run a simulation of your buy/sell strategy.
 - [x] **Strategy Optimization by machine learning**: Use machine learning to optimize your buy/sell strategy parameters with real exchange data.
-- [x] **Edge position sizing** Calculate your win rate, risk reward ratio, the best stoploss and adjust your position size before taking a position for each specific market. [Learn more](https://www.freqtrade.io/en/latest/edge/).
+- [x] **Edge position sizing** Calculate your win rate, risk reward ratio, the best stoploss and adjust your position size before taking a position for each specific market. [Learn more](https://www.freqtrade.io/en/stable/edge/).
 - [x] **Whitelist crypto-currencies**: Select which crypto-currency you want to trade or use dynamic whitelists.
 - [x] **Blacklist crypto-currencies**: Select which crypto-currency you want to avoid.
+- [x] **Builtin WebUI**: Builtin web UI to manage your bot.
 - [x] **Manageable via Telegram**: Manage the bot with Telegram.
-- [x] **Display profit/loss in fiat**: Display your profit/loss in 33 fiat.
-- [x] **Daily summary of profit/loss**: Provide a daily summary of your profit/loss.
+- [x] **Display profit/loss in fiat**: Display your profit/loss in fiat currency.
 - [x] **Performance status report**: Provide a performance status of your current trades.
 
 ## Quick start
 
-Freqtrade provides a Linux/macOS script to install all dependencies and help you to configure the bot.
+Please refer to the [Docker Quickstart documentation](https://www.freqtrade.io/en/stable/docker_quickstart/) on how to get started quickly.
 
-```bash
-git clone -b develop https://github.com/freqtrade/freqtrade.git 
-cd freqtrade
-./setup.sh --install
-```
-
-For any other type of installation please refer to [Installation doc](https://www.freqtrade.io/en/latest/installation/).
+For further (native) installation methods, please refer to the [Installation documentation page](https://www.freqtrade.io/en/stable/installation/).
 
 ## Basic Usage
 
@@ -121,14 +121,15 @@ optional arguments:
 
 ### Telegram RPC commands
 
-Telegram is not mandatory. However, this is a great way to control your bot. More details and the full command list on our [documentation](https://www.freqtrade.io/en/latest/telegram-usage/)
+Telegram is not mandatory. However, this is a great way to control your bot. More details and the full command list on the [documentation](https://www.freqtrade.io/en/latest/telegram-usage/)
 
 - `/start`: Starts the trader.
 - `/stop`: Stops the trader.
 - `/stopbuy`: Stop entering new trades.
 - `/status <trade_id>|[table]`: Lists all or specific open trades.
 - `/profit [<n>]`: Lists cumulative profit from all finished trades, over the last n days.
-- `/forcesell <trade_id>|all`: Instantly sells the given trade (Ignoring `minimum_roi`).
+- `/forceexit <trade_id>|all`: Instantly exits the given trade (Ignoring `minimum_roi`).
+- `/fx <trade_id>|all`: Alias to `/forceexit`
 - `/performance`: Show performance of each finished trade grouped by pair
 - `/balance`: Show account balance per currency.
 - `/daily <n>`: Shows profit or loss per day, over the last n days.
@@ -152,10 +153,10 @@ For any questions not covered by the documentation or for further information ab
 ### [Bugs / Issues](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
 
 If you discover a bug in the bot, please
-[search our issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
+[search the issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
 first. If it hasn't been reported, please
 [create a new issue](https://github.com/freqtrade/freqtrade/issues/new/choose) and
-ensure you follow the template guide so that our team can assist you as
+ensure you follow the template guide so that the team can assist you as
 quickly as possible.
 
 ### [Feature Requests](https://github.com/freqtrade/freqtrade/labels/enhancement)
@@ -169,13 +170,13 @@ in the bug reports.
 
 ### [Pull Requests](https://github.com/freqtrade/freqtrade/pulls)
 
-Feel like our bot is missing a feature? We welcome your pull requests!
+Feel like the bot is missing a feature? We welcome your pull requests!
 
-Please read our
+Please read the
 [Contributing document](https://github.com/freqtrade/freqtrade/blob/develop/CONTRIBUTING.md)
 to understand the requirements before sending your pull-requests.
 
-Coding is not a necessity to contribute - maybe start with improving our documentation?
+Coding is not a necessity to contribute - maybe start with improving the documentation?
 Issues labeled [good first issue](https://github.com/freqtrade/freqtrade/labels/good%20first%20issue) can be good first contributions, and will help get you familiar with the codebase.
 
 **Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [discord](https://discord.gg/p7nuUNVfP7) (please use the #dev channel for this). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it.
@@ -196,7 +197,7 @@ To run this bot we recommend you a cloud instance with a minimum of:
 
 ### Software requirements
 
-- [Python 3.7.x](http://docs.python-guide.org/en/latest/starting/installation/)
+- [Python >= 3.8](http://docs.python-guide.org/en/latest/starting/installation/)
 - [pip](https://pip.pypa.io/en/stable/installing/)
 - [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
 - [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html)
diff --git a/build_helpers/TA_Lib-0.4.21-cp37-cp37m-win_amd64.whl b/build_helpers/TA_Lib-0.4.21-cp37-cp37m-win_amd64.whl
deleted file mode 100644
index bccfd090f..000000000
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deleted file mode 100644
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deleted file mode 100644
index da9d74558..000000000
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diff --git a/build_helpers/TA_Lib-0.4.24-cp310-cp310-win_amd64.whl b/build_helpers/TA_Lib-0.4.24-cp310-cp310-win_amd64.whl
new file mode 100644
index 000000000..9a96b7894
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diff --git a/build_helpers/TA_Lib-0.4.24-cp38-cp38-win_amd64.whl b/build_helpers/TA_Lib-0.4.24-cp38-cp38-win_amd64.whl
new file mode 100644
index 000000000..f6c66375b
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diff --git a/build_helpers/TA_Lib-0.4.24-cp39-cp39-win_amd64.whl b/build_helpers/TA_Lib-0.4.24-cp39-cp39-win_amd64.whl
new file mode 100644
index 000000000..84d3e60ab
Binary files /dev/null and b/build_helpers/TA_Lib-0.4.24-cp39-cp39-win_amd64.whl differ
diff --git a/build_helpers/install_ta-lib.sh b/build_helpers/install_ta-lib.sh
index d12b16364..00c4417ae 100755
--- a/build_helpers/install_ta-lib.sh
+++ b/build_helpers/install_ta-lib.sh
@@ -11,8 +11,13 @@ if [ ! -f "${INSTALL_LOC}/lib/libta_lib.a" ]; then
   && curl 'http://git.savannah.gnu.org/gitweb/?p=config.git;a=blob_plain;f=config.guess;hb=HEAD' -o config.guess \
   && curl 'http://git.savannah.gnu.org/gitweb/?p=config.git;a=blob_plain;f=config.sub;hb=HEAD' -o config.sub \
   && ./configure --prefix=${INSTALL_LOC}/ \
-  && make -j$(nproc) \
-  && which sudo && sudo make install || make install
+  && make
+  if [ $? -ne 0 ]; then
+    echo "Failed building ta-lib."
+    cd .. && rm -rf ./ta-lib/
+    exit 1
+  fi
+  which sudo && sudo make install || make install
   if [ -x "$(command -v apt-get)" ]; then
     echo "Updating library path using ldconfig"
     sudo ldconfig
diff --git a/build_helpers/install_windows.ps1 b/build_helpers/install_windows.ps1
index ec38ea212..4caefa340 100644
--- a/build_helpers/install_windows.ps1
+++ b/build_helpers/install_windows.ps1
@@ -1,19 +1,18 @@
 # Downloads don't work automatically, since the URL is regenerated via javascript.
 # Downloaded from https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib
 
-python -m pip install --upgrade pip
+python -m pip install --upgrade pip wheel
 
 $pyv = python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
 
-if ($pyv -eq '3.7') {
-    pip install build_helpers\TA_Lib-0.4.21-cp37-cp37m-win_amd64.whl
-}
 if ($pyv -eq '3.8') {
-    pip install build_helpers\TA_Lib-0.4.21-cp38-cp38-win_amd64.whl
+    pip install build_helpers\TA_Lib-0.4.24-cp38-cp38-win_amd64.whl
 }
 if ($pyv -eq '3.9') {
-    pip install build_helpers\TA_Lib-0.4.21-cp39-cp39-win_amd64.whl
+    pip install build_helpers\TA_Lib-0.4.24-cp39-cp39-win_amd64.whl
+}
+if ($pyv -eq '3.10') {
+    pip install build_helpers\TA_Lib-0.4.24-cp310-cp310-win_amd64.whl
 }
-
 pip install -r requirements-dev.txt
 pip install -e .
diff --git a/build_helpers/publish_docker_arm64.sh b/build_helpers/publish_docker_arm64.sh
index 1ad8074d4..70f99e54b 100755
--- a/build_helpers/publish_docker_arm64.sh
+++ b/build_helpers/publish_docker_arm64.sh
@@ -42,7 +42,7 @@ docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_I
 docker tag freqtrade:$TAG_PLOT_ARM ${CACHE_IMAGE}:$TAG_PLOT_ARM
 
 # Run backtest
-docker run --rm -v $(pwd)/config_examples/config_bittrex.example.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG_ARM} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy StrategyTestV2
+docker run --rm -v $(pwd)/config_examples/config_bittrex.example.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG_ARM} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy StrategyTestV3
 
 if [ $? -ne 0 ]; then
     echo "failed running backtest"
diff --git a/build_helpers/publish_docker_multi.sh b/build_helpers/publish_docker_multi.sh
index dd6ac841e..fd5f0ef93 100755
--- a/build_helpers/publish_docker_multi.sh
+++ b/build_helpers/publish_docker_multi.sh
@@ -53,7 +53,7 @@ docker build --cache-from freqtrade:${TAG} --build-arg sourceimage=${CACHE_IMAGE
 docker tag freqtrade:$TAG_PLOT ${CACHE_IMAGE}:$TAG_PLOT
 
 # Run backtest
-docker run --rm -v $(pwd)/config_examples/config_bittrex.example.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy StrategyTestV2
+docker run --rm -v $(pwd)/config_examples/config_bittrex.example.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy StrategyTestV3
 
 if [ $? -ne 0 ]; then
     echo "failed running backtest"
diff --git a/config_examples/config_binance.example.json b/config_examples/config_binance.example.json
index 938bc9342..ad8862afa 100644
--- a/config_examples/config_binance.example.json
+++ b/config_examples/config_binance.example.json
@@ -8,19 +8,23 @@
     "dry_run": true,
     "cancel_open_orders_on_exit": false,
     "unfilledtimeout": {
-        "buy": 10,
-        "sell": 30
+        "entry": 10,
+        "exit": 10,
+        "exit_timeout_count": 0,
+        "unit": "minutes"
     },
-    "bid_strategy": {
-        "ask_last_balance": 0.0,
+    "entry_pricing": {
+        "price_side": "same",
         "use_order_book": true,
         "order_book_top": 1,
+        "price_last_balance": 0.0,
         "check_depth_of_market": {
             "enabled": false,
             "bids_to_ask_delta": 1
         }
     },
-    "ask_strategy": {
+    "exit_pricing": {
+        "price_side": "same",
         "use_order_book": true,
         "order_book_top": 1
     },
@@ -28,10 +32,8 @@
         "name": "binance",
         "key": "your_exchange_key",
         "secret": "your_exchange_secret",
-        "ccxt_config": {"enableRateLimit": true},
+        "ccxt_config": {},
         "ccxt_async_config": {
-            "enableRateLimit": true,
-            "rateLimit": 200
         },
         "pair_whitelist": [
             "ALGO/BTC",
@@ -88,7 +90,7 @@
     },
     "bot_name": "freqtrade",
     "initial_state": "running",
-    "forcebuy_enable": false,
+    "force_enter_enable": false,
     "internals": {
         "process_throttle_secs": 5
     }
diff --git a/config_examples/config_bittrex.example.json b/config_examples/config_bittrex.example.json
index 4352d8822..a0a5071dd 100644
--- a/config_examples/config_bittrex.example.json
+++ b/config_examples/config_bittrex.example.json
@@ -8,19 +8,23 @@
     "dry_run": true,
     "cancel_open_orders_on_exit": false,
     "unfilledtimeout": {
-        "buy": 10,
-        "sell": 30
+        "entry": 10,
+        "exit": 10,
+        "exit_timeout_count": 0,
+        "unit": "minutes"
     },
-    "bid_strategy": {
+    "entry_pricing": {
+        "price_side": "same",
         "use_order_book": true,
-        "ask_last_balance": 0.0,
         "order_book_top": 1,
+        "price_last_balance": 0.0,
         "check_depth_of_market": {
             "enabled": false,
             "bids_to_ask_delta": 1
         }
     },
-    "ask_strategy":{
+    "exit_pricing":{
+        "price_side": "same",
         "use_order_book": true,
         "order_book_top": 1
     },
@@ -83,7 +87,7 @@
     },
     "bot_name": "freqtrade",
     "initial_state": "running",
-    "forcebuy_enable": false,
+    "force_entry_enable": false,
     "internals": {
         "process_throttle_secs": 5
     }
diff --git a/config_examples/config_ftx.example.json b/config_examples/config_ftx.example.json
index 48651f04c..c49898277 100644
--- a/config_examples/config_ftx.example.json
+++ b/config_examples/config_ftx.example.json
@@ -8,19 +8,23 @@
     "dry_run": true,
     "cancel_open_orders_on_exit": false,
     "unfilledtimeout": {
-        "buy": 10,
-        "sell": 30
+        "entry": 10,
+        "exit": 10,
+        "exit_timeout_count": 0,
+        "unit": "minutes"
     },
-    "bid_strategy": {
-        "ask_last_balance": 0.0,
+    "entry_pricing": {
+        "price_side": "same",
         "use_order_book": true,
         "order_book_top": 1,
+        "price_last_balance": 0.0,
         "check_depth_of_market": {
             "enabled": false,
             "bids_to_ask_delta": 1
         }
     },
-    "ask_strategy": {
+    "exit_pricing": {
+        "price_side": "same",
         "use_order_book": true,
         "order_book_top": 1
     },
@@ -28,11 +32,8 @@
         "name": "ftx",
         "key": "your_exchange_key",
         "secret": "your_exchange_secret",
-        "ccxt_config": {"enableRateLimit": true},
-        "ccxt_async_config": {
-            "enableRateLimit": true,
-            "rateLimit": 50
-        },
+        "ccxt_config": {},
+        "ccxt_async_config": {},
         "pair_whitelist": [
             "BTC/USD",
             "ETH/USD",
@@ -88,7 +89,7 @@
     },
     "bot_name": "freqtrade",
     "initial_state": "running",
-    "forcebuy_enable": false,
+    "force_entry_enable": false,
     "internals": {
         "process_throttle_secs": 5
     }
diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json
index c415d70b0..193cc30bc 100644
--- a/config_examples/config_full.example.json
+++ b/config_examples/config_full.example.json
@@ -8,16 +8,20 @@
     "amend_last_stake_amount": false,
     "last_stake_amount_min_ratio": 0.5,
     "dry_run": true,
+    "dry_run_wallet": 1000,
     "cancel_open_orders_on_exit": false,
     "timeframe": "5m",
     "trailing_stop": false,
     "trailing_stop_positive": 0.005,
     "trailing_stop_positive_offset": 0.0051,
     "trailing_only_offset_is_reached": false,
-    "use_sell_signal": true,
-    "sell_profit_only": false,
-    "sell_profit_offset": 0.0,
-    "ignore_roi_if_buy_signal": false,
+    "use_exit_signal": true,
+    "exit_profit_only": false,
+    "exit_profit_offset": 0.0,
+    "ignore_roi_if_entry_signal": false,
+    "ignore_buying_expired_candle_after": 300,
+    "trading_mode": "spot",
+    "margin_mode": "",
     "minimal_roi": {
         "40":  0.0,
         "30":  0.01,
@@ -26,38 +30,41 @@
     },
     "stoploss": -0.10,
     "unfilledtimeout": {
-        "buy": 10,
-        "sell": 30,
+        "entry": 10,
+        "exit": 10,
+        "exit_timeout_count": 0,
         "unit": "minutes"
     },
-    "bid_strategy": {
-        "price_side": "bid",
+    "entry_pricing": {
+        "price_side": "same",
         "use_order_book": true,
-        "ask_last_balance": 0.0,
         "order_book_top": 1,
+        "price_last_balance": 0.0,
         "check_depth_of_market": {
             "enabled": false,
             "bids_to_ask_delta": 1
         }
     },
-    "ask_strategy":{
-        "price_side": "ask",
+    "exit_pricing":{
+        "price_side": "same",
         "use_order_book": true,
-        "order_book_top": 1
+        "order_book_top": 1,
+        "price_last_balance": 0.0
     },
     "order_types": {
-        "buy": "limit",
-        "sell": "limit",
-        "emergencysell": "market",
-        "forcesell": "market",
-        "forcebuy": "market",
+        "entry": "limit",
+        "exit": "limit",
+        "emergency_exit": "market",
+        "force_exit": "market",
+        "force_entry": "market",
         "stoploss": "market",
         "stoploss_on_exchange": false,
-        "stoploss_on_exchange_interval": 60
+        "stoploss_on_exchange_interval": 60,
+        "stoploss_on_exchange_limit_ratio": 0.99
     },
     "order_time_in_force": {
-        "buy": "gtc",
-        "sell": "gtc"
+        "entry": "gtc",
+        "exit": "gtc"
     },
     "pairlists": [
         {"method": "StaticPairList"},
@@ -84,12 +91,9 @@
         "key": "your_exchange_key",
         "secret": "your_exchange_secret",
         "password": "",
-        "ccxt_config": {"enableRateLimit": true},
-        "ccxt_async_config": {
-            "enableRateLimit": true,
-            "rateLimit": 500,
-            "aiohttp_trust_env": false
-        },
+        "log_responses": false,
+        "ccxt_config": {},
+        "ccxt_async_config": {},
         "pair_whitelist": [
             "ALGO/BTC",
             "ATOM/BTC",
@@ -135,21 +139,21 @@
             "status": "on",
             "warning": "on",
             "startup": "on",
-            "buy": "on",
-            "buy_fill": "on",
-            "sell": {
+            "entry": "on",
+            "entry_fill": "on",
+            "exit": {
                 "roi": "off",
-                "emergency_sell": "off",
-                "force_sell": "off",
-                "sell_signal": "off",
+                "emergency_exit": "off",
+                "force_exit": "off",
+                "exit_signal": "off",
                 "trailing_stop_loss": "off",
                 "stop_loss": "off",
                 "stoploss_on_exchange": "off",
-                "custom_sell": "off"
+                "custom_exit": "off"
             },
-            "sell_fill": "on",
-            "buy_cancel": "on",
-            "sell_cancel": "on",
+            "exit_fill": "on",
+            "entry_cancel": "on",
+            "exit_cancel": "on",
             "protection_trigger": "off",
             "protection_trigger_global": "on"
         },
@@ -170,7 +174,7 @@
     "bot_name": "freqtrade",
     "db_url": "sqlite:///tradesv3.sqlite",
     "initial_state": "running",
-    "forcebuy_enable": false,
+    "force_entry_enable": false,
     "internals": {
         "process_throttle_secs": 5,
         "heartbeat_interval": 60
@@ -178,6 +182,7 @@
     "disable_dataframe_checks": false,
     "strategy": "SampleStrategy",
     "strategy_path": "user_data/strategies/",
+    "add_config_files": [],
     "dataformat_ohlcv": "json",
     "dataformat_trades": "jsongz"
 }
diff --git a/config_examples/config_kraken.example.json b/config_examples/config_kraken.example.json
index bf3548568..c55dea6ba 100644
--- a/config_examples/config_kraken.example.json
+++ b/config_examples/config_kraken.example.json
@@ -8,19 +8,23 @@
     "dry_run": true,
     "cancel_open_orders_on_exit": false,
     "unfilledtimeout": {
-        "buy": 10,
-        "sell": 30
+        "entry": 10,
+        "exit": 10,
+        "exit_timeout_count": 0,
+        "unit": "minutes"
     },
-    "bid_strategy": {
+    "entry_pricing": {
+        "price_side": "same",
         "use_order_book": true,
-        "ask_last_balance": 0.0,
         "order_book_top": 1,
+        "price_last_balance": 0.0,
         "check_depth_of_market": {
             "enabled": false,
             "bids_to_ask_delta": 1
         }
     },
-    "ask_strategy":{
+    "exit_pricing":{
+        "price_side": "same",
         "use_order_book": true,
         "order_book_top": 1
     },
@@ -28,10 +32,8 @@
         "name": "kraken",
         "key": "your_exchange_key",
         "secret": "your_exchange_key",
-        "ccxt_config": {"enableRateLimit": true},
+        "ccxt_config": {},
         "ccxt_async_config": {
-            "enableRateLimit": true,
-            "rateLimit": 1000
         },
         "pair_whitelist": [
             "ADA/EUR",
@@ -93,7 +95,7 @@
     },
     "bot_name": "freqtrade",
     "initial_state": "running",
-    "forcebuy_enable": false,
+    "force_entry_enable": false,
     "internals": {
         "process_throttle_secs": 5
     },
diff --git a/docker-compose.yml b/docker-compose.yml
index 80e194ab2..445fbaea0 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -15,10 +15,10 @@ services:
     volumes:
       - "./user_data:/freqtrade/user_data"
     # Expose api on port 8080 (localhost only)
-    # Please read the https://www.freqtrade.io/en/latest/rest-api/ documentation
+    # Please read the https://www.freqtrade.io/en/stable/rest-api/ documentation
     # before enabling this.
-    # ports:
-    #   - "127.0.0.1:8080:8080"
+    ports:
+      - "127.0.0.1:8080:8080"
     # Default command used when running `docker compose up`
     command: >
       trade
diff --git a/docker/Dockerfile.armhf b/docker/Dockerfile.armhf
index f9827774e..16f2aebcd 100644
--- a/docker/Dockerfile.armhf
+++ b/docker/Dockerfile.armhf
@@ -1,4 +1,4 @@
-FROM python:3.7.10-slim-buster as base
+FROM python:3.9.9-slim-bullseye as base
 
 # Setup env
 ENV LANG C.UTF-8
diff --git a/docs/advanced-hyperopt.md b/docs/advanced-hyperopt.md
index f5a52ff49..7f1bd0fed 100644
--- a/docs/advanced-hyperopt.md
+++ b/docs/advanced-hyperopt.md
@@ -13,7 +13,7 @@ A sample of this can be found below, which is identical to the Default Hyperopt
 
 ``` python
 from datetime import datetime
-from typing import Dict
+from typing import Any, Dict
 
 from pandas import DataFrame
 
@@ -56,7 +56,7 @@ Currently, the arguments are:
 
 * `results`: DataFrame containing the resulting trades.
     The following columns are available in results (corresponds to the output-file of backtesting when used with `--export trades`):  
-    `pair, profit_ratio, profit_abs, open_date, open_rate, fee_open, close_date, close_rate, fee_close, amount, trade_duration, is_open, sell_reason, stake_amount, min_rate, max_rate, stop_loss_ratio, stop_loss_abs`
+    `pair, profit_ratio, profit_abs, open_date, open_rate, fee_open, close_date, close_rate, fee_close, amount, trade_duration, is_open, exit_reason, stake_amount, min_rate, max_rate, stop_loss_ratio, stop_loss_abs`
 * `trade_count`: Amount of trades (identical to `len(results)`)
 * `min_date`: Start date of the timerange used
 * `min_date`: End date of the timerange used
@@ -105,7 +105,7 @@ You can define your own estimator for Hyperopt by implementing `generate_estimat
 ```python
 class MyAwesomeStrategy(IStrategy):
     class HyperOpt:
-        def generate_estimator():
+        def generate_estimator(dimensions: List['Dimension'], **kwargs):
             return "RF"
 
 ```
@@ -119,13 +119,34 @@ Example for `ExtraTreesRegressor` ("ET") with additional parameters:
 ```python
 class MyAwesomeStrategy(IStrategy):
     class HyperOpt:
-        def generate_estimator():
+        def generate_estimator(dimensions: List['Dimension'], **kwargs):
             from skopt.learning import ExtraTreesRegressor
             # Corresponds to "ET" - but allows additional parameters.
             return ExtraTreesRegressor(n_estimators=100)
 
 ```
 
+The `dimensions` parameter is the list of `skopt.space.Dimension` objects corresponding to the parameters to be optimized. It can be used to create isotropic kernels for the `skopt.learning.GaussianProcessRegressor` estimator. Here's an example:
+
+```python
+class MyAwesomeStrategy(IStrategy):
+    class HyperOpt:
+        def generate_estimator(dimensions: List['Dimension'], **kwargs):
+            from skopt.utils import cook_estimator
+            from skopt.learning.gaussian_process.kernels import (Matern, ConstantKernel)
+            kernel_bounds = (0.0001, 10000)
+            kernel = (
+                ConstantKernel(1.0, kernel_bounds) * 
+                Matern(length_scale=np.ones(len(dimensions)), length_scale_bounds=[kernel_bounds for d in dimensions], nu=2.5)
+            )
+            kernel += (
+                ConstantKernel(1.0, kernel_bounds) * 
+                Matern(length_scale=np.ones(len(dimensions)), length_scale_bounds=[kernel_bounds for d in dimensions], nu=1.5)
+            )
+
+            return cook_estimator("GP", space=dimensions, kernel=kernel, n_restarts_optimizer=2)
+```
+
 !!! Note
     While custom estimators can be provided, it's up to you as User to do research on possible parameters and analyze / understand which ones should be used.
     If you're unsure about this, best use one of the Defaults (`"ET"` has proven to be the most versatile) without further parameters.
diff --git a/docs/advanced-setup.md b/docs/advanced-setup.md
index f03bc10c0..93a2025ed 100644
--- a/docs/advanced-setup.md
+++ b/docs/advanced-setup.md
@@ -52,6 +52,71 @@ freqtrade trade -c MyConfigUSDT.json -s MyCustomStrategy --db-url sqlite:///user
 
 For more information regarding usage of the sqlite databases, for example to manually enter or remove trades, please refer to the [SQL Cheatsheet](sql_cheatsheet.md).
 
+### Multiple instances using docker
+
+To run multiple instances of freqtrade using docker you will need to edit the docker-compose.yml file and add all the instances you want as separate services. Remember, you can separate your configuration into multiple files, so it's a good idea to think about making them modular, then if you need to edit something common to all bots, you can do that in a single config file. 
+``` yml
+---
+version: '3'
+services:
+  freqtrade1:
+    image: freqtradeorg/freqtrade:stable
+    # image: freqtradeorg/freqtrade:develop
+    # Use plotting image
+    # image: freqtradeorg/freqtrade:develop_plot
+    # Build step - only needed when additional dependencies are needed
+    # build:
+    #   context: .
+    #   dockerfile: "./docker/Dockerfile.custom"
+    restart: always
+    container_name: freqtrade1
+    volumes:
+      - "./user_data:/freqtrade/user_data"
+    # Expose api on port 8080 (localhost only)
+    # Please read the https://www.freqtrade.io/en/latest/rest-api/ documentation
+    # before enabling this.
+     ports:
+     - "127.0.0.1:8080:8080"
+    # Default command used when running `docker compose up`
+    command: >
+      trade
+      --logfile /freqtrade/user_data/logs/freqtrade1.log
+      --db-url sqlite:////freqtrade/user_data/tradesv3_freqtrade1.sqlite
+      --config /freqtrade/user_data/config.json
+      --config /freqtrade/user_data/config.freqtrade1.json
+      --strategy SampleStrategy
+  
+  freqtrade2:
+    image: freqtradeorg/freqtrade:stable
+    # image: freqtradeorg/freqtrade:develop
+    # Use plotting image
+    # image: freqtradeorg/freqtrade:develop_plot
+    # Build step - only needed when additional dependencies are needed
+    # build:
+    #   context: .
+    #   dockerfile: "./docker/Dockerfile.custom"
+    restart: always
+    container_name: freqtrade2
+    volumes:
+      - "./user_data:/freqtrade/user_data"
+    # Expose api on port 8080 (localhost only)
+    # Please read the https://www.freqtrade.io/en/latest/rest-api/ documentation
+    # before enabling this.
+    ports:
+      - "127.0.0.1:8081:8080"
+    # Default command used when running `docker compose up`
+    command: >
+      trade
+      --logfile /freqtrade/user_data/logs/freqtrade2.log
+      --db-url sqlite:////freqtrade/user_data/tradesv3_freqtrade2.sqlite
+      --config /freqtrade/user_data/config.json
+      --config /freqtrade/user_data/config.freqtrade2.json
+      --strategy SampleStrategy
+
+```
+You can use whatever naming convention you want, freqtrade1 and 2 are arbitrary. Note, that you will need to use different database files, port mappings and telegram configurations for each instance, as mentioned above. 
+
+
 ## Configure the bot running as a systemd service
 
 Copy the `freqtrade.service` file to your systemd user directory (usually `~/.config/systemd/user`) and update `WorkingDirectory` and `ExecStart` to match your setup.
@@ -111,12 +176,15 @@ Log messages are send to `syslog` with the `user` facility. So you can see them
 On many systems `syslog` (`rsyslog`) fetches data from `journald` (and vice versa), so both `--logfile syslog` or `--logfile journald` can be used and the messages be viewed with both `journalctl` and a syslog viewer utility. You can combine this in any way which suites you better.
 
 For `rsyslog` the messages from the bot can be redirected into a separate dedicated log file. To achieve this, add
+
 ```
 if $programname startswith "freqtrade" then -/var/log/freqtrade.log
 ```
+
 to one of the rsyslog configuration files, for example at the end of the `/etc/rsyslog.d/50-default.conf`.
 
 For `syslog` (`rsyslog`), the reduction mode can be switched on. This will reduce the number of repeating messages. For instance, multiple bot Heartbeat messages will be reduced to a single message when nothing else happens with the bot. To achieve this, set in `/etc/rsyslog.conf`:
+
 ```
 # Filter duplicated messages
 $RepeatedMsgReduction on
diff --git a/docs/assets/TokenBot-Freqtrade-banner.png b/docs/assets/TokenBot-Freqtrade-banner.png
new file mode 100644
index 000000000..6087056b6
Binary files /dev/null and b/docs/assets/TokenBot-Freqtrade-banner.png differ
diff --git a/docs/assets/frequi_url.png b/docs/assets/frequi_url.png
new file mode 100644
index 000000000..bd6ef52b6
Binary files /dev/null and b/docs/assets/frequi_url.png differ
diff --git a/docs/assets/plot-profit.png b/docs/assets/plot-profit.png
index 88d69a2d4..e9fe6c341 100644
Binary files a/docs/assets/plot-profit.png and b/docs/assets/plot-profit.png differ
diff --git a/docs/assets/windows_install.png b/docs/assets/windows_install.png
new file mode 100644
index 000000000..530c3047f
Binary files /dev/null and b/docs/assets/windows_install.png differ
diff --git a/docs/backtesting.md b/docs/backtesting.md
index 66e682745..5d836d01b 100644
--- a/docs/backtesting.md
+++ b/docs/backtesting.md
@@ -21,16 +21,18 @@ usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                              [--timeframe-detail TIMEFRAME_DETAIL]
                              [--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
                              [--export {none,trades}] [--export-filename PATH]
+                             [--breakdown {day,week,month} [{day,week,month} ...]]
+                             [--cache {none,day,week,month}]
 
 optional arguments:
   -h, --help            show this help message and exit
-  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
+  -i TIMEFRAME, --timeframe TIMEFRAME
                         Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
   --timerange TIMERANGE
                         Specify what timerange of data to use.
   --data-format-ohlcv {json,jsongz,hdf5}
                         Storage format for downloaded candle (OHLCV) data.
-                        (default: `None`).
+                        (default: `json`).
   --max-open-trades INT
                         Override the value of the `max_open_trades`
                         configuration setting.
@@ -61,12 +63,11 @@ optional arguments:
                         `30m`, `1h`, `1d`).
   --strategy-list STRATEGY_LIST [STRATEGY_LIST ...]
                         Provide a space-separated list of strategies to
-                        backtest. Please note that ticker-interval needs to be
+                        backtest. Please note that timeframe needs to be
                         set either in config or via command line. When using
                         this together with `--export trades`, the strategy-
                         name is injected into the filename (so `backtest-
-                        data.json` becomes `backtest-data-
-                        SampleStrategy.json`
+                        data.json` becomes `backtest-data-SampleStrategy.json`
   --export {none,trades}
                         Export backtest results (default: trades).
   --export-filename PATH
@@ -74,6 +75,11 @@ optional arguments:
                         Requires `--export` to be set as well. Example:
                         `--export-filename=user_data/backtest_results/backtest
                         _today.json`
+  --breakdown {day,week,month} [{day,week,month} ...]
+                        Show backtesting breakdown per [day, week, month].
+  --cache {none,day,week,month}
+                        Load a cached backtest result no older than specified
+                        age (default: day).
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
@@ -113,7 +119,7 @@ The result of backtesting will confirm if your bot has better odds of making a p
 All profit calculations include fees, and freqtrade will use the exchange's default fees for the calculation.
 
 !!! Warning "Using dynamic pairlists for backtesting"
-    Using dynamic pairlists is possible, however it relies on the current market conditions - which will not reflect the historic status of the pairlist.
+    Using dynamic pairlists is possible (not all of the handlers are allowed to be used in backtest mode), however it relies on the current market conditions - which will not reflect the historic status of the pairlist.
     Also, when using pairlists other than StaticPairlist, reproducibility of backtesting-results cannot be guaranteed.
     Please read the [pairlists documentation](plugins.md#pairlists) for more information.
 
@@ -268,55 +274,56 @@ A backtesting result will look like that:
 | XRP/BTC  |     35 |           0.66 |          22.96 |       0.00114897 |          11.48 | 3:49:00      |    12     0    23   34.3 |
 | ZEC/BTC  |     22 |          -0.46 |         -10.18 |      -0.00050971 |          -5.09 | 2:22:00      |     7     0    15   31.8 |
 | TOTAL    |    429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00      |   186     0   243   43.4 |
-========================================================= SELL REASON STATS ==========================================================
-| Sell Reason        |   Sells |  Wins |  Draws |  Losses |
+========================================================= EXIT REASON STATS ==========================================================
+| Exit Reason        |   Sells |  Wins |  Draws |  Losses |
 |:-------------------|--------:|------:|-------:|--------:|
 | trailing_stop_loss |     205 |   150 |      0 |      55 |
 | stop_loss          |     166 |     0 |      0 |     166 |
-| sell_signal        |      56 |    36 |      0 |      20 |
-| force_sell         |       2 |     0 |      0 |       2 |
+| exit_signal        |      56 |    36 |      0 |      20 |
+| force_exit         |       2 |     0 |      0 |       2 |
 ====================================================== LEFT OPEN TRADES REPORT ======================================================
 | Pair     |   Buys |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Win Draw Loss Win% |
 |:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|--------------------:|
 | ADA/BTC  |      1 |           0.89 |           0.89 |       0.00004434 |           0.44 | 6:00:00        |    1    0    0  100 |
 | LTC/BTC  |      1 |           0.68 |           0.68 |       0.00003421 |           0.34 | 2:00:00        |    1    0    0  100 |
 | TOTAL    |      2 |           0.78 |           1.57 |       0.00007855 |           0.78 | 4:00:00        |    2    0    0  100 |
-=============== SUMMARY METRICS ===============
-| Metric                | Value               |
-|-----------------------+---------------------|
-| Backtesting from      | 2019-01-01 00:00:00 |
-| Backtesting to        | 2019-05-01 00:00:00 |
-| Max open trades       | 3                   |
-|                       |                     |
-| Total/Daily Avg Trades| 429 / 3.575         |
-| Starting balance      | 0.01000000 BTC      |
-| Final balance         | 0.01762792 BTC      |
-| Absolute profit       | 0.00762792 BTC      |
-| Total profit %        | 76.2%               |
-| Trades per day        | 3.575               |
-| Avg. stake amount     | 0.001      BTC      |
-| Total trade volume    | 0.429      BTC      |
-|                       |                     |
-| Best Pair             | LSK/BTC 26.26%      |
-| Worst Pair            | ZEC/BTC -10.18%     |
-| Best Trade            | LSK/BTC 4.25%       |
-| Worst Trade           | ZEC/BTC -10.25%     |
-| Best day              | 0.00076 BTC         |
-| Worst day             | -0.00036 BTC        |
-| Days win/draw/lose    | 12 / 82 / 25        |
-| Avg. Duration Winners | 4:23:00             |
-| Avg. Duration Loser   | 6:55:00             |
-| Rejected Buy signals  | 3089                |
-|                       |                     |
-| Min balance           | 0.00945123 BTC      |
-| Max balance           | 0.01846651 BTC      |
-| Drawdown              | 50.63%              |
-| Drawdown              | 0.0015 BTC          |
-| Drawdown high         | 0.0013 BTC          |
-| Drawdown low          | -0.0002 BTC         |
-| Drawdown Start        | 2019-02-15 14:10:00 |
-| Drawdown End          | 2019-04-11 18:15:00 |
-| Market change         | -5.88%              |
+================ SUMMARY METRICS ===============
+| Metric                 | Value               |
+|------------------------+---------------------|
+| Backtesting from       | 2019-01-01 00:00:00 |
+| Backtesting to         | 2019-05-01 00:00:00 |
+| Max open trades        | 3                   |
+|                        |                     |
+| Total/Daily Avg Trades | 429 / 3.575         |
+| Starting balance       | 0.01000000 BTC      |
+| Final balance          | 0.01762792 BTC      |
+| Absolute profit        | 0.00762792 BTC      |
+| Total profit %         | 76.2%               |
+| Trades per day         | 3.575               |
+| Avg. stake amount      | 0.001      BTC      |
+| Total trade volume     | 0.429      BTC      |
+|                        |                     |
+| Best Pair              | LSK/BTC 26.26%      |
+| Worst Pair             | ZEC/BTC -10.18%     |
+| Best Trade             | LSK/BTC 4.25%       |
+| Worst Trade            | ZEC/BTC -10.25%     |
+| Best day               | 0.00076 BTC         |
+| Worst day              | -0.00036 BTC        |
+| Days win/draw/lose     | 12 / 82 / 25        |
+| Avg. Duration Winners  | 4:23:00             |
+| Avg. Duration Loser    | 6:55:00             |
+| Rejected Entry signals | 3089                |
+| Entry/Exit Timeouts    | 0 / 0               |
+|                        |                     |
+| Min balance            | 0.00945123 BTC      |
+| Max balance            | 0.01846651 BTC      |
+| Drawdown (Account)     | 13.33%              |
+| Drawdown               | 0.0015 BTC          |
+| Drawdown high          | 0.0013 BTC          |
+| Drawdown low           | -0.0002 BTC         |
+| Drawdown Start         | 2019-02-15 14:10:00 |
+| Drawdown End           | 2019-04-11 18:15:00 |
+| Market change          | -5.88%              |
 ===============================================
 ```
 
@@ -338,9 +345,9 @@ The column `Avg Profit %` shows the average profit for all trades made while the
 The column `Tot Profit %` shows instead the total profit % in relation to the starting balance.
 In the above results, we have a starting balance of 0.01 BTC and an absolute profit of 0.00762792 BTC - so the `Tot Profit %` will be `(0.00762792 / 0.01) * 100 ~= 76.2%`.
 
-Your strategy performance is influenced by your buy strategy, your sell strategy, and also by the `minimal_roi` and `stop_loss` you have set.
+Your strategy performance is influenced by your buy strategy, your exit strategy, and also by the `minimal_roi` and `stop_loss` you have set.
 
-For example, if your `minimal_roi` is only `"0":  0.01` you cannot expect the bot to make more profit than 1% (because it will sell every time a trade reaches 1%).
+For example, if your `minimal_roi` is only `"0":  0.01` you cannot expect the bot to make more profit than 1% (because it will exit every time a trade reaches 1%).
 
 ```json
 "minimal_roi": {
@@ -352,14 +359,14 @@ On the other hand, if you set a too high `minimal_roi` like `"0":  0.55`
 (55%), there is almost no chance that the bot will ever reach this profit.
 Hence, keep in mind that your performance is an integral mix of all different elements of the strategy, your configuration, and the crypto-currency pairs you have set up.
 
-### Sell reasons table
+### Exit reasons table
 
-The 2nd table contains a recap of sell reasons.
-This table can tell you which area needs some additional work (e.g. all or many of the `sell_signal` trades are losses, so you should work on improving the sell signal, or consider disabling it).
+The 2nd table contains a recap of exit reasons.
+This table can tell you which area needs some additional work (e.g. all or many of the `exit_signal` trades are losses, so you should work on improving the exit signal, or consider disabling it).
 
 ### Left open trades table
 
-The 3rd table contains all trades the bot had to `forcesell` at the end of the backtesting period to present you the full picture.
+The 3rd table contains all trades the bot had to `force_exit` at the end of the backtesting period to present you the full picture.
 This is necessary to simulate realistic behavior, since the backtest period has to end at some point, while realistically, you could leave the bot running forever.
 These trades are also included in the first table, but are also shown separately in this table for clarity.
 
@@ -369,42 +376,49 @@ The last element of the backtest report is the summary metrics table.
 It contains some useful key metrics about performance of your strategy on backtesting data.
 
 ```
-=============== SUMMARY METRICS ===============
-| Metric                | Value               |
-|-----------------------+---------------------|
-| Backtesting from      | 2019-01-01 00:00:00 |
-| Backtesting to        | 2019-05-01 00:00:00 |
-| Max open trades       | 3                   |
-|                       |                     |
-| Total/Daily Avg Trades| 429 / 3.575         |
-| Starting balance      | 0.01000000 BTC      |
-| Final balance         | 0.01762792 BTC      |
-| Absolute profit       | 0.00762792 BTC      |
-| Total profit %        | 76.2%               |
-| Avg. stake amount     | 0.001      BTC      |
-| Total trade volume    | 0.429      BTC      |
-|                       |                     |
-| Best Pair             | LSK/BTC 26.26%      |
-| Worst Pair            | ZEC/BTC -10.18%     |
-| Best Trade            | LSK/BTC 4.25%       |
-| Worst Trade           | ZEC/BTC -10.25%     |
-| Best day              | 0.00076 BTC         |
-| Worst day             | -0.00036 BTC        |
-| Days win/draw/lose    | 12 / 82 / 25        |
-| Avg. Duration Winners | 4:23:00             |
-| Avg. Duration Loser   | 6:55:00             |
-| Rejected Buy signals  | 3089                |
-|                       |                     |
-| Min balance           | 0.00945123 BTC      |
-| Max balance           | 0.01846651 BTC      |
-| Drawdown              | 50.63%              |
-| Drawdown              | 0.0015 BTC          |
-| Drawdown high         | 0.0013 BTC          |
-| Drawdown low          | -0.0002 BTC         |
-| Drawdown Start        | 2019-02-15 14:10:00 |
-| Drawdown End          | 2019-04-11 18:15:00 |
-| Market change         | -5.88%              |
-===============================================
+================ SUMMARY METRICS ===============
+| Metric                 | Value               |
+|------------------------+---------------------|
+| Backtesting from       | 2019-01-01 00:00:00 |
+| Backtesting to         | 2019-05-01 00:00:00 |
+| Max open trades        | 3                   |
+|                        |                     |
+| Total/Daily Avg Trades | 429 / 3.575         |
+| Starting balance       | 0.01000000 BTC      |
+| Final balance          | 0.01762792 BTC      |
+| Absolute profit        | 0.00762792 BTC      |
+| Total profit %         | 76.2%               |
+| Avg. stake amount      | 0.001      BTC      |
+| Total trade volume     | 0.429      BTC      |
+|                        |                     |
+| Long / Short           | 352 / 77            |
+| Total profit Long %    | 1250.58%            |
+| Total profit Short %   | -15.02%             |
+| Absolute profit Long   | 0.00838792 BTC      |
+| Absolute profit Short  | -0.00076 BTC        |
+|                        |                     |
+| Best Pair              | LSK/BTC 26.26%      |
+| Worst Pair             | ZEC/BTC -10.18%     |
+| Best Trade             | LSK/BTC 4.25%       |
+| Worst Trade            | ZEC/BTC -10.25%     |
+| Best day               | 0.00076 BTC         |
+| Worst day              | -0.00036 BTC        |
+| Days win/draw/lose     | 12 / 82 / 25        |
+| Avg. Duration Winners  | 4:23:00             |
+| Avg. Duration Loser    | 6:55:00             |
+| Rejected Entry signals | 3089                |
+| Entry/Exit Timeouts    | 0 / 0               |
+|                        |                     |
+| Min balance            | 0.00945123 BTC      |
+| Max balance            | 0.01846651 BTC      |
+| Drawdown (Account)     | 13.33%              |
+| Drawdown               | 0.0015 BTC          |
+| Drawdown high          | 0.0013 BTC          |
+| Drawdown low           | -0.0002 BTC         |
+| Drawdown Start         | 2019-02-15 14:10:00 |
+| Drawdown End           | 2019-04-11 18:15:00 |
+| Market change          | -5.88%              |
+================================================
 
 ```
 
@@ -422,17 +436,55 @@ It contains some useful key metrics about performance of your strategy on backte
 - `Best day` / `Worst day`: Best and worst day based on daily profit.
 - `Days win/draw/lose`: Winning / Losing days (draws are usually days without closed trade).
 - `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades.
-- `Rejected Buy signals`: Buy signals that could not be acted upon due to max_open_trades being reached.
+- `Rejected Entry signals`: Trade entry signals that could not be acted upon due to `max_open_trades` being reached.
+- `Entry/Exit Timeouts`: Entry/exit orders which did not fill (only applicable if custom pricing is used).
 - `Min balance` / `Max balance`: Lowest and Highest Wallet balance during the backtest period.
-- `Drawdown`: Maximum drawdown experienced. For example, the value of 50% means that from highest to subsequent lowest point, a 50% drop was experienced).
+- `Drawdown (Account)`: Maximum Account Drawdown experienced. Calculated as $(Absolute Drawdown) / (DrawdownHigh + startingBalance)$.
+- `Drawdown`: Maximum, absolute drawdown experienced. Difference between Drawdown High and Subsequent Low point.
 - `Drawdown high` / `Drawdown low`: Profit at the beginning and end of the largest drawdown period. A negative low value means initial capital lost.
 - `Drawdown Start` / `Drawdown End`: Start and end datetime for this largest drawdown (can also be visualized via the `plot-dataframe` sub-command).
 - `Market change`: Change of the market during the backtest period. Calculated as average of all pairs changes from the first to the last candle using the "close" column.
+- `Long / Short`: Split long/short values (Only shown when short trades were made).
+- `Total profit Long %` / `Absolute profit Long`: Profit long trades only (Only shown when short trades were made).
+- `Total profit Short %` / `Absolute profit Short`: Profit short trades only (Only shown when short trades were made).
+
+### Daily / Weekly / Monthly breakdown
+
+You can get an overview over daily / weekly or monthly results by using the `--breakdown <>` switch.
+
+To visualize daily and weekly breakdowns, you can use the following:
+
+``` bash
+freqtrade backtesting --strategy MyAwesomeStrategy --breakdown day month
+```
+
+``` output
+======================== DAY BREAKDOWN =========================
+|        Day |   Tot Profit USDT |   Wins |   Draws |   Losses |
+|------------+-------------------+--------+---------+----------|
+| 03/07/2021 |           200.0   |      2 |       0 |        0 |
+| 04/07/2021 |           -50.31  |      0 |       0 |        2 |
+| 05/07/2021 |           220.611 |      3 |       2 |        0 |
+| 06/07/2021 |           150.974 |      3 |       0 |        2 |
+| 07/07/2021 |           -70.193 |      1 |       0 |        2 |
+| 08/07/2021 |           212.413 |      2 |       0 |        3 |
+
+```
+
+The output will show a table containing the realized absolute Profit (in stake currency) for the given timeperiod, as well as wins, draws and losses that materialized (closed) on this day.
+
+### Backtest result caching
+
+To save time, by default backtest will reuse a cached result from within the last day when the backtested strategy and config match that of a previous backtest. To force a new backtest despite existing result for an identical run specify `--cache none` parameter.
+
+!!! Warning
+    Caching is automatically disabled for open-ended timeranges (`--timerange 20210101-`), as freqtrade cannot ensure reliably that the underlying data didn't change. It can also use cached results where it shouldn't if the original backtest had missing data at the end, which was fixed by downloading more data.
+    In this instance, please use `--cache none` once to force a fresh backtest.
 
 ### Further backtest-result analysis
 
 To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
-You can then load the trades to perform further analysis as shown in our [data analysis](data-analysis.md#backtesting) backtesting section.
+You can then load the trades to perform further analysis as shown in the [data analysis](data-analysis.md#backtesting) backtesting section.
 
 ## Assumptions made by backtesting
 
@@ -440,24 +492,25 @@ Since backtesting lacks some detailed information about what happens within a ca
 
 - Buys happen at open-price
 - All orders are filled at the requested price (no slippage, no unfilled orders)
-- Sell-signal sells happen at open-price of the consecutive candle
-- Sell-signal is favored over Stoploss, because sell-signals are assumed to trigger on candle's open
+- Exit-signal exits happen at open-price of the consecutive candle
+- Exit-signal is favored over Stoploss, because exit-signals are assumed to trigger on candle's open
 - ROI
-  - sells are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the sell will be at 2%)
-  - sells are never "below the candle", so a ROI of 2% may result in a sell at 2.4% if low was at 2.4% profit
-  - Forcesells caused by `<N>=-1` ROI entries use low as sell value, unless N falls on the candle open (e.g. `120: -1` for 1h candles)
-- Stoploss sells happen exactly at stoploss price, even if low was lower, but the loss will be `2 * fees` higher than the stoploss price
-- Stoploss is evaluated before ROI within one candle. So you can often see more trades with the `stoploss` sell reason comparing to the results obtained with the same strategy in the Dry Run/Live Trade modes
+  - exits are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the exit will be at 2%)
+  - exits are never "below the candle", so a ROI of 2% may result in a exit at 2.4% if low was at 2.4% profit
+  - Forceexits caused by `<N>=-1` ROI entries use low as exit value, unless N falls on the candle open (e.g. `120: -1` for 1h candles)
+- Stoploss exits happen exactly at stoploss price, even if low was lower, but the loss will be `2 * fees` higher than the stoploss price
+- Stoploss is evaluated before ROI within one candle. So you can often see more trades with the `stoploss` exit reason comparing to the results obtained with the same strategy in the Dry Run/Live Trade modes
 - Low happens before high for stoploss, protecting capital first
 - Trailing stoploss
   - Trailing Stoploss is only adjusted if it's below the candle's low (otherwise it would be triggered)
+  - On trade entry candles that trigger trailing stoploss, the "minimum offset" (`stop_positive_offset`) is assumed (instead of high) - and the stop is calculated from this point
   - High happens first - adjusting stoploss
-  - Low uses the adjusted stoploss (so sells with large high-low difference are backtested correctly)
+  - Low uses the adjusted stoploss (so exits with large high-low difference are backtested correctly)
   - ROI applies before trailing-stop, ensuring profits are "top-capped" at ROI if both ROI and trailing stop applies
-- Sell-reason does not explain if a trade was positive or negative, just what triggered the sell (this can look odd if negative ROI values are used)
+- Exit-reason does not explain if a trade was positive or negative, just what triggered the exit (this can look odd if negative ROI values are used)
 - Evaluation sequence (if multiple signals happen on the same candle)
+  - Exit-signal
   - ROI (if not stoploss)
-  - Sell-signal
   - Stoploss
 
 Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will **never** replace running a strategy in dry-run mode.
@@ -480,7 +533,7 @@ freqtrade backtesting --strategy AwesomeStrategy --timeframe 1h --timeframe-deta
 ```
 
 This will load 1h data as well as 5m data for the timeframe. The strategy will be analyzed with the 1h timeframe - and for every "open trade candle" (candles where a trade is open) the 5m data will be used to simulate intra-candle movements.
-All callback functions (`custom_sell()`, `custom_stoploss()`, ... ) will be running for each 5m candle once the trade is opened (so 12 times in the above example of 1h timeframe, and 5m detailed timeframe).
+All callback functions (`custom_exit()`, `custom_stoploss()`, ... ) will be running for each 5m candle once the trade is opened (so 12 times in the above example of 1h timeframe, and 5m detailed timeframe).
 
 `--timeframe-detail` must be smaller than the original timeframe, otherwise backtesting will fail to start.
 
diff --git a/docs/bot-basics.md b/docs/bot-basics.md
index 80443a0bf..e45e3d9ca 100644
--- a/docs/bot-basics.md
+++ b/docs/bot-basics.md
@@ -24,25 +24,27 @@ By default, loop runs every few seconds (`internals.process_throttle_secs`) and
 
 * Fetch open trades from persistence.
 * Calculate current list of tradable pairs.
-* Download ohlcv data for the pairlist including all [informative pairs](strategy-customization.md#get-data-for-non-tradeable-pairs)  
+* Download OHLCV data for the pairlist including all [informative pairs](strategy-customization.md#get-data-for-non-tradeable-pairs)  
   This step is only executed once per Candle to avoid unnecessary network traffic.
 * Call `bot_loop_start()` strategy callback.
 * Analyze strategy per pair.
   * Call `populate_indicators()`
-  * Call `populate_buy_trend()`
-  * Call `populate_sell_trend()`
+  * Call `populate_entry_trend()`
+  * Call `populate_exit_trend()`
 * Check timeouts for open orders.
-  * Calls `check_buy_timeout()` strategy callback for open buy orders.
-  * Calls `check_sell_timeout()` strategy callback for open sell orders.
-* Verifies existing positions and eventually places sell orders.
-  * Considers stoploss, ROI and sell-signal, `custom_sell()` and `custom_stoploss()`.
-  * Determine sell-price based on `ask_strategy` configuration setting or by using the `custom_exit_price()` callback.
-  * Before a sell order is placed, `confirm_trade_exit()` strategy callback is called.
+  * Calls `check_entry_timeout()` strategy callback for open entry orders.
+  * Calls `check_exit_timeout()` strategy callback for open exit orders.
+* Verifies existing positions and eventually places exit orders.
+  * Considers stoploss, ROI and exit-signal, `custom_exit()` and `custom_stoploss()`.
+  * Determine exit-price based on `exit_pricing` configuration setting or by using the `custom_exit_price()` callback.
+  * Before a exit order is placed, `confirm_trade_exit()` strategy callback is called.
+* Check position adjustments for open trades if enabled by calling `adjust_trade_position()` and place additional order if required.
 * Check if trade-slots are still available (if `max_open_trades` is reached).
-* Verifies buy signal trying to enter new positions.
-  * Determine buy-price based on `bid_strategy` configuration setting, or by using the `custom_entry_price()` callback.
+* Verifies entry signal trying to enter new positions.
+  * Determine entry-price based on `entry_pricing` configuration setting, or by using the `custom_entry_price()` callback.
+  * In Margin and Futures mode, `leverage()` strategy callback is called to determine the desired leverage.
   * Determine stake size by calling the `custom_stake_amount()` callback.
-  * Before a buy order is placed, `confirm_trade_entry()` strategy callback is called.
+  * Before an entry order is placed, `confirm_trade_entry()` strategy callback is called.
 
 This loop will be repeated again and again until the bot is stopped.
 
@@ -53,10 +55,17 @@ This loop will be repeated again and again until the bot is stopped.
 * Load historic data for configured pairlist.
 * Calls `bot_loop_start()` once.
 * Calculate indicators (calls `populate_indicators()` once per pair).
-* Calculate buy / sell signals (calls `populate_buy_trend()` and `populate_sell_trend()` once per pair).
+* Calculate entry / exit signals (calls `populate_entry_trend()` and `populate_exit_trend()` once per pair).
 * Loops per candle simulating entry and exit points.
-  * Confirm trade buy / sell (calls `confirm_trade_entry()` and `confirm_trade_exit()` if implemented in the strategy).
-  * Call `custom_stoploss()` and `custom_sell()` to find custom exit points.
+  * Check for Order timeouts, either via the `unfilledtimeout` configuration, or via `check_entry_timeout()` / `check_exit_timeout()` strategy callbacks.
+  * Check for trade entry signals (`enter_long` / `enter_short` columns).
+  * Confirm trade entry / exits (calls `confirm_trade_entry()` and `confirm_trade_exit()` if implemented in the strategy).
+  * Call `custom_entry_price()` (if implemented in the strategy) to determine entry price (Prices are moved to be within the opening candle).
+  * In Margin and Futures mode, `leverage()` strategy callback is called to determine the desired leverage.
+  * Determine stake size by calling the `custom_stake_amount()` callback.
+  * Check position adjustments for open trades if enabled and call `adjust_trade_position()` to determine if an additional order is requested.
+  * Call `custom_stoploss()` and `custom_exit()` to find custom exit points.
+  * For exits based on exit-signal and custom-exit: Call `custom_exit_price()` to determine exit price (Prices are moved to be within the closing candle).
 * Generate backtest report output
 
 !!! Note
diff --git a/docs/configuration.md b/docs/configuration.md
index 6ccea4c73..369c4e2dd 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -37,6 +37,15 @@ Using this scheme, all configuration settings will also be available as environm
 
 Please note that Environment variables will overwrite corresponding settings in your configuration, but command line Arguments will always win.
 
+Common example:
+
+```
+FREQTRADE__TELEGRAM__CHAT_ID=<telegramchatid>
+FREQTRADE__TELEGRAM__TOKEN=<telegramToken>
+FREQTRADE__EXCHANGE__KEY=<yourExchangeKey>
+FREQTRADE__EXCHANGE__SECRET=<yourExchangeSecret>
+```
+
 !!! Note
     Environment variables detected are logged at startup - so if you can't find why a value is not what you think it should be based on the configuration, make sure it's not loaded from an environment variable.
 
@@ -44,14 +53,63 @@ Please note that Environment variables will overwrite corresponding settings in
 
 Multiple configuration files can be specified and used by the bot or the bot can read its configuration parameters from the process standard input stream.
 
+You can specify additional configuration files in `add_config_files`. Files specified in this parameter will be loaded and merged with the initial config file. The files are resolved relative to the initial configuration file.
+This is similar to using multiple `--config` parameters, but simpler in usage as you don't have to specify all files for all commands.
+
 !!! Tip "Use multiple configuration files to keep secrets secret"
     You can use a 2nd configuration file containing your secrets. That way you can share your "primary" configuration file, while still keeping your API keys for yourself.
 
+    ``` json title="user_data/config.json"
+    "add_config_files": [
+        "config-private.json"
+    ]
+    ```
+    
+    ``` bash
+    freqtrade trade --config user_data/config.json <...>
+    ```
+
+    The 2nd file should only specify what you intend to override.
+    If a key is in more than one of the configurations, then the "last specified configuration" wins (in the above example, `config-private.json`).
+
+    For one-off commands, you can also use the below syntax by specifying multiple "--config" parameters.
+
     ``` bash
     freqtrade trade --config user_data/config.json --config user_data/config-private.json <...>
     ```
-    The 2nd file should only specify what you intend to override.
-    If a key is in more than one of the configurations, then the "last specified configuration" wins (in the above example, `config-private.json`).
+
+    This is equivalent to the example above - but `config-private.json` is specified as cli argument.
+
+??? Note "config collision handling"
+    If the same configuration setting takes place in both `config.json` and `config-import.json`, then the parent configuration wins.
+    In the below case, `max_open_trades` would be 3 after the merging - as the reusable "import" configuration has this key overwritten.
+
+    ``` json title="user_data/config.json"
+    {
+        "max_open_trades": 3,
+        "stake_currency": "USDT",
+        "add_config_files": [
+            "config-import.json"
+        ]
+    }
+    ```
+
+    ``` json title="user_data/config-import.json"
+    {
+        "max_open_trades": 10,
+        "stake_amount": "unlimited",
+    }
+    ```
+    
+    Resulting combined configuration:
+
+    ``` json title="Result"
+    {
+        "max_open_trades": 10,
+        "stake_currency": "USDT",
+        "stake_amount": "unlimited"
+    }
+    ```
 
 ## Configuration parameters
 
@@ -77,53 +135,59 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `amend_last_stake_amount` | Use reduced last stake amount if necessary. [More information below](#configuring-amount-per-trade). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
 | `last_stake_amount_min_ratio` | Defines minimum stake amount that has to be left and executed. Applies only to the last stake amount when it's amended to a reduced value (i.e. if `amend_last_stake_amount` is set to `true`). [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.5`.* <br> **Datatype:** Float (as ratio)
 | `amount_reserve_percent` | Reserve some amount in min pair stake amount. The bot will reserve `amount_reserve_percent` + stoploss value when calculating min pair stake amount in order to avoid possible trade refusals. <br>*Defaults to `0.05` (5%).* <br> **Datatype:** Positive Float as ratio.
-| `timeframe` | The timeframe (former ticker interval) to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
+| `timeframe` | The timeframe to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
 | `fiat_display_currency` | Fiat currency used to show your profits. [More information below](#what-values-can-be-used-for-fiat_display_currency). <br> **Datatype:** String
 | `dry_run` | **Required.** Define if the bot must be in Dry Run or production mode. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
 | `dry_run_wallet` | Define the starting amount in stake currency for the simulated wallet used by the bot running in Dry Run mode.<br>*Defaults to `1000`.* <br> **Datatype:** Float
 | `cancel_open_orders_on_exit` | Cancel open orders when the `/stop` RPC command is issued, `Ctrl+C` is pressed or the bot dies unexpectedly. When set to `true`, this allows you to use `/stop` to cancel unfilled and partially filled orders in the event of a market crash. It does not impact open positions. <br>*Defaults to `false`.* <br> **Datatype:** Boolean
 | `process_only_new_candles` | Enable processing of indicators only when new candles arrive. If false each loop populates the indicators, this will mean the same candle is processed many times creating system load but can be useful of your strategy depends on tick data not only candle. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*  <br> **Datatype:** Boolean
-| `minimal_roi` | **Required.** Set the threshold as ratio the bot will use to sell a trade. [More information below](#understand-minimal_roi). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
+| `minimal_roi` | **Required.** Set the threshold as ratio the bot will use to exit a trade. [More information below](#understand-minimal_roi). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
 | `stoploss` |  **Required.** Value as ratio of the stoploss used by the bot. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).  <br> **Datatype:** Float (as ratio)
 | `trailing_stop` | Enables trailing stoploss (based on `stoploss` in either configuration or strategy file). More details in the [stoploss documentation](stoploss.md#trailing-stop-loss). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Boolean
 | `trailing_stop_positive` | Changes stoploss once profit has been reached. More details in the [stoploss documentation](stoploss.md#trailing-stop-loss-custom-positive-loss). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Float
 | `trailing_stop_positive_offset` | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive. More details in the [stoploss documentation](stoploss.md#trailing-stop-loss-only-once-the-trade-has-reached-a-certain-offset). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0` (no offset).* <br> **Datatype:** Float
 | `trailing_only_offset_is_reached` | Only apply trailing stoploss when the offset is reached. [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*  <br> **Datatype:** Boolean
 | `fee` | Fee used during backtesting / dry-runs. Should normally not be configured, which has freqtrade fall back to the exchange default fee. Set as ratio (e.g. 0.001 = 0.1%). Fee is applied twice for each trade, once when buying, once when selling. <br> **Datatype:** Float (as ratio)
-| `unfilledtimeout.buy` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
-| `unfilledtimeout.sell` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
+| `trading_mode` | Specifies if you want to trade regularly, trade with leverage, or trade contracts whose prices are derived from matching cryptocurrency prices. [leverage documentation](leverage.md). <br>*Defaults to `"spot"`.*  <br> **Datatype:** String
+| `margin_mode` | When trading with leverage, this determines if the collateral owned by the trader will be shared or isolated to each trading pair [leverage documentation](leverage.md). <br> **Datatype:** String
+| `liquidation_buffer` | A ratio specifying how large of a safety net to place between the liquidation price and the stoploss to prevent a position from reaching the liquidation price [leverage documentation](leverage.md). <br>*Defaults to `0.05`.*  <br> **Datatype:** Float
+| `unfilledtimeout.entry` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled entry order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
+| `unfilledtimeout.exit` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled exit order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
 | `unfilledtimeout.unit` | Unit to use in unfilledtimeout setting. Note: If you set unfilledtimeout.unit to "seconds", "internals.process_throttle_secs" must be inferior or equal to timeout [Strategy Override](#parameters-in-the-strategy). <br> *Defaults to `minutes`.* <br> **Datatype:** String
-| `bid_strategy.price_side` | Select the side of the spread the bot should look at to get the buy rate. [More information below](#buy-price-side).<br> *Defaults to `bid`.* <br> **Datatype:** String (either `ask` or `bid`).
-| `bid_strategy.ask_last_balance` | **Required.** Interpolate the bidding price. More information [below](#buy-price-without-orderbook-enabled).
-| `bid_strategy.use_order_book` | Enable buying using the rates in [Order Book Bids](#buy-price-with-orderbook-enabled). <br> **Datatype:** Boolean
-| `bid_strategy.order_book_top` | Bot will use the top N rate in Order Book "price_side" to buy. I.e. a value of 2 will allow the bot to pick the 2nd bid rate in [Order Book Bids](#buy-price-with-orderbook-enabled). <br>*Defaults to `1`.*  <br> **Datatype:** Positive Integer
-| `bid_strategy. check_depth_of_market.enabled` | Do not buy if the difference of buy orders and sell orders is met in Order Book. [Check market depth](#check-depth-of-market). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
-| `bid_strategy. check_depth_of_market.bids_to_ask_delta` | The difference ratio of buy orders and sell orders found in Order Book. A value below 1 means sell order size is greater, while value greater than 1 means buy order size is higher. [Check market depth](#check-depth-of-market) <br> *Defaults to `0`.*  <br> **Datatype:** Float (as ratio)
-| `ask_strategy.price_side` | Select the side of the spread the bot should look at to get the sell rate. [More information below](#sell-price-side).<br> *Defaults to `ask`.* <br> **Datatype:** String (either `ask` or `bid`).
-| `ask_strategy.bid_last_balance` | Interpolate the selling price. More information [below](#sell-price-without-orderbook-enabled).
-| `ask_strategy.use_order_book` | Enable selling of open trades using [Order Book Asks](#sell-price-with-orderbook-enabled). <br> **Datatype:** Boolean
-| `ask_strategy.order_book_top` | Bot will use the top N rate in Order Book "price_side" to sell. I.e. a value of 2 will allow the bot to pick the 2nd ask rate in [Order Book Asks](#sell-price-with-orderbook-enabled)<br>*Defaults to `1`.* <br> **Datatype:** Positive Integer
-| `use_sell_signal` | Use sell signals produced by the strategy in addition to the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `true`.* <br> **Datatype:** Boolean
-| `sell_profit_only` | Wait until the bot reaches `sell_profit_offset` before taking a sell decision. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
-| `sell_profit_offset` | Sell-signal is only active above this value. Only active in combination with `sell_profit_only=True`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0`.* <br> **Datatype:** Float (as ratio)
-| `ignore_roi_if_buy_signal` | Do not sell if the buy signal is still active. This setting takes preference over `minimal_roi` and `use_sell_signal`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `unfilledtimeout.exit_timeout_count` | How many times can exit orders time out. Once this number of timeouts is reached, an emergency exit is triggered. 0 to disable and allow unlimited order cancels. [Strategy Override](#parameters-in-the-strategy).<br>*Defaults to `0`.* <br> **Datatype:** Integer
+| `entry_pricing.price_side` | Select the side of the spread the bot should look at to get the entry rate. [More information below](#buy-price-side).<br> *Defaults to `same`.* <br> **Datatype:** String (either `ask`, `bid`, `same` or `other`).
+| `entry_pricing.price_last_balance` | **Required.** Interpolate the bidding price. More information [below](#entry-price-without-orderbook-enabled).
+| `entry_pricing.use_order_book` | Enable entering using the rates in [Order Book Entry](#entry-price-with-orderbook-enabled). <br> *Defaults to `True`.*<br> **Datatype:** Boolean
+| `entry_pricing.order_book_top` | Bot will use the top N rate in Order Book "price_side" to enter a trade. I.e. a value of 2 will allow the bot to pick the 2nd entry in [Order Book Entry](#entry-price-with-orderbook-enabled). <br>*Defaults to `1`.*  <br> **Datatype:** Positive Integer
+| `entry_pricing. check_depth_of_market.enabled` | Do not enter if the difference of buy orders and sell orders is met in Order Book. [Check market depth](#check-depth-of-market). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `entry_pricing. check_depth_of_market.bids_to_ask_delta` | The difference ratio of buy orders and sell orders found in Order Book. A value below 1 means sell order size is greater, while value greater than 1 means buy order size is higher. [Check market depth](#check-depth-of-market) <br> *Defaults to `0`.*  <br> **Datatype:** Float (as ratio)
+| `exit_pricing.price_side` | Select the side of the spread the bot should look at to get the exit rate. [More information below](#exit-price-side).<br> *Defaults to `same`.* <br> **Datatype:** String (either `ask`, `bid`, `same` or `other`).
+| `exit_pricing.price_last_balance` | Interpolate the exiting price. More information [below](#exit-price-without-orderbook-enabled).
+| `exit_pricing.use_order_book` | Enable exiting of open trades using [Order Book Exit](#exit-price-with-orderbook-enabled). <br> *Defaults to `True`.*<br> **Datatype:** Boolean
+| `exit_pricing.order_book_top` | Bot will use the top N rate in Order Book "price_side" to exit. I.e. a value of 2 will allow the bot to pick the 2nd ask rate in [Order Book Exit](#exit-price-with-orderbook-enabled)<br>*Defaults to `1`.* <br> **Datatype:** Positive Integer
+| `use_exit_signal` | Use exit signals produced by the strategy in addition to the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `true`.* <br> **Datatype:** Boolean
+| `exit_profit_only` | Wait until the bot reaches `exit_profit_offset` before taking an exit decision. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `exit_profit_offset` | Exit-signal is only active above this value. Only active in combination with `exit_profit_only=True`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0`.* <br> **Datatype:** Float (as ratio)
+| `ignore_roi_if_entry_signal` | Do not exit if the entry signal is still active. This setting takes preference over `minimal_roi` and `use_exit_signal`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
 | `ignore_buying_expired_candle_after` | Specifies the number of seconds until a buy signal is no longer used. <br> **Datatype:** Integer
-| `order_types` | Configure order-types depending on the action (`"buy"`, `"sell"`, `"stoploss"`, `"stoploss_on_exchange"`). [More information below](#understand-order_types). [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Dict
-| `order_time_in_force` | Configure time in force for buy and sell orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
+| `order_types` | Configure order-types depending on the action (`"entry"`, `"exit"`, `"stoploss"`, `"stoploss_on_exchange"`). [More information below](#understand-order_types). [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Dict
+| `order_time_in_force` | Configure time in force for entry and exit orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
 | `custom_price_max_distance_ratio` | Configure maximum distance ratio between current and custom entry or exit price. <br>*Defaults to `0.02` 2%).*<br> **Datatype:** Positive float
 | `exchange.name` | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename). <br> **Datatype:** String
 | `exchange.sandbox` | Use the 'sandbox' version of the exchange, where the exchange provides a sandbox for risk-free integration. See [here](sandbox-testing.md) in more details.<br> **Datatype:** Boolean
 | `exchange.key` | API key to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.secret` | API secret to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.password` | API password to use for the exchange. Only required when you are in production mode and for exchanges that use password for API requests.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
+| `exchange.uid` | API uid to use for the exchange. Only required when you are in production mode and for exchanges that use uid for API requests.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.pair_whitelist` | List of pairs to use by the bot for trading and to check for potential trades during backtesting. Supports regex pairs as `.*/BTC`. Not used by VolumePairList. [More information](plugins.md#pairlists-and-pairlist-handlers). <br> **Datatype:** List
 | `exchange.pair_blacklist` | List of pairs the bot must absolutely avoid for trading and backtesting. [More information](plugins.md#pairlists-and-pairlist-handlers). <br> **Datatype:** List
-| `exchange.ccxt_config` | Additional CCXT parameters passed to both ccxt instances (sync and async). This is usually the correct place for ccxt configurations. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
+| `exchange.ccxt_config` | Additional CCXT parameters passed to both ccxt instances (sync and async). This is usually the correct place for additional ccxt configurations. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation). Please avoid adding exchange secrets here (use the dedicated fields instead), as they may be contained in logs. <br> **Datatype:** Dict
 | `exchange.ccxt_sync_config` | Additional CCXT parameters passed to the regular (sync) ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
 | `exchange.ccxt_async_config` | Additional CCXT parameters passed to the async ccxt instance. Parameters may differ from exchange to exchange  and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
 | `exchange.markets_refresh_interval` | The interval in minutes in which markets are reloaded. <br>*Defaults to `60` minutes.* <br> **Datatype:** Positive Integer
 | `exchange.skip_pair_validation` | Skip pairlist validation on startup.<br>*Defaults to `false`<br> **Datatype:** Boolean
 | `exchange.skip_open_order_update` | Skips open order updates on startup should the exchange cause problems. Only relevant in live conditions.<br>*Defaults to `false`<br> **Datatype:** Boolean
+| `exchange.unknown_fee_rate` | Fallback value to use when calculating trading fees. This can be useful for exchanges which have fees in non-tradable currencies. The value provided here will be multiplied with the "fee cost".<br>*Defaults to `None`<br> **Datatype:** float
 | `exchange.log_responses` | Log relevant exchange responses. For debug mode only - use with care.<br>*Defaults to `false`<br> **Datatype:** Boolean
 | `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation.
 | `experimental.block_bad_exchanges` | Block exchanges known to not work with freqtrade. Leave on default unless you want to test if that exchange works now. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
@@ -135,10 +199,12 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `telegram.balance_dust_level` | Dust-level (in stake currency) - currencies with a balance below this will not be shown by `/balance`. <br> **Datatype:** float
 | `webhook.enabled` | Enable usage of Webhook notifications <br> **Datatype:** Boolean
 | `webhook.url` | URL for the webhook. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
-| `webhook.webhookbuy` | Payload to send on buy. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
-| `webhook.webhookbuycancel` | Payload to send on buy order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
-| `webhook.webhooksell` | Payload to send on sell. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
-| `webhook.webhooksellcancel` | Payload to send on sell order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhookentry` | Payload to send on entry. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhookentrycancel` | Payload to send on entry order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhookentryfill` | Payload to send on entry order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhookexit` | Payload to send on exit. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhookexitcancel` | Payload to send on exit order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhookexitfill` | Payload to send on exit order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
 | `webhook.webhookstatus` | Payload to send on status calls. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
 | `api_server.enabled` | Enable usage of API Server. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** Boolean
 | `api_server.listen_ip_address` | Bind IP address. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** IPv4
@@ -149,7 +215,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `bot_name` | Name of the bot. Passed via API to a client - can be shown to distinguish / name bots.<br> *Defaults to `freqtrade`*<br> **Datatype:** String
 | `db_url` | Declares database URL to use. NOTE: This defaults to `sqlite:///tradesv3.dryrun.sqlite` if `dry_run` is `true`, and to `sqlite:///tradesv3.sqlite` for production instances. <br> **Datatype:** String, SQLAlchemy connect string
 | `initial_state` | Defines the initial application state. If set to stopped, then the bot has to be explicitly started via `/start` RPC command. <br>*Defaults to `stopped`.* <br> **Datatype:** Enum, either `stopped` or `running`
-| `forcebuy_enable` | Enables the RPC Commands to force a buy. More information below. <br> **Datatype:** Boolean
+| `force_entry_enable` | Enables the RPC Commands to force a Trade entry. More information below. <br> **Datatype:** Boolean
 | `disable_dataframe_checks` | Disable checking the OHLCV dataframe returned from the strategy methods for correctness. Only use when intentionally changing the dataframe and understand what you are doing. [Strategy Override](#parameters-in-the-strategy).<br> *Defaults to `False`*. <br> **Datatype:** Boolean
 | `strategy` | **Required** Defines Strategy class to use. Recommended to be set via `--strategy NAME`. <br> **Datatype:** ClassName
 | `strategy_path` | Adds an additional strategy lookup path (must be a directory). <br> **Datatype:** String
@@ -158,8 +224,11 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `internals.sd_notify` | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](installation.md#7-optional-configure-freqtrade-as-a-systemd-service) for more details. <br> **Datatype:** Boolean
 | `logfile` | Specifies logfile name. Uses a rolling strategy for log file rotation for 10 files with the 1MB limit per file. <br> **Datatype:** String
 | `user_data_dir` | Directory containing user data. <br> *Defaults to `./user_data/`*. <br> **Datatype:** String
+| `add_config_files` | Additional config files. These files will be loaded and merged with the current config file. The files are resolved relative to the initial file.<br> *Defaults to `[]`*. <br> **Datatype:** List of strings
 | `dataformat_ohlcv` | Data format to use to store historical candle (OHLCV) data. <br> *Defaults to `json`*. <br> **Datatype:** String
 | `dataformat_trades` | Data format to use to store historical trades data. <br> *Defaults to `jsongz`*. <br> **Datatype:** String
+| `position_adjustment_enable` | Enables the strategy to use position adjustments (additional buys or sells). [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*<br> **Datatype:** Boolean
+| `max_entry_position_adjustment` | Maximum additional order(s) for each open trade on top of the first entry Order. Set it to `-1` for unlimited additional orders. [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `-1`.*<br> **Datatype:** Positive Integer or -1
 
 ### Parameters in the strategy
 
@@ -179,11 +248,13 @@ Values set in the configuration file always overwrite values set in the strategy
 * `order_time_in_force`
 * `unfilledtimeout`
 * `disable_dataframe_checks`
-* `use_sell_signal`
-* `sell_profit_only`
-* `sell_profit_offset`
-* `ignore_roi_if_buy_signal`
+- `use_exit_signal`
+* `exit_profit_only`
+- `exit_profit_offset`
+- `ignore_roi_if_entry_signal`
 * `ignore_buying_expired_candle_after`
+* `position_adjustment_enable`
+* `max_entry_position_adjustment`
 
 ### Configuring amount per trade
 
@@ -192,9 +263,8 @@ There are several methods to configure how much of the stake currency the bot wi
 #### Minimum trade stake
 
 The minimum stake amount will depend on exchange and pair and is usually listed in the exchange support pages.
-Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.6$.
 
-The minimum stake amount to buy this pair is, therefore, `20 * 0.6 ~= 12`.
+Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.6$, the minimum stake amount to buy this pair is `20 * 0.6 ~= 12`.
 This exchange has also a limit on USD - where all orders must be > 10$ - which however does not apply in this case.
 
 To guarantee safe execution, freqtrade will not allow buying with a stake-amount of 10.1$, instead, it'll make sure that there's enough space to place a stoploss below the pair (+ an offset, defined by `amount_reserve_percent`, which defaults to 5%).
@@ -204,7 +274,7 @@ With a reserve of 5%, the minimum stake amount would be ~12.6$ (`12 * (1 + 0.05)
 To limit this calculation in case of large stoploss values, the calculated minimum stake-limit will never be more than 50% above the real limit.
 
 !!! Warning
-    Since the limits on exchanges are usually stable and are not updated often, some pairs can show pretty high minimum limits, simply because the price increased a lot since the last limit adjustment by the exchange.
+    Since the limits on exchanges are usually stable and are not updated often, some pairs can show pretty high minimum limits, simply because the price increased a lot since the last limit adjustment by the exchange. Freqtrade adjusts the stake-amount to this value, unless it's > 30% more than the calculated/desired stake-amount - in which case the trade is rejected.
 
 #### Tradable balance
 
@@ -291,6 +361,15 @@ To allow the bot to trade all the available `stake_currency` in your account (mi
     When using `"stake_amount" : "unlimited",` in combination with Dry-Run, Backtesting or Hyperopt, the balance will be simulated starting with a stake of `dry_run_wallet` which will evolve.
     It is therefore important to set `dry_run_wallet` to a sensible value (like 0.05 or 0.01 for BTC and 1000 or 100 for USDT, for example), otherwise, it may simulate trades with 100 BTC (or more) or 0.05 USDT (or less) at once - which may not correspond to your real available balance or is less than the exchange minimal limit for the order amount for the stake currency.
 
+#### Dynamic stake amount with position adjustment
+
+When you want to use position adjustment with unlimited stakes, you must also implement `custom_stake_amount` to a return a value depending on your strategy.
+Typical value would be in the range of 25% - 50% of the proposed stakes, but depends highly on your strategy and how much you wish to leave into the wallet as position adjustment buffer.
+
+For example if your position adjustment assumes it can do 2 additional buys with the same stake amounts then your buffer should be 66.6667% of the initially proposed unlimited stake amount.
+
+Or another example if your position adjustment assumes it can do 1 additional buy with 3x the original stake amount then `custom_stake_amount` should return 25% of proposed stake amount and leave 75% for possible later position adjustments.
+
 --8<-- "includes/pricing.md"
 
 ### Understand minimal_roi
@@ -301,10 +380,10 @@ See the example below:
 
 ```json
 "minimal_roi": {
-    "40": 0.0,    # Sell after 40 minutes if the profit is not negative
-    "30": 0.01,   # Sell after 30 minutes if there is at least 1% profit
-    "20": 0.02,   # Sell after 20 minutes if there is at least 2% profit
-    "0":  0.04    # Sell immediately if there is at least 4% profit
+    "40": 0.0,    # Exit after 40 minutes if the profit is not negative
+    "30": 0.01,   # Exit after 30 minutes if there is at least 1% profit
+    "20": 0.02,   # Exit after 20 minutes if there is at least 2% profit
+    "0":  0.04    # Exit immediately if there is at least 4% profit
 },
 ```
 
@@ -313,14 +392,14 @@ This parameter can be set in either Strategy or Configuration file. If you use i
 `minimal_roi` value from the strategy file.
 If it is not set in either Strategy or Configuration, a default of 1000% `{"0": 10}` is used, and minimal ROI is disabled unless your trade generates 1000% profit.
 
-!!! Note "Special case to forcesell after a specific time"
-    A special case presents using `"<N>": -1` as ROI. This forces the bot to sell a trade after N Minutes, no matter if it's positive or negative, so represents a time-limited force-sell.
+!!! Note "Special case to forceexit after a specific time"
+    A special case presents using `"<N>": -1` as ROI. This forces the bot to exit a trade after N Minutes, no matter if it's positive or negative, so represents a time-limited force-exit.
 
-### Understand forcebuy_enable
+### Understand force_entry_enable
 
-The `forcebuy_enable` configuration parameter enables the usage of forcebuy commands via Telegram and REST API.
+The `force_entry_enable` configuration parameter enables the usage of force-enter (`/forcelong`, `/forceshort`) commands via Telegram and REST API.
 For security reasons, it's disabled by default, and freqtrade will show a warning message on startup if enabled.
-For example, you can send `/forcebuy ETH/BTC` to the bot, which will result in freqtrade buying the pair and holds it until a regular sell-signal (ROI, stoploss, /forcesell) appears.
+For example, you can send `/forceenter ETH/BTC` to the bot, which will result in freqtrade buying the pair and holds it until a regular exit-signal (ROI, stoploss, /forceexit) appears.
 
 This can be dangerous with some strategies, so use with care.
 
@@ -347,29 +426,27 @@ For example, if your strategy is using a 1h timeframe, and you only want to buy
 
 ### Understand order_types
 
-The `order_types` configuration parameter maps actions (`buy`, `sell`, `stoploss`, `emergencysell`, `forcesell`, `forcebuy`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds.
+The `order_types` configuration parameter maps actions (`entry`, `exit`, `stoploss`, `emergency_exit`, `force_exit`, `force_entry`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds.
+
+This allows to enter using limit orders, exit using limit-orders, and create stoplosses using market orders.
+It also allows to set the
+stoploss "on exchange" which means stoploss order would be placed immediately once the buy order is fulfilled.
 
-This allows to buy using limit orders, sell using
-limit-orders, and create stoplosses using market orders. It also allows to set the
-stoploss "on exchange" which means stoploss order would be placed immediately once
-the buy order is fulfilled.
-    
 `order_types` set in the configuration file overwrites values set in the strategy as a whole, so you need to configure the whole `order_types` dictionary in one place.
 
-If this is configured, the following 4 values (`buy`, `sell`, `stoploss` and
-`stoploss_on_exchange`) need to be present, otherwise, the bot will fail to start.
+If this is configured, the following 4 values (`entry`, `exit`, `stoploss` and `stoploss_on_exchange`) need to be present, otherwise, the bot will fail to start.
 
-For information on (`emergencysell`,`forcesell`, `forcebuy`, `stoploss_on_exchange`,`stoploss_on_exchange_interval`,`stoploss_on_exchange_limit_ratio`) please see stop loss documentation [stop loss on exchange](stoploss.md)
+For information on (`emergency_exit`,`force_exit`, `force_entry`, `stoploss_on_exchange`,`stoploss_on_exchange_interval`,`stoploss_on_exchange_limit_ratio`) please see stop loss documentation [stop loss on exchange](stoploss.md)
 
 Syntax for Strategy:
 
 ```python
 order_types = {
-    "buy": "limit",
-    "sell": "limit",
-    "emergencysell": "market",
-    "forcebuy": "market",
-    "forcesell": "market",
+    "entry": "limit",
+    "exit": "limit",
+    "emergency_exit": "market",
+    "force_entry": "market",
+    "force_exit": "market",
     "stoploss": "market",
     "stoploss_on_exchange": False,
     "stoploss_on_exchange_interval": 60,
@@ -381,11 +458,11 @@ Configuration:
 
 ```json
 "order_types": {
-    "buy": "limit",
-    "sell": "limit",
-    "emergencysell": "market",
-    "forcebuy": "market",
-    "forcesell": "market",
+    "entry": "limit",
+    "exit": "limit",
+    "emergency_exit": "market",
+    "force_entry": "market",
+    "force_exit": "market",
     "stoploss": "market",
     "stoploss_on_exchange": false,
     "stoploss_on_exchange_interval": 60
@@ -408,7 +485,7 @@ Configuration:
     If `stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new stoploss order.
 
 !!! Warning "Warning: stoploss_on_exchange failures"
-    If stoploss on exchange creation fails for some reason, then an "emergency sell" is initiated. By default, this will sell the asset using a market order. The order-type for the emergency-sell can be changed by setting the `emergencysell` value in the `order_types` dictionary - however, this is not advised.
+    If stoploss on exchange creation fails for some reason, then an "emergency exit" is initiated. By default, this will exit the trade using a market order. The order-type for the emergency-exit can be changed by setting the `emergency_exit` value in the `order_types` dictionary - however, this is not advised.
 
 ### Understand order_time_in_force
 
@@ -438,8 +515,8 @@ The possible values are: `gtc` (default), `fok` or `ioc`.
 
 ``` python
 "order_time_in_force": {
-    "buy": "gtc",
-    "sell": "gtc"
+    "entry": "gtc",
+    "exit": "gtc"
 },
 ```
 
@@ -447,45 +524,6 @@ The possible values are: `gtc` (default), `fok` or `ioc`.
     This is ongoing work. For now, it is supported only for binance and kucoin.
     Please don't change the default value unless you know what you are doing and have researched the impact of using different values for your particular exchange.
 
-### Exchange configuration
-
-Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports over 100 cryptocurrency
-exchange markets and trading APIs. The complete up-to-date list can be found in the
-[CCXT repo homepage](https://github.com/ccxt/ccxt/tree/master/python).
- However, the bot was tested by the development team with only Bittrex, Binance and Kraken,
- so these are the only officially supported exchanges:
-
-- [Bittrex](https://bittrex.com/): "bittrex"
-- [Binance](https://www.binance.com/): "binance"
-- [Kraken](https://kraken.com/): "kraken"
-
-Feel free to test other exchanges and submit your PR to improve the bot.
-
-Some exchanges require special configuration, which can be found on the [Exchange-specific Notes](exchanges.md) documentation page.
-
-#### Sample exchange configuration
-
-A exchange configuration for "binance" would look as follows:
-
-```json
-"exchange": {
-    "name": "binance",
-    "key": "your_exchange_key",
-    "secret": "your_exchange_secret",
-    "ccxt_config": {"enableRateLimit": true},
-    "ccxt_async_config": {
-        "enableRateLimit": true,
-        "rateLimit": 200
-    },
-```
-
-This configuration enables binance, as well as rate-limiting to avoid bans from the exchange.
-`"rateLimit": 200` defines a wait-event of 0.2s between each call. This can also be completely disabled by setting `"enableRateLimit"` to false.
-
-!!! Note
-    Optimal settings for rate-limiting depend on the exchange and the size of the whitelist, so an ideal parameter will vary on many other settings.
-    We try to provide sensible defaults per exchange where possible, if you encounter bans please make sure that `"enableRateLimit"` is enabled and increase the `"rateLimit"` parameter step by step.
-
 ### What values can be used for fiat_display_currency?
 
 The `fiat_display_currency` configuration parameter sets the base currency to use for the
@@ -524,10 +562,10 @@ creating trades on the exchange.
 
 ```json
 "exchange": {
-        "name": "bittrex",
-        "key": "key",
-        "secret": "secret",
-        ...
+    "name": "bittrex",
+    "key": "key",
+    "secret": "secret",
+    ...
 }
 ```
 
diff --git a/docs/data-analysis.md b/docs/data-analysis.md
index 17da98935..9a79ee5ed 100644
--- a/docs/data-analysis.md
+++ b/docs/data-analysis.md
@@ -1,6 +1,6 @@
-# Analyzing bot data with Jupyter notebooks  
+# Analyzing bot data with Jupyter notebooks
 
-You can analyze the results of backtests and trading history easily using Jupyter notebooks. Sample notebooks are located at `user_data/notebooks/` after initializing the user directory with `freqtrade create-userdir --userdir user_data`.  
+You can analyze the results of backtests and trading history easily using Jupyter notebooks. Sample notebooks are located at `user_data/notebooks/` after initializing the user directory with `freqtrade create-userdir --userdir user_data`.
 
 ## Quick start with docker
 
@@ -41,32 +41,35 @@ ipython kernel install --user --name=freqtrade
 !!! Warning
     Some tasks don't work especially well in notebooks. For example, anything using asynchronous execution is a problem for Jupyter. Also, freqtrade's primary entry point is the shell cli, so using pure python in a notebook bypasses arguments that provide required objects and parameters to helper functions. You may need to set those values or create expected objects manually.
 
-## Recommended workflow  
+## Recommended workflow
 
-| Task | Tool |  
-  --- | ---  
-Bot operations | CLI  
+| Task | Tool |
+  --- | ---
+Bot operations | CLI
 Repetitive tasks | Shell scripts
-Data analysis & visualization | Notebook  
+Data analysis & visualization | Notebook
 
 1. Use the CLI to
+
     * download historical data
     * run a backtest
     * run with real-time data
-    * export results  
+    * export results
 
 1. Collect these actions in shell scripts
+
     * save complicated commands with arguments
-    * execute multi-step operations  
+    * execute multi-step operations
     * automate testing strategies and preparing data for analysis
 
 1. Use a notebook to
+
     * visualize data
-    * munge and plot to generate insights
+    * mangle and plot to generate insights
 
-## Example utility snippets  
+## Example utility snippets
 
-### Change directory to root  
+### Change directory to root
 
 Jupyter notebooks execute from the notebook directory. The following snippet searches for the project root, so relative paths remain consistent.
 
diff --git a/docs/data-download.md b/docs/data-download.md
index 0ca86b0d3..9bfc1e685 100644
--- a/docs/data-download.md
+++ b/docs/data-download.md
@@ -11,7 +11,7 @@ Otherwise `--exchange` becomes mandatory.
 You can use a relative timerange (`--days 20`) or an absolute starting point (`--timerange 20200101-`). For incremental downloads, the relative approach should be used.
 
 !!! Tip "Tip: Updating existing data"
-    If you already have backtesting data available in your data-directory and would like to refresh this data up to today, do not use `--days` or `--timerange` parameters. Freqtrade will keep the available data and only download the missing data.
+    If you already have backtesting data available in your data-directory and would like to refresh this data up to today, freqtrade will automatically calculate the data missing for the existing pairs and the download will occur from the latest available point until "now", neither --days or --timerange parameters are required. Freqtrade will keep the available data and only download the missing data.
     If you are updating existing data after inserting new pairs that you have no data for, use `--new-pairs-days xx` parameter. Specified number of days will be downloaded for new pairs while old pairs will be updated with missing data only.
     If you use `--days xx` parameter alone - data for specified number of days will be downloaded for _all_ pairs. Be careful, if specified number of days is smaller than gap between now and last downloaded candle - freqtrade will delete all existing data to avoid gaps in candle data.
 
@@ -22,12 +22,14 @@ usage: freqtrade download-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                                [-d PATH] [--userdir PATH]
                                [-p PAIRS [PAIRS ...]] [--pairs-file FILE]
                                [--days INT] [--new-pairs-days INT]
+                               [--include-inactive-pairs]
                                [--timerange TIMERANGE] [--dl-trades]
                                [--exchange EXCHANGE]
                                [-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]]
                                [--erase]
                                [--data-format-ohlcv {json,jsongz,hdf5}]
                                [--data-format-trades {json,jsongz,hdf5}]
+                               [--trading-mode {spot,margin,futures}]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -38,6 +40,8 @@ optional arguments:
   --days INT            Download data for given number of days.
   --new-pairs-days INT  Download data of new pairs for given number of days.
                         Default: `None`.
+  --include-inactive-pairs
+                        Also download data from inactive pairs.
   --timerange TIMERANGE
                         Specify what timerange of data to use.
   --dl-trades           Download trades instead of OHLCV data. The bot will
@@ -52,10 +56,12 @@ optional arguments:
                         exchange/pairs/timeframes.
   --data-format-ohlcv {json,jsongz,hdf5}
                         Storage format for downloaded candle (OHLCV) data.
-                        (default: `None`).
+                        (default: `json`).
   --data-format-trades {json,jsongz,hdf5}
                         Storage format for downloaded trades data. (default:
-                        `None`).
+                        `jsongz`).
+  --trading-mode {spot,margin,futures}
+                        Select Trading mode
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
@@ -80,6 +86,82 @@ Common arguments:
 
     For that reason, `download-data` does not care about the "startup-period" defined in a strategy. It's up to the user to download additional days if the backtest should start at a specific point in time (while respecting startup period).
 
+### Pairs file
+
+In alternative to the whitelist from `config.json`, a `pairs.json` file can be used.
+If you are using Binance for example:
+
+- create a directory `user_data/data/binance` and copy or create the `pairs.json` file in that directory.
+- update the `pairs.json` file to contain the currency pairs you are interested in.
+
+```bash
+mkdir -p user_data/data/binance
+touch user_data/data/binance/pairs.json
+```
+
+The format of the `pairs.json` file is a simple json list.
+Mixing different stake-currencies is allowed for this file, since it's only used for downloading.
+
+``` json
+[
+    "ETH/BTC",
+    "ETH/USDT",
+    "BTC/USDT",
+    "XRP/ETH"
+]
+```
+
+!!! Tip "Downloading all data for one quote currency"
+    Often, you'll want to download data for all pairs of a specific quote-currency. In such cases, you can use the following shorthand:
+    `freqtrade download-data --exchange binance --pairs .*/USDT <...>`. The provided "pairs" string will be expanded to contain all active pairs on the exchange.
+    To also download data for inactive (delisted) pairs, add `--include-inactive-pairs` to the command.
+
+??? Note "Permission denied errors"
+    If your configuration directory `user_data` was made by docker, you may get the following error:
+
+    ```
+    cp: cannot create regular file 'user_data/data/binance/pairs.json': Permission denied
+    ```
+
+    You can fix the permissions of your user-data directory as follows:
+
+    ```
+    sudo chown -R $UID:$GID user_data
+    ```
+
+### Start download
+
+Then run:
+
+```bash
+freqtrade download-data --exchange binance
+```
+
+This will download historical candle (OHLCV) data for all the currency pairs you defined in `pairs.json`.
+
+Alternatively, specify the pairs directly
+
+```bash
+freqtrade download-data --exchange binance --pairs ETH/USDT XRP/USDT BTC/USDT
+```
+
+or as regex (to download all active USDT pairs)
+
+```bash
+freqtrade download-data --exchange binance --pairs .*/USDT
+```
+
+### Other Notes
+
+- To use a different directory than the exchange specific default, use `--datadir user_data/data/some_directory`.
+- To change the exchange used to download the historical data from, please use a different configuration file (you'll probably need to adjust rate limits etc.)
+- To use `pairs.json` from some other directory, use `--pairs-file some_other_dir/pairs.json`.
+- To download historical candle (OHLCV) data for only 10 days, use `--days 10` (defaults to 30 days).
+- To download historical candle (OHLCV) data from a fixed starting point, use `--timerange 20200101-` - which will download all data from January 1st, 2020. Eventually set end dates are ignored.
+- Use `--timeframes` to specify what timeframe download the historical candle (OHLCV) data for. Default is `--timeframes 1m 5m` which will download 1-minute and 5-minute data.
+- To use exchange, timeframe and list of pairs as defined in your configuration file, use the `-c/--config` option. With this, the script uses the whitelist defined in the config as the list of currency pairs to download data for and does not require the pairs.json file. You can combine `-c/--config` with most other options.
+
+
 ### Data format
 
 Freqtrade currently supports 3 data-formats for both OHLCV and trades data:
@@ -114,11 +196,14 @@ usage: freqtrade convert-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                               {json,jsongz,hdf5} --format-to
                               {json,jsongz,hdf5} [--erase]
                               [-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]]
+                              [--exchange EXCHANGE]
+                              [--trading-mode {spot,margin,futures}]
+                              [--candle-types {spot,,futures,mark,index,premiumIndex,funding_rate} [{spot,,futures,mark,index,premiumIndex,funding_rate} ...]]
 
 optional arguments:
   -h, --help            show this help message and exit
   -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
-                        Show profits for only these pairs. Pairs are space-
+                        Limit command to these pairs. Pairs are space-
                         separated.
   --format-from {json,jsongz,hdf5}
                         Source format for data conversion.
@@ -129,6 +214,12 @@ optional arguments:
   -t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...], --timeframes {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]
                         Specify which tickers to download. Space-separated
                         list. Default: `1m 5m`.
+  --exchange EXCHANGE   Exchange name (default: `bittrex`). Only valid if no
+                        config is provided.
+  --trading-mode {spot,margin,futures}
+                        Select Trading mode
+  --candle-types {spot,,futures,mark,index,premiumIndex,funding_rate} [{spot,,futures,mark,index,premiumIndex,funding_rate} ...]
+                        Select candle type to use
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
@@ -145,6 +236,7 @@ Common arguments:
                         Path to directory with historical backtesting data.
   --userdir PATH, --user-data-dir PATH
                         Path to userdata directory.
+
 ```
 
 ##### Example converting data
@@ -204,6 +296,61 @@ It'll also remove original jsongz data files (`--erase` parameter).
 freqtrade convert-trade-data --format-from jsongz --format-to json --datadir ~/.freqtrade/data/kraken --erase
 ```
 
+### Sub-command trades to ohlcv
+
+When you need to use `--dl-trades` (kraken only) to download data, conversion of trades data to ohlcv data is the last step.
+This command will allow you to repeat this last step for additional timeframes without re-downloading the data.
+
+```
+usage: freqtrade trades-to-ohlcv [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                                 [-d PATH] [--userdir PATH]
+                                 [-p PAIRS [PAIRS ...]]
+                                 [-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]]
+                                 [--exchange EXCHANGE]
+                                 [--data-format-ohlcv {json,jsongz,hdf5}]
+                                 [--data-format-trades {json,jsongz,hdf5}]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
+                        Limit command to these pairs. Pairs are space-
+                        separated.
+  -t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...], --timeframes {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]
+                        Specify which tickers to download. Space-separated
+                        list. Default: `1m 5m`.
+  --exchange EXCHANGE   Exchange name (default: `bittrex`). Only valid if no
+                        config is provided.
+  --data-format-ohlcv {json,jsongz,hdf5}
+                        Storage format for downloaded candle (OHLCV) data.
+                        (default: `json`).
+  --data-format-trades {json,jsongz,hdf5}
+                        Storage format for downloaded trades data. (default:
+                        `jsongz`).
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+```
+
+#### Example trade-to-ohlcv conversion
+
+``` bash
+freqtrade trades-to-ohlcv --exchange kraken -t 5m 1h 1d --pairs BTC/EUR ETH/EUR
+```
+
 ### Sub-command list-data
 
 You can get a list of downloaded data using the `list-data` sub-command.
@@ -213,6 +360,7 @@ usage: freqtrade list-data [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
                            [--userdir PATH] [--exchange EXCHANGE]
                            [--data-format-ohlcv {json,jsongz,hdf5}]
                            [-p PAIRS [PAIRS ...]]
+                           [--trading-mode {spot,margin,futures}]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -222,8 +370,10 @@ optional arguments:
                         Storage format for downloaded candle (OHLCV) data.
                         (default: `json`).
   -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
-                        Show profits for only these pairs. Pairs are space-
+                        Limit command to these pairs. Pairs are space-
                         separated.
+  --trading-mode {spot,margin,futures}
+                        Select Trading mode
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
@@ -257,64 +407,6 @@ ETH/BTC     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
 ETH/USDT    5m, 15m, 30m, 1h, 2h, 4h
 ```
 
-### Pairs file
-
-In alternative to the whitelist from `config.json`, a `pairs.json` file can be used.
-
-If you are using Binance for example:
-
-- create a directory `user_data/data/binance` and copy or create the `pairs.json` file in that directory.
-- update the `pairs.json` file to contain the currency pairs you are interested in.
-
-```bash
-mkdir -p user_data/data/binance
-cp tests/testdata/pairs.json user_data/data/binance
-```
-
-If your configuration directory `user_data` was made by docker, you may get the following error:
-
-```
-cp: cannot create regular file 'user_data/data/binance/pairs.json': Permission denied
-```
-
-You can fix the permissions of your user-data directory as follows:
-
-```
-sudo chown -R $UID:$GID user_data
-```
-
-The format of the `pairs.json` file is a simple json list.
-Mixing different stake-currencies is allowed for this file, since it's only used for downloading.
-
-``` json
-[
-    "ETH/BTC",
-    "ETH/USDT",
-    "BTC/USDT",
-    "XRP/ETH"
-]
-```
-
-### Start download
-
-Then run:
-
-```bash
-freqtrade download-data --exchange binance
-```
-
-This will download historical candle (OHLCV) data for all the currency pairs you defined in `pairs.json`.
-
-### Other Notes
-
-- To use a different directory than the exchange specific default, use `--datadir user_data/data/some_directory`.
-- To change the exchange used to download the historical data from, please use a different configuration file (you'll probably need to adjust rate limits etc.)
-- To use `pairs.json` from some other directory, use `--pairs-file some_other_dir/pairs.json`.
-- To download historical candle (OHLCV) data for only 10 days, use `--days 10` (defaults to 30 days).
-- To download historical candle (OHLCV) data from a fixed starting point, use `--timerange 20200101-` - which will download all data from January 1st, 2020. Eventually set end dates are ignored.
-- Use `--timeframes` to specify what timeframe download the historical candle (OHLCV) data for. Default is `--timeframes 1m 5m` which will download 1-minute and 5-minute data.
-- To use exchange, timeframe and list of pairs as defined in your configuration file, use the `-c/--config` option. With this, the script uses the whitelist defined in the config as the list of currency pairs to download data for and does not require the pairs.json file. You can combine `-c/--config` with most other options.
-
 ### Trades (tick) data
 
 By default, `download-data` sub-command downloads Candles (OHLCV) data. Some exchanges also provide historic trade-data via their API.
diff --git a/docs/deprecated.md b/docs/deprecated.md
index d86a7ac7a..beceb12ab 100644
--- a/docs/deprecated.md
+++ b/docs/deprecated.md
@@ -15,8 +15,8 @@ This command line option was deprecated in 2019.7-dev (develop branch) and remov
 
 ### The **--dynamic-whitelist** command line option
 
-This command line option was deprecated in 2018 and removed freqtrade 2019.6-dev (develop branch)
-and in freqtrade 2019.7.
+This command line option was deprecated in 2018 and removed freqtrade 2019.6-dev (develop branch) and in freqtrade 2019.7.
+Please refer to [pairlists](plugins.md#pairlists-and-pairlist-handlers) instead.
 
 ### the `--live` command line option
 
@@ -24,6 +24,10 @@ and in freqtrade 2019.7.
 Did only download the latest 500 candles, so was ineffective in getting good backtest data.
 Removed in 2019-7-dev (develop branch) and in freqtrade 2019.8.
 
+### `ticker_interval` (now `timeframe`)
+
+Support for `ticker_interval` terminology was deprecated in 2020.6 in favor of `timeframe` - and compatibility code was removed in 2022.3.
+
 ### Allow running multiple pairlists in sequence
 
 The former `"pairlist"` section in the configuration has been removed, and is replaced by `"pairlists"` - being a list to specify a sequence of pairlists.
@@ -34,7 +38,7 @@ The old section of configuration parameters (`"pairlist"`) has been deprecated i
 
 Since only quoteVolume can be compared between assets, the other options (bidVolume, askVolume) have been deprecated in 2020.4, and have been removed in 2020.9.
 
-### Using order book steps for sell price
+### Using order book steps for exit price
 
 Using `order_book_min` and `order_book_max` used to allow stepping the orderbook and trying to find the next ROI slot - trying to place sell-orders early.
 As this does however increase risk and provides no benefit, it's been removed for maintainability purposes in 2021.7.
@@ -43,3 +47,30 @@ As this does however increase risk and provides no benefit, it's been removed fo
 
 Using separate hyperopt files was deprecated in 2021.4 and was removed in 2021.9.
 Please switch to the new [Parametrized Strategies](hyperopt.md) to benefit from the new hyperopt interface.
+
+## Strategy changes between V2 and V3
+
+Isolated Futures / short trading was introduced in 2022.4. This required major changes to configuration settings, strategy interfaces, ...
+
+We have put a great effort into keeping compatibility with existing strategies, so if you just want to continue using freqtrade in spot markets, there are no changes necessary.
+While we may drop support for the current interface sometime in the future, we will announce this separately and have an appropriate transition period.
+
+Please follow the [Strategy migration](strategy_migration.md) guide to migrate your strategy to the new format to start using the new functionalities.
+
+### webhooks - changes with 2022.4
+
+#### `buy_tag` has been renamed to `enter_tag`
+
+This should apply only to your strategy and potentially to webhooks.
+We will keep a compatibility layer for 1-2 versions (so both `buy_tag` and `enter_tag` will still work), but support for this in webhooks will disappear after that.
+
+#### Naming changes
+
+Webhook terminology changed from "sell" to "exit", and from "buy" to "entry".
+
+* `webhookbuy` -> `webhookentry`
+* `webhookbuyfill` -> `webhookentryfill`
+* `webhookbuycancel` -> `webhookentrycancel`
+* `webhooksell` -> `webhookexit`
+* `webhooksellfill` -> `webhookexitfill`
+* `webhooksellcancel` -> `webhookexitcancel`
diff --git a/docs/developer.md b/docs/developer.md
index bd138212b..1cc16294b 100644
--- a/docs/developer.md
+++ b/docs/developer.md
@@ -8,7 +8,7 @@ All contributions, bug reports, bug fixes, documentation improvements, enhanceme
 
 Documentation is available at [https://freqtrade.io](https://www.freqtrade.io/) and needs to be provided with every new feature PR.
 
-Special fields for the documentation (like Note boxes, ...) can be found [here](https://squidfunk.github.io/mkdocs-material/extensions/admonition/).
+Special fields for the documentation (like Note boxes, ...) can be found [here](https://squidfunk.github.io/mkdocs-material/reference/admonitions/).
 
 To test the documentation locally use the following commands.
 
@@ -26,6 +26,11 @@ Alternatively (e.g. if your system is not supported by the setup.sh script), fol
 
 This will install all required tools for development, including `pytest`, `flake8`, `mypy`, and `coveralls`.
 
+Then install the git hook scripts by running `pre-commit install`, so your changes will be verified locally before committing.
+This avoids a lot of waiting for CI already, as some basic formatting checks are done locally on your machine.
+
+Before opening a pull request, please familiarize yourself with our [Contributing Guidelines](https://github.com/freqtrade/freqtrade/blob/develop/CONTRIBUTING.md).
+
 ### Devcontainer setup
 
 The fastest and easiest way to get started is to use [VSCode](https://code.visualstudio.com/) with the Remote container extension.
@@ -218,13 +223,13 @@ Protections can have 2 different ways to stop trading for a limited :
 ##### Protections - per pair
 
 Protections that implement the per pair approach must set `has_local_stop=True`.
-The method `stop_per_pair()` will be called whenever a trade closed (sell order completed).
+The method `stop_per_pair()` will be called whenever a trade closed (exit order completed).
 
 ##### Protections - global protection
 
 These Protections should do their evaluation across all pairs, and consequently will also lock all pairs from trading (called a global PairLock).
 Global protection must set `has_global_stop=True` to be evaluated for global stops.
-The method `global_stop()` will be called whenever a trade closed (sell order completed).
+The method `global_stop()` will be called whenever a trade closed (exit order completed).
 
 ##### Protections - calculating lock end time
 
@@ -250,7 +255,23 @@ Most exchanges supported by CCXT should work out of the box.
 To quickly test the public endpoints of an exchange, add a configuration for your exchange to `test_ccxt_compat.py` and run these tests with `pytest --longrun tests/exchange/test_ccxt_compat.py`.
 Completing these tests successfully a good basis point (it's a requirement, actually), however these won't guarantee correct exchange functioning, as this only tests public endpoints, but no private endpoint (like generate order or similar).
 
-Also try to use `freqtrade download-data` for an extended timerange and verify that the data downloaded correctly (no holes, the specified timerange was actually downloaded).
+Also try to use `freqtrade download-data` for an extended timerange (multiple months) and verify that the data downloaded correctly (no holes, the specified timerange was actually downloaded).
+
+These are prerequisites to have an exchange listed as either Supported or Community tested (listed on the homepage).
+The below are "extras", which will make an exchange better (feature-complete) - but are not absolutely necessary for either of the 2 categories.
+
+Additional tests / steps to complete:
+
+* Verify data provided by `fetch_ohlcv()` - and eventually adjust `ohlcv_candle_limit` for this exchange
+* Check L2 orderbook limit range (API documentation) - and eventually set as necessary
+* Check if balance shows correctly (*)
+* Create market order (*)
+* Create limit order (*)
+* Complete trade (enter + exit) (*)
+  * Compare result calculation between exchange and bot
+  * Ensure fees are applied correctly (check the database against the exchange)
+
+(*) Requires API keys and Balance on the exchange.
 
 ### Stoploss On Exchange
 
@@ -306,9 +327,8 @@ jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to markdown freqtrade
 This documents some decisions taken for the CI Pipeline.
 
 * CI runs on all OS variants, Linux (ubuntu), macOS and Windows.
-* Docker images are build for the branches `stable` and `develop`.
+* Docker images are build for the branches `stable` and `develop`, and are built as multiarch builds, supporting multiple platforms via the same tag.
 * Docker images containing Plot dependencies are also available as `stable_plot` and `develop_plot`.
-* Raspberry PI Docker images are postfixed with `_pi` - so tags will be `:stable_pi` and `develop_pi`.
 * Docker images contain a file, `/freqtrade/freqtrade_commit` containing the commit this image is based of.
 * Full docker image rebuilds are run once a week via schedule.
 * Deployments run on ubuntu.
diff --git a/docs/docker_quickstart.md b/docs/docker_quickstart.md
index 2f350d207..84c1d596a 100644
--- a/docs/docker_quickstart.md
+++ b/docs/docker_quickstart.md
@@ -70,6 +70,18 @@ docker-compose up -d
 !!! Warning "Default configuration"
     While the configuration generated will be mostly functional, you will still need to verify that all options correspond to what you want (like Pricing, pairlist, ...) before starting the bot.
 
+#### Accessing the UI
+
+If you've selected to enable FreqUI in the `new-config` step, you will have freqUI available at port `localhost:8080`.
+
+You can now access the UI by typing localhost:8080 in your browser.
+
+??? Note "UI Access on a remote servers"
+    If you're running on a VPS, you should consider using either a ssh tunnel, or setup a VPN (openVPN, wireguard) to connect to your bot.
+    This will ensure that freqUI is not directly exposed to the internet, which is not recommended for security reasons (freqUI does not support https out of the box).
+    Setup of these tools is not part of this tutorial, however many good tutorials can be found on the internet.
+    Please also read the [API configuration with docker](rest-api.md#configuration-with-docker) section to learn more about this configuration.
+
 #### Monitoring the bot
 
 You can check for running instances with `docker-compose ps`.
@@ -109,10 +121,17 @@ All freqtrade arguments will be available by running `docker-compose run --rm fr
 !!! Warning "`docker-compose` for trade commands"
     Trade commands (`freqtrade trade <...>`) should not be ran via `docker-compose run` - but should use `docker-compose up -d` instead.
     This makes sure that the container is properly started (including port forwardings) and will make sure that the container will restart after a system reboot.
+    If you intend to use freqUI, please also ensure to adjust the [configuration accordingly](rest-api.md#configuration-with-docker), otherwise the UI will not be available.
 
 !!! Note "`docker-compose run --rm`"
     Including `--rm` will remove the container after completion, and is highly recommended for all modes except trading mode (running with `freqtrade trade` command).
 
+??? Note "Using docker without docker-compose"
+    "`docker-compose run --rm`" will require a compose file to be provided.
+    Some freqtrade commands that don't require authentication such as `list-pairs` can be run with "`docker run --rm`" instead.  
+    For example `docker run --rm freqtradeorg/freqtrade:stable list-pairs --exchange binance --quote BTC --print-json`.  
+    This can be useful for fetching exchange information to add to your `config.json` without affecting your running containers.
+
 #### Example: Download data with docker-compose
 
 Download backtesting data for 5 days for the pair ETH/BTC and 1h timeframe from Binance. The data will be stored in the directory `user_data/data/` on the host.
@@ -147,27 +166,9 @@ You'll then also need to modify the `docker-compose.yml` file and uncomment the
       dockerfile: "./Dockerfile.<yourextension>"
 ```
 
-You can then run `docker-compose build` to build the docker image, and run it using the commands described above.
+You can then run `docker-compose build --pull` to build the docker image, and run it using the commands described above.
 
-### Troubleshooting
-
-#### Docker on Windows
-
-* Error: `"Timestamp for this request is outside of the recvWindow."`
-  * The market api requests require a synchronized clock but the time in the docker container shifts a bit over time into the past.
-    To fix this issue temporarily you need to run `wsl --shutdown` and restart docker again (a popup on windows 10 will ask you to do so).
-    A permanent solution is either to host the docker container on a linux host or restart the wsl from time to time with the scheduler.
-    ```
-    taskkill /IM "Docker Desktop.exe" /F
-    wsl --shutdown
-    start "" "C:\Program Files\Docker\Docker\Docker Desktop.exe"
-    ```
-
-!!! Warning
-    Due to the above, we do not recommend the usage of docker on windows for production setups, but only for experimentation, datadownload and backtesting.
-    Best use a linux-VPS for running freqtrade reliably.
-
-## Plotting with docker-compose
+### Plotting with docker-compose
 
 Commands `freqtrade plot-profit` and `freqtrade plot-dataframe` ([Documentation](plotting.md)) are available by changing the image to `*_plot` in your docker-compose.yml file.
 You can then use these commands as follows:
@@ -178,7 +179,7 @@ docker-compose run --rm freqtrade plot-dataframe --strategy AwesomeStrategy -p B
 
 The output will be stored in the `user_data/plot` directory, and can be opened with any modern browser.
 
-## Data analysis using docker compose
+### Data analysis using docker compose
 
 Freqtrade provides a docker-compose file which starts up a jupyter lab server.
 You can run this server using the following command:
@@ -195,3 +196,22 @@ Since part of this image is built on your machine, it is recommended to rebuild
 ``` bash
 docker-compose -f docker/docker-compose-jupyter.yml build --no-cache
 ```
+
+## Troubleshooting
+
+### Docker on Windows
+
+* Error: `"Timestamp for this request is outside of the recvWindow."`
+  * The market api requests require a synchronized clock but the time in the docker container shifts a bit over time into the past.
+    To fix this issue temporarily you need to run `wsl --shutdown` and restart docker again (a popup on windows 10 will ask you to do so).
+    A permanent solution is either to host the docker container on a linux host or restart the wsl from time to time with the scheduler.
+
+    ``` bash
+    taskkill /IM "Docker Desktop.exe" /F
+    wsl --shutdown
+    start "" "C:\Program Files\Docker\Docker\Docker Desktop.exe"
+    ```
+
+!!! Warning
+    Due to the above, we do not recommend the usage of docker on windows for production setups, but only for experimentation, datadownload and backtesting.
+    Best use a linux-VPS for running freqtrade reliably.
diff --git a/docs/edge.md b/docs/edge.md
index 4402d767f..e92abf40f 100644
--- a/docs/edge.md
+++ b/docs/edge.md
@@ -222,7 +222,7 @@ usage: freqtrade edge [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
 
 optional arguments:
   -h, --help            show this help message and exit
-  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
+  -i TIMEFRAME, --timeframe TIMEFRAME
                         Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
   --timerange TIMERANGE
                         Specify what timerange of data to use.
diff --git a/docs/exchanges.md b/docs/exchanges.md
index c0fbdc694..18a7af5a1 100644
--- a/docs/exchanges.md
+++ b/docs/exchanges.md
@@ -1,19 +1,91 @@
 # Exchange-specific Notes
 
-This page combines common gotchas and informations which are exchange-specific and most likely don't apply to other exchanges.
+This page combines common gotchas and Information which are exchange-specific and most likely don't apply to other exchanges.
+
+## Exchange configuration
+
+Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports over 100 cryptocurrency
+exchange markets and trading APIs. The complete up-to-date list can be found in the
+[CCXT repo homepage](https://github.com/ccxt/ccxt/tree/master/python).
+However, the bot was tested by the development team with only a few exchanges.
+A current list of these can be found in the "Home" section of this documentation.
+
+Feel free to test other exchanges and submit your feedback or PR to improve the bot or confirm exchanges that work flawlessly..
+
+Some exchanges require special configuration, which can be found below.
+
+### Sample exchange configuration
+
+A exchange configuration for "binance" would look as follows:
+
+```json
+"exchange": {
+    "name": "binance",
+    "key": "your_exchange_key",
+    "secret": "your_exchange_secret",
+    "ccxt_config": {},
+    "ccxt_async_config": {},
+    // ... 
+```
+
+### Setting rate limits
+
+Usually, rate limits set by CCXT are reliable and work well.
+In case of problems related to rate-limits (usually DDOS Exceptions in your logs), it's easy to change rateLimit settings to other values.
+
+```json
+"exchange": {
+    "name": "kraken",
+    "key": "your_exchange_key",
+    "secret": "your_exchange_secret",
+    "ccxt_config": {"enableRateLimit": true},
+    "ccxt_async_config": {
+        "enableRateLimit": true,
+        "rateLimit": 3100
+    },
+```
+
+This configuration enables kraken, as well as rate-limiting to avoid bans from the exchange.
+`"rateLimit": 3100` defines a wait-event of 3.1s between each call. This can also be completely disabled by setting `"enableRateLimit"` to false.
+
+!!! Note
+    Optimal settings for rate-limiting depend on the exchange and the size of the whitelist, so an ideal parameter will vary on many other settings.
+    We try to provide sensible defaults per exchange where possible, if you encounter bans please make sure that `"enableRateLimit"` is enabled and increase the `"rateLimit"` parameter step by step.
 
 ## Binance
 
 Binance supports [time_in_force](configuration.md#understand-order_time_in_force).
 
 !!! Tip "Stoploss on Exchange"
-    Binance supports `stoploss_on_exchange` and uses stop-loss-limit orders. It provides great advantages, so we recommend to benefit from it.
+    Binance supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange..
 
 ### Binance Blacklist
 
 For Binance, please add `"BNB/<STAKE>"` to your blacklist to avoid issues.
 Accounts having BNB accounts use this to pay for fees - if your first trade happens to be on `BNB`, further trades will consume this position and make the initial BNB trade unsellable as the expected amount is not there anymore.
 
+### Binance Futures
+
+Binance has specific (unfortunately complex) [Futures Trading Quantitative Rules](https://www.binance.com/en/support/faq/4f462ebe6ff445d4a170be7d9e897272) which need to be followed, and which prohibit a too low stake-amount (among others) for too many orders.
+Violating these rules will result in a trading restriction.
+
+When trading on Binance Futures market, orderbook must be used because there is no price ticker data for futures.
+
+``` jsonc
+  "entry_pricing": {
+      "use_order_book": true,
+      "order_book_top": 1,
+      "check_depth_of_market": {
+          "enabled": false,
+          "bids_to_ask_delta": 1
+      }
+  },
+  "exit_pricing": {
+      "use_order_book": true,
+      "order_book_top": 1
+  },
+```
+
 ### Binance sites
 
 Binance has been split into 2, and users must use the correct ccxt exchange ID for their exchange, otherwise API keys are not recognized.
@@ -127,11 +199,45 @@ Kucoin requires a passphrase for each api key, you will therefore need to add th
 
 Kucoin supports [time_in_force](configuration.md#understand-order_time_in_force).
 
+!!! Tip "Stoploss on Exchange"
+    Kucoin supports `stoploss_on_exchange` and can use both stop-loss-market and stop-loss-limit orders. It provides great advantages, so we recommend to benefit from it.
+    You can use either `"limit"` or `"market"` in the `order_types.stoploss` configuration setting to decide which type of stoploss shall be used.
+
 ### Kucoin Blacklists
 
 For Kucoin, please add `"KCS/<STAKE>"` to your blacklist to avoid issues.
 Accounts having KCS accounts use this to pay for fees - if your first trade happens to be on `KCS`, further trades will consume this position and make the initial KCS trade unsellable as the expected amount is not there anymore.
 
+## Huobi
+
+!!! Tip "Stoploss on Exchange"
+    Huobi supports `stoploss_on_exchange` and uses `stop-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
+
+## OKX (former OKEX)
+
+OKX requires a passphrase for each api key, you will therefore need to add this key into the configuration so your exchange section looks as follows:
+
+```json
+"exchange": {
+    "name": "okx",
+    "key": "your_exchange_key",
+    "secret": "your_exchange_secret",
+    "password": "your_exchange_api_key_password",
+    // ...
+}
+```
+
+!!! Warning
+    OKX only provides 100 candles per api call. Therefore, the strategy will only have a pretty low amount of data available in backtesting mode.
+
+## Gate.io
+
+!!! Tip "Stoploss on Exchange"
+    Gate.io supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange..
+
+Gate.io allows the use of `POINT` to pay for fees. As this is not a tradable currency (no regular market available), automatic fee calculations will fail (and default to a fee of 0).
+The configuration parameter `exchange.unknown_fee_rate` can be used to specify the exchange rate between Point and the stake currency. Obviously, changing the stake-currency will also require changes to this value.
+
 ## All exchanges
 
 Should you experience constant errors with Nonce (like `InvalidNonce`), it is best to regenerate the API keys. Resetting Nonce is difficult and it's usually easier to regenerate the API keys.
diff --git a/docs/faq.md b/docs/faq.md
index 285625491..f1542d08e 100644
--- a/docs/faq.md
+++ b/docs/faq.md
@@ -6,13 +6,15 @@ Freqtrade supports spot trading only.
 
 ### Can I open short positions?
 
-No, Freqtrade does not support trading with margin / leverage, and cannot open short positions.
+Freqtrade can open short positions in futures markets.
+This requires the strategy to be made for this - and `"trading_mode": "futures"` in the configuration.
+Please make sure to read the [relevant documentation page](leverage.md) first.
 
-In some cases, your exchange may provide leveraged spot tokens which can be traded with Freqtrade eg. BTCUP/USD, BTCDOWN/USD, ETHBULL/USD, ETHBEAR/USD, etc...
+In spot markets, you can in some cases use leveraged spot tokens, which reflect an inverted pair (eg. BTCUP/USD, BTCDOWN/USD, ETHBULL/USD, ETHBEAR/USD,...) which can be traded with Freqtrade.
 
 ### Can I trade options or futures?
 
-No, options and futures trading are not supported.
+Futures trading is supported for selected exchanges.
 
 ## Beginner Tips & Tricks
 
@@ -42,7 +44,7 @@ position for a trade. Be patient!
 ### I have made 12 trades already, why is my total profit negative?
 
 I understand your disappointment but unfortunately 12 trades is just
-not enough to say anything. If you run backtesting, you can see that our
+not enough to say anything. If you run backtesting, you can see that the
 current algorithm does leave you on the plus side, but that is after
 thousands of trades and even there, you will be left with losses on
 specific coins that you have traded tens if not hundreds of times. We
@@ -54,13 +56,30 @@ you can't say much from few trades.
 
 Yes. You can edit your config and use the `/reload_config` command to reload the configuration. The bot will stop, reload the configuration and strategy and will restart with the new configuration and strategy.
 
-### I want to improve the bot with a new strategy
+### Why does my bot not sell everything it bought?
 
-That's great. We have a nice backtesting and hyperoptimization setup. See the tutorial [here|Testing-new-strategies-with-Hyperopt](bot-usage.md#hyperopt-commands).
+This is called "coin dust" and can happen on all exchanges.
+It happens because many exchanges subtract fees from the "receiving currency" - so you buy 100 COIN - but you only get 99.9 COIN.
+As COIN is trading in full lot sizes (1COIN steps), you cannot sell 0.9 COIN (or 99.9 COIN) - but you need to round down to 99 COIN.
+
+This is not a bot-problem, but will also happen while manual trading.
+
+While freqtrade can handle this (it'll sell 99 COIN), fees are often below the minimum tradable lot-size (you can only trade full COIN, not 0.9 COIN).
+Leaving the dust (0.9 COIN) on the exchange makes usually sense, as the next time freqtrade buys COIN, it'll eat into the remaining small balance, this time selling everything it bought, and therefore slowly declining the dust balance (although it most likely will never reach exactly 0).
+
+Where possible (e.g. on binance), the use of the exchange's dedicated fee currency will fix this.  
+On binance, it's sufficient to have BNB in your account, and have "Pay fees in BNB" enabled in your profile. Your BNB balance will slowly decline (as it's used to pay fees) - but you'll no longer encounter dust (Freqtrade will include the fees in the profit calculations).
+Other exchanges don't offer such possibilities, where it's simply something you'll have to accept or move to a different exchange.
+
+### I want to use incomplete candles
+
+Freqtrade will not provide incomplete candles to strategies. Using incomplete candles will lead to repainting and consequently to strategies with "ghost" buys, which are impossible to both backtest, and verify after they happened.
+
+You can use "current" market data by using the [dataprovider](strategy-customization.md#orderbookpair-maximum)'s orderbook or ticker methods - which however cannot be used during backtesting.
 
 ### Is there a setting to only SELL the coins being held and not perform anymore BUYS?
 
-You can use the `/stopbuy` command in Telegram to prevent future buys, followed by `/forcesell all` (sell all open trades).
+You can use the `/stopbuy` command in Telegram to prevent future buys, followed by `/forceexit all` (sell all open trades).
 
 ### I want to run multiple bots on the same machine
 
@@ -76,22 +95,34 @@ If this happens for all pairs in the pairlist, this might indicate a recent exch
 
 Irrespectively of the reason, Freqtrade will fill up these candles with "empty" candles, where open, high, low and close are set to the previous candle close - and volume is empty. In a chart, this will look like a `_` - and is aligned with how exchanges usually represent 0 volume candles.
 
+### I'm getting "Outdated history for pair xxx" in the log
+
+The bot is trying to tell you that it got an outdated last candle (not the last complete candle).
+As a consequence, Freqtrade will not enter a trade for this pair - as trading on old information is usually not what is desired.
+
+This warning can point to one of the below problems:
+
+* Exchange downtime -> Check your exchange status page / blog / twitter feed for details.
+* Wrong system time -> Ensure your system-time is correct.
+* Barely traded pair -> Check the pair on the exchange webpage, look at the timeframe your strategy uses. If the pair does not have any volume in some candles (usually visualized with a "volume 0" bar, and a "_" as candle), this pair did not have any trades in this timeframe. These pairs should ideally be avoided, as they can cause problems with order-filling.
+* API problem -> API returns wrong data (this only here for completeness, and should not happen with supported exchanges).
+
 ### I'm getting the "RESTRICTED_MARKET" message in the log
 
 Currently known to happen for US Bittrex users.  
 
 Read [the Bittrex section about restricted markets](exchanges.md#restricted-markets) for more information.
 
-### I'm getting the "Exchange Bittrex does not support market orders." message and cannot run my strategy
+### I'm getting the "Exchange XXX does not support market orders." message and cannot run my strategy
 
-As the message says, Bittrex does not support market orders and you have one of the [order types](configuration.md/#understand-order_types) set to "market". Your strategy was probably written with other exchanges in mind and sets "market" orders for "stoploss" orders, which is correct and preferable for most of the exchanges supporting market orders (but not for Bittrex).
+As the message says, your exchange does not support market orders and you have one of the [order types](configuration.md/#understand-order_types) set to "market". Your strategy was probably written with other exchanges in mind and sets "market" orders for "stoploss" orders, which is correct and preferable for most of the exchanges supporting market orders (but not for Bittrex and Gate.io).
 
-To fix it for Bittrex, redefine order types in the strategy to use "limit" instead of "market":
+To fix this, redefine order types in the strategy to use "limit" instead of "market":
 
-```
+``` python
     order_types = {
         ...
-        'stoploss': 'limit',
+        "stoploss": "limit",
         ...
     }
 ```
@@ -136,6 +167,8 @@ On Windows, the `--logfile` option is also supported by Freqtrade and you can us
 > type \path\to\mylogfile.log | findstr "something"
 ```
 
+## Hyperopt module
+
 ### Why does freqtrade not have GPU support?
 
 First of all, most indicator libraries don't have GPU support - as such, there would be little benefit for indicator calculations.
@@ -152,19 +185,17 @@ The benefit of using GPU would therefore be pretty slim - and will not justify t
 
 There is however nothing preventing you from using GPU-enabled indicators within your strategy if you think you must have this - you will however probably be disappointed by the slim gain that will give you (compared to the complexity).
 
-## Hyperopt module
-
 ### How many epochs do I need to get a good Hyperopt result?
 
 Per default Hyperopt called without the `-e`/`--epochs` command line option will only
 run 100 epochs, means 100 evaluations of your triggers, guards, ... Too few
 to find a great result (unless if you are very lucky), so you probably
-have to run it for 10.000 or more. But it will take an eternity to
+have to run it for 10000 or more. But it will take an eternity to
 compute.
 
 Since hyperopt uses Bayesian search, running for too many epochs may not produce greater results.
 
-It's therefore recommended to run between 500-1000 epochs over and over until you hit at least 10.000 epochs in total (or are satisfied with the result). You can best judge by looking at the results - if the bot keeps discovering better strategies, it's best to keep on going.
+It's therefore recommended to run between 500-1000 epochs over and over until you hit at least 10000 epochs in total (or are satisfied with the result). You can best judge by looking at the results - if the bot keeps discovering better strategies, it's best to keep on going.
 
 ```bash
 freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy SampleStrategy -e 1000
@@ -188,9 +219,9 @@ already 8\*10^9\*10 evaluations. A roughly total of 80 billion evaluations.
 Did you run 100 000 evaluations? Congrats, you've done roughly 1 / 100 000 th
 of the search space, assuming that the bot never tests the same parameters more than once.
 
-* The time it takes to run 1000 hyperopt epochs depends on things like: The available cpu, hard-disk, ram, timeframe, timerange, indicator settings, indicator count, amount of coins that hyperopt test strategies on and the resulting trade count - which can be 650 trades in a year or 10.0000 trades depending if the strategy aims for big profits by trading rarely or for many low profit trades. 
+* The time it takes to run 1000 hyperopt epochs depends on things like: The available cpu, hard-disk, ram, timeframe, timerange, indicator settings, indicator count, amount of coins that hyperopt test strategies on and the resulting trade count - which can be 650 trades in a year or 100000 trades depending if the strategy aims for big profits by trading rarely or for many low profit trades. 
 
-Example: 4% profit 650 times vs 0,3% profit a trade 10.000 times in a year. If we assume you set the --timerange to 365 days. 
+Example: 4% profit 650 times vs 0,3% profit a trade 10000 times in a year. If we assume you set the --timerange to 365 days. 
 
 Example:
 `freqtrade --config config.json --strategy SampleStrategy --hyperopt SampleHyperopt -e 1000 --timerange 20190601-20200601`
diff --git a/docs/hyperopt.md b/docs/hyperopt.md
index 09d43939a..3f613a208 100644
--- a/docs/hyperopt.md
+++ b/docs/hyperopt.md
@@ -51,16 +51,17 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
                           [--print-all] [--no-color] [--print-json] [-j JOBS]
                           [--random-state INT] [--min-trades INT]
                           [--hyperopt-loss NAME] [--disable-param-export]
+                          [--ignore-missing-spaces]
 
 optional arguments:
   -h, --help            show this help message and exit
-  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
+  -i TIMEFRAME, --timeframe TIMEFRAME
                         Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
   --timerange TIMERANGE
                         Specify what timerange of data to use.
   --data-format-ohlcv {json,jsongz,hdf5}
                         Storage format for downloaded candle (OHLCV) data.
-                        (default: `None`).
+                        (default: `json`).
   --max-open-trades INT
                         Override the value of the `max_open_trades`
                         configuration setting.
@@ -114,9 +115,13 @@ optional arguments:
                         Hyperopt-loss-functions are:
                         ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss,
                         SharpeHyperOptLoss, SharpeHyperOptLossDaily,
-                        SortinoHyperOptLoss, SortinoHyperOptLossDaily
+                        SortinoHyperOptLoss, SortinoHyperOptLossDaily,
+                        CalmarHyperOptLoss, MaxDrawDownHyperOptLoss, ProfitDrawDownHyperOptLoss
   --disable-param-export
                         Disable automatic hyperopt parameter export.
+  --ignore-missing-spaces, --ignore-unparameterized-spaces
+                        Suppress errors for any requested Hyperopt spaces that
+                        do not contain any parameters.
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
@@ -148,8 +153,8 @@ Checklist on all tasks / possibilities in hyperopt
 
 Depending on the space you want to optimize, only some of the below are required:
 
-* define parameters with `space='buy'` - for buy signal optimization
-* define parameters with `space='sell'` - for sell signal optimization
+* define parameters with `space='buy'` - for entry signal optimization
+* define parameters with `space='sell'` - for exit signal optimization
 
 !!! Note
     `populate_indicators` needs to create all indicators any of the spaces may use, otherwise hyperopt will not work.
@@ -175,7 +180,7 @@ Hyperopt will first load your data into memory and will then run `populate_indic
 
 Hyperopt will then spawn into different processes (number of processors, or `-j <n>`), and run backtesting over and over again, changing the parameters that are part of the `--spaces` defined.
 
-For every new set of parameters, freqtrade will run first `populate_buy_trend()` followed by `populate_sell_trend()`, and then run the regular backtesting process to simulate trades.
+For every new set of parameters, freqtrade will run first `populate_entry_trend()` followed by `populate_exit_trend()`, and then run the regular backtesting process to simulate trades.
 
 After backtesting, the results are passed into the [loss function](#loss-functions), which will evaluate if this result was better or worse than previous results.  
 Based on the loss function result, hyperopt will determine the next set of parameters to try in the next round of backtesting.
@@ -185,7 +190,7 @@ Based on the loss function result, hyperopt will determine the next set of param
 There are two places you need to change in your strategy file to add a new buy hyperopt for testing:
 
 * Define the parameters at the class level hyperopt shall be optimizing.
-* Within `populate_buy_trend()` - use defined parameter values instead of raw constants.
+* Within `populate_entry_trend()` - use defined parameter values instead of raw constants.
 
 There you have two different types of indicators: 1. `guards` and 2. `triggers`.
 
@@ -195,25 +200,25 @@ There you have two different types of indicators: 1. `guards` and 2. `triggers`.
 !!! Hint "Guards and Triggers"
     Technically, there is no difference between Guards and Triggers.  
     However, this guide will make this distinction to make it clear that signals should not be "sticking".
-    Sticking signals are signals that are active for multiple candles. This can lead into buying a signal late (right before the signal disappears - which means that the chance of success is a lot lower than right at the beginning).
+    Sticking signals are signals that are active for multiple candles. This can lead into entering a signal late (right before the signal disappears - which means that the chance of success is a lot lower than right at the beginning).
 
 Hyper-optimization will, for each epoch round, pick one trigger and possibly multiple guards.
 
-#### Sell optimization
+#### Exit signal optimization
 
-Similar to the buy-signal above, sell-signals can also be optimized.
+Similar to the entry-signal above, exit-signals can also be optimized.
 Place the corresponding settings into the following methods
 
 * Define the parameters at the class level hyperopt shall be optimizing, either naming them `sell_*`, or by explicitly defining `space='sell'`.
-* Within `populate_sell_trend()` - use defined parameter values instead of raw constants.
+* Within `populate_exit_trend()` - use defined parameter values instead of raw constants.
 
 The configuration and rules are the same than for buy signals.
 
 ## Solving a Mystery
 
-Let's say you are curious: should you use MACD crossings or lower Bollinger Bands to trigger your buys. 
-And you also wonder should you use RSI or ADX to help with those buy decisions. 
-If you decide to use RSI or ADX, which values should I use for them? 
+Let's say you are curious: should you use MACD crossings or lower Bollinger Bands to trigger your long entries.
+And you also wonder should you use RSI or ADX to help with those decisions.
+If you decide to use RSI or ADX, which values should I use for them?
 
 So let's use hyperparameter optimization to solve this mystery.
 
@@ -269,7 +274,7 @@ The last one we call `trigger` and use it to decide which buy trigger we want to
 So let's write the buy strategy using these values:
 
 ```python
-    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         conditions = []
         # GUARDS AND TRENDS
         if self.buy_adx_enabled.value:
@@ -291,12 +296,12 @@ So let's write the buy strategy using these values:
         if conditions:
             dataframe.loc[
                 reduce(lambda x, y: x & y, conditions),
-                'buy'] = 1
+                'enter_long'] = 1
 
         return dataframe
 ```
 
-Hyperopt will now call `populate_buy_trend()` many times (`epochs`) with different value combinations.  
+Hyperopt will now call `populate_entry_trend()` many times (`epochs`) with different value combinations.  
 It will use the given historical data and simulate buys based on the buy signals generated with the above function.  
 Based on the results, hyperopt will tell you which parameter combination produced the best results (based on the configured [loss function](#loss-functions)).
 
@@ -359,7 +364,7 @@ class MyAwesomeStrategy(IStrategy):
         
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         conditions = []
         conditions.append(qtpylib.crossed_above(
                 dataframe[f'ema_short_{self.buy_ema_short.value}'], dataframe[f'ema_long_{self.buy_ema_long.value}']
@@ -371,10 +376,10 @@ class MyAwesomeStrategy(IStrategy):
         if conditions:
             dataframe.loc[
                 reduce(lambda x, y: x & y, conditions),
-                'buy'] = 1
+                'enter_long'] = 1
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         conditions = []
         conditions.append(qtpylib.crossed_above(
                 dataframe[f'ema_long_{self.buy_ema_long.value}'], dataframe[f'ema_short_{self.buy_ema_short.value}']
@@ -386,7 +391,7 @@ class MyAwesomeStrategy(IStrategy):
         if conditions:
             dataframe.loc[
                 reduce(lambda x, y: x & y, conditions),
-                'sell'] = 1
+                'exit_long'] = 1
         return dataframe
 ```
 
@@ -503,6 +508,46 @@ class MyAwesomeStrategy(IStrategy):
 
 You will then obviously also change potential interesting entries to parameters to allow hyper-optimization.
 
+### Optimizing `max_entry_position_adjustment`
+
+While `max_entry_position_adjustment` is not a separate space, it can still be used in hyperopt by using the property approach shown above.
+
+``` python
+from pandas import DataFrame
+from functools import reduce
+
+import talib.abstract as ta
+
+from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter, 
+                                IStrategy, IntParameter)
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+
+class MyAwesomeStrategy(IStrategy):
+    stoploss = -0.05
+    timeframe = '15m'
+
+    # Define the parameter spaces
+    max_epa = CategoricalParameter([-1, 0, 1, 3, 5, 10], default=1, space="buy", optimize=True)
+
+    @property
+    def max_entry_position_adjustment(self):
+        return self.max_epa.value
+        
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # ...
+```
+
+??? Tip "Using `IntParameter`"
+    You can also use the `IntParameter` for this optimization, but you must explicitly return an integer:
+    ``` python
+    max_epa = IntParameter(-1, 10, default=1, space="buy", optimize=True)
+
+    @property
+    def max_entry_position_adjustment(self):
+        return int(self.max_epa.value)
+    ```
+
 ## Loss-functions
 
 Each hyperparameter tuning requires a target. This is usually defined as a loss function (sometimes also called objective function), which should decrease for more desirable results, and increase for bad results.
@@ -512,12 +557,15 @@ This class should be in its own file within the `user_data/hyperopts/` directory
 
 Currently, the following loss functions are builtin:
 
-* `ShortTradeDurHyperOptLoss` (default legacy Freqtrade hyperoptimization loss function) - Mostly for short trade duration and avoiding losses.
-* `OnlyProfitHyperOptLoss` (which takes only amount of profit into consideration)
-* `SharpeHyperOptLoss` (optimizes Sharpe Ratio calculated on trade returns relative to standard deviation)
-* `SharpeHyperOptLossDaily` (optimizes Sharpe Ratio calculated on **daily** trade returns relative to standard deviation)
-* `SortinoHyperOptLoss` (optimizes Sortino Ratio calculated on trade returns relative to **downside** standard deviation)
-* `SortinoHyperOptLossDaily` (optimizes Sortino Ratio calculated on **daily** trade returns relative to **downside** standard deviation)
+* `ShortTradeDurHyperOptLoss` - (default legacy Freqtrade hyperoptimization loss function) - Mostly for short trade duration and avoiding losses.
+* `OnlyProfitHyperOptLoss` - takes only amount of profit into consideration.
+* `SharpeHyperOptLoss` - optimizes Sharpe Ratio calculated on trade returns relative to standard deviation.
+* `SharpeHyperOptLossDaily` - optimizes Sharpe Ratio calculated on **daily** trade returns relative to standard deviation.
+* `SortinoHyperOptLoss` - optimizes Sortino Ratio calculated on trade returns relative to **downside** standard deviation.
+* `SortinoHyperOptLossDaily` - optimizes Sortino Ratio calculated on **daily** trade returns relative to **downside** standard deviation.
+* `MaxDrawDownHyperOptLoss` - Optimizes Maximum drawdown.
+* `CalmarHyperOptLoss` - Optimizes Calmar Ratio calculated on trade returns relative to max drawdown.
+* `ProfitDrawDownHyperOptLoss` - Optimizes by max Profit & min Drawdown objective. `DRAWDOWN_MULT` variable within the hyperoptloss file can be adjusted to be stricter or more flexible on drawdown purposes.
 
 Creation of a custom loss function is covered in the [Advanced Hyperopt](advanced-hyperopt.md) part of the documentation.
 
diff --git a/docs/includes/pairlists.md b/docs/includes/pairlists.md
index b612a4ddf..cec5ceb19 100644
--- a/docs/includes/pairlists.md
+++ b/docs/includes/pairlists.md
@@ -52,6 +52,8 @@ To skip pair validation against active markets, set `"allow_inactive": true` wit
 This can be useful for backtesting expired pairs (like quarterly spot-markets).
 This option must be configured along with `exchange.skip_pair_validation` in the exchange configuration.
 
+When used in a "follow-up" position (e.g. after VolumePairlist), all pairs in `'pair_whitelist'` will be added to the end of the pairlist.
+
 #### Volume Pair List
 
 `VolumePairList` employs sorting/filtering of pairs by their trading volume. It selects `number_assets` top pairs with sorting based on the `sort_key` (which can only be `quoteVolume`).
@@ -194,23 +196,33 @@ Trade count is used as a tie breaker.
 You can use the `minutes` parameter to only consider performance of the past X minutes (rolling window).
 Not defining this parameter (or setting it to 0) will use all-time performance.
 
+The optional `min_profit` (as ratio -> a setting of `0.01` corresponds to 1%) parameter defines the minimum profit a pair must have to be considered.
+Pairs below this level will be filtered out.
+Using this parameter without `minutes` is highly discouraged, as it can lead to an empty pairlist without a way to recover.
+
 ```json
 "pairlists": [
     // ...
     {
         "method": "PerformanceFilter",
-        "minutes": 1440  // rolling 24h
+        "minutes": 1440,  // rolling 24h
+        "min_profit": 0.01  // minimal profit 1%
     }
 ],
 ```
 
-!!! Note
+As this Filter uses past performance of the bot, it'll have some startup-period - and should only be used after the bot has a few 100 trades in the database.
+
+!!! Warning "Backtesting"
     `PerformanceFilter` does not support backtesting mode.
 
 #### PrecisionFilter
 
 Filters low-value coins which would not allow setting stoplosses.
 
+!!! Warning "Backtesting"
+    `PrecisionFilter` does not support backtesting mode using multiple strategies.
+
 #### PriceFilter
 
 The `PriceFilter` allows filtering of pairs by price. Currently the following price filters are supported:
@@ -234,7 +246,7 @@ On exchanges that deduct fees from the receiving currency (e.g. FTX) - this can
 The `low_price_ratio` setting removes pairs where a raise of 1 price unit (pip) is above the `low_price_ratio` ratio.
 This option is disabled by default, and will only apply if set to > 0.
 
-For `PriceFiler` at least one of its `min_price`, `max_price` or `low_price_ratio` settings must be applied.
+For `PriceFilter` at least one of its `min_price`, `max_price` or `low_price_ratio` settings must be applied.
 
 Calculation example:
 
@@ -248,7 +260,7 @@ Min price precision for SHITCOIN/BTC is 8 decimals. If its price is 0.00000011 -
 Shuffles (randomizes) pairs in the pairlist. It can be used for preventing the bot from trading some of the pairs more frequently then others when you want all pairs be treated with the same priority.
 
 !!! Tip
-    You may set the `seed` value for this Pairlist to obtain reproducible results, which can be useful for repeated backtesting sessions. If `seed` is not set, the pairs are shuffled in the non-repeatable random order.
+    You may set the `seed` value for this Pairlist to obtain reproducible results, which can be useful for repeated backtesting sessions. If `seed` is not set, the pairs are shuffled in the non-repeatable random order. ShuffleFilter will automatically detect runmodes and apply the `seed` only for backtesting modes - if a `seed` value is set.
 
 #### SpreadFilter
 
@@ -283,7 +295,7 @@ If the trading range over the last 10 days is <1% or >99%, remove the pair from
 
 #### VolatilityFilter
 
-Volatility is the degree of historical variation of a pairs over time, is is measured by the standard deviation of logarithmic daily returns. Returns are assumed to be normally distributed, although actual distribution might be different. In a normal distribution, 68% of observations fall within one standard deviation and 95% of observations fall within two standard deviations. Assuming a volatility of 0.05 means that the expected returns for 20 out of 30 days is expected to be less than 5% (one standard deviation). Volatility is a positive ratio of the expected deviation of return and can be greater than 1.00. Please refer to the wikipedia definition of [`volatility`](https://en.wikipedia.org/wiki/Volatility_(finance)).
+Volatility is the degree of historical variation of a pairs over time, it is measured by the standard deviation of logarithmic daily returns. Returns are assumed to be normally distributed, although actual distribution might be different. In a normal distribution, 68% of observations fall within one standard deviation and 95% of observations fall within two standard deviations. Assuming a volatility of 0.05 means that the expected returns for 20 out of 30 days is expected to be less than 5% (one standard deviation). Volatility is a positive ratio of the expected deviation of return and can be greater than 1.00. Please refer to the wikipedia definition of [`volatility`](https://en.wikipedia.org/wiki/Volatility_(finance)).
 
 This filter removes pairs if the average volatility over a `lookback_days` days is below `min_volatility` or above `max_volatility`. Since this is a filter that requires additional data, the results are cached for `refresh_period`.
 
@@ -337,5 +349,5 @@ The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets,
         "refresh_period": 86400
     },
     {"method": "ShuffleFilter", "seed": 42}
-    ],
+],
 ```
diff --git a/docs/includes/pricing.md b/docs/includes/pricing.md
index ed8a45e68..ee6ec0cce 100644
--- a/docs/includes/pricing.md
+++ b/docs/includes/pricing.md
@@ -1,6 +1,6 @@
 ## Prices used for orders
 
-Prices for regular orders can be controlled via the parameter structures `bid_strategy` for buying and `ask_strategy` for selling.
+Prices for regular orders can be controlled via the parameter structures `entry_pricing` for trade entries and `exit_pricing` for trade exits.
 Prices are always retrieved right before an order is placed, either by querying the exchange tickers or by using the orderbook data.
 
 !!! Note
@@ -9,20 +9,11 @@ Prices are always retrieved right before an order is placed, either by querying
 !!! Warning "Using market orders"
     Please read the section [Market order pricing](#market-order-pricing) section when using market orders.
 
-### Buy price
+### Entry price
 
-#### Check depth of market
+#### Enter price side
 
-When check depth of market is enabled (`bid_strategy.check_depth_of_market.enabled=True`), the buy signals are filtered based on the orderbook depth (sum of all amounts) for each orderbook side.
-
-Orderbook `bid` (buy) side depth is then divided by the orderbook `ask` (sell) side depth and the resulting delta is compared to the value of the `bid_strategy.check_depth_of_market.bids_to_ask_delta` parameter. The buy order is only executed if the orderbook delta is greater than or equal to the configured delta value.
-
-!!! Note
-    A delta value below 1 means that `ask` (sell) orderbook side depth is greater than the depth of the `bid` (buy) orderbook side, while a value greater than 1 means opposite (depth of the buy side is higher than the depth of the sell side).
-
-#### Buy price side
-
-The configuration setting `bid_strategy.price_side` defines the side of the spread the bot looks for when buying.
+The configuration setting `entry_pricing.price_side` defines the side of the orderbook the bot looks for when buying.
 
 The following displays an orderbook.
 
@@ -38,30 +29,53 @@ The following displays an orderbook.
 ...
 ```
 
-If `bid_strategy.price_side` is set to `"bid"`, then the bot will use 99 as buying price.  
-In line with that, if `bid_strategy.price_side` is set to `"ask"`, then the bot will use 101 as buying price.
+If `entry_pricing.price_side` is set to `"bid"`, then the bot will use 99 as entry price.  
+In line with that, if `entry_pricing.price_side` is set to `"ask"`, then the bot will use 101 as entry price.
 
-Using `ask` price often guarantees quicker filled orders, but the bot can also end up paying more than what would have been necessary.
+Depending on the order direction (_long_/_short_), this will lead to different results. Therefore we recommend to use `"same"` or `"other"` for this configuration instead.
+This would result in the following pricing matrix:
+
+| direction | Order | setting | price | crosses spread |
+|------ |--------|-----|-----|-----|
+| long  | buy  | ask   | 101 | yes |
+| long  | buy  | bid   | 99  | no  |
+| long  | buy  | same  | 99  | no  |
+| long  | buy  | other | 101 | yes |
+| short | sell | ask   | 101 | no  |
+| short | sell | bid   | 99  | yes |
+| short | sell | same  | 101 | no  |
+| short | sell | other | 99  | yes |
+
+Using the other side of the orderbook often guarantees quicker filled orders, but the bot can also end up paying more than what would have been necessary.
 Taker fees instead of maker fees will most likely apply even when using limit buy orders.
-Also, prices at the "ask" side of the spread are higher than prices at the "bid" side in the orderbook, so the order behaves similar to a market order (however with a maximum price).
+Also, prices at the "other" side of the spread are higher than prices at the "bid" side in the orderbook, so the order behaves similar to a market order (however with a maximum price).
 
-#### Buy price with Orderbook enabled
+#### Entry price with Orderbook enabled
 
-When buying with the orderbook enabled (`bid_strategy.use_order_book=True`), Freqtrade fetches the `bid_strategy.order_book_top` entries from the orderbook and uses the entry specified as `bid_strategy.order_book_top` on the configured side (`bid_strategy.price_side`) of the orderbook. 1 specifies the topmost entry in the orderbook, while 2 would use the 2nd entry in the orderbook, and so on.
+When entering a trade with the orderbook enabled (`entry_pricing.use_order_book=True`), Freqtrade fetches the `entry_pricing.order_book_top` entries from the orderbook and uses the entry specified as `entry_pricing.order_book_top` on the configured side (`entry_pricing.price_side`) of the orderbook. 1 specifies the topmost entry in the orderbook, while 2 would use the 2nd entry in the orderbook, and so on.
 
-#### Buy price without Orderbook enabled
+#### Entry price without Orderbook enabled
 
-The following section uses `side` as the configured `bid_strategy.price_side`.
+The following section uses `side` as the configured `entry_pricing.price_side` (defaults to `"same"`).
 
-When not using orderbook (`bid_strategy.use_order_book=False`), Freqtrade uses the best `side` price from the ticker if it's below the `last` traded price from the ticker. Otherwise (when the `side` price is above the `last` price), it calculates a rate between `side` and `last` price.
+When not using orderbook (`entry_pricing.use_order_book=False`), Freqtrade uses the best `side` price from the ticker if it's below the `last` traded price from the ticker. Otherwise (when the `side` price is above the `last` price), it calculates a rate between `side` and `last` price based on `entry_pricing.price_last_balance`.
 
-The `bid_strategy.ask_last_balance` configuration parameter controls this. A value of `0.0` will use `side` price, while `1.0` will use the `last` price and values between those interpolate between ask and last price.
+The `entry_pricing.price_last_balance` configuration parameter controls this. A value of `0.0` will use `side` price, while `1.0` will use the `last` price and values between those interpolate between ask and last price.
 
-### Sell price
+#### Check depth of market
 
-#### Sell price side
+When check depth of market is enabled (`entry_pricing.check_depth_of_market.enabled=True`), the entry signals are filtered based on the orderbook depth (sum of all amounts) for each orderbook side.
 
-The configuration setting `ask_strategy.price_side` defines the side of the spread the bot looks for when selling.
+Orderbook `bid` (buy) side depth is then divided by the orderbook `ask` (sell) side depth and the resulting delta is compared to the value of the `entry_pricing.check_depth_of_market.bids_to_ask_delta` parameter. The entry order is only executed if the orderbook delta is greater than or equal to the configured delta value.
+
+!!! Note
+    A delta value below 1 means that `ask` (sell) orderbook side depth is greater than the depth of the `bid` (buy) orderbook side, while a value greater than 1 means opposite (depth of the buy side is higher than the depth of the sell side).
+
+### Exit price
+
+#### Exit price side
+
+The configuration setting `exit_pricing.price_side` defines the side of the spread the bot looks for when exiting a trade.
 
 The following displays an orderbook:
 
@@ -77,40 +91,54 @@ The following displays an orderbook:
 ...
 ```
 
-If `ask_strategy.price_side` is set to `"ask"`, then the bot will use 101 as selling price.  
-In line with that, if `ask_strategy.price_side` is set to `"bid"`, then the bot will use 99 as selling price.
+If `exit_pricing.price_side` is set to `"ask"`, then the bot will use 101 as exiting price.  
+In line with that, if `exit_pricing.price_side` is set to `"bid"`, then the bot will use 99 as exiting price.
 
-#### Sell price with Orderbook enabled
+Depending on the order direction (_long_/_short_), this will lead to different results. Therefore we recommend to use `"same"` or `"other"` for this configuration instead.
+This would result in the following pricing matrix:
 
-When selling with the orderbook enabled (`ask_strategy.use_order_book=True`), Freqtrade fetches the `ask_strategy.order_book_top` entries in the orderbook and uses the entry specified as `ask_strategy.order_book_top` from the configured side (`ask_strategy.price_side`) as selling price.
+| Direction | Order | setting | price | crosses spread |
+|------ |--------|-----|-----|-----|
+| long  | sell | ask   | 101 | no  |
+| long  | sell | bid   | 99  | yes |
+| long  | sell | same  | 101 | no  |
+| long  | sell | other | 99  | yes |
+| short | buy  | ask   | 101 | yes |
+| short | buy  | bid   | 99  | no  |
+| short | buy  | same  | 99  | no  |
+| short | buy  | other | 101 | yes |
+
+#### Exit price with Orderbook enabled
+
+When exiting with the orderbook enabled (`exit_pricing.use_order_book=True`), Freqtrade fetches the `exit_pricing.order_book_top` entries in the orderbook and uses the entry specified as `exit_pricing.order_book_top` from the configured side (`exit_pricing.price_side`) as trade exit price.
 
 1 specifies the topmost entry in the orderbook, while 2 would use the 2nd entry in the orderbook, and so on.
 
-#### Sell price without Orderbook enabled
+#### Exit price without Orderbook enabled
 
-When not using orderbook (`ask_strategy.use_order_book=False`), the price at the `ask_strategy.price_side` side (defaults to `"ask"`) from the ticker will be used as the sell price.
+The following section uses `side` as the configured `exit_pricing.price_side` (defaults to `"ask"`).
 
-When not using orderbook (`ask_strategy.use_order_book=False`), Freqtrade uses the best `side` price from the ticker if it's below the `last` traded price from the ticker. Otherwise (when the `side` price is above the `last` price), it calculates a rate between `side` and `last` price.
+When not using orderbook (`exit_pricing.use_order_book=False`), Freqtrade uses the best `side` price from the ticker if it's above the `last` traded price from the ticker. Otherwise (when the `side` price is below the `last` price), it calculates a rate between `side` and `last` price based on `exit_pricing.price_last_balance`.
 
-The `ask_strategy.bid_last_balance` configuration parameter controls this. A value of `0.0` will use `side` price, while `1.0` will use the last price and values between those interpolate between `side` and last price.
+The `exit_pricing.price_last_balance` configuration parameter controls this. A value of `0.0` will use `side` price, while `1.0` will use the last price and values between those interpolate between `side` and last price.
 
 ### Market order pricing
 
 When using market orders, prices should be configured to use the "correct" side of the orderbook to allow realistic pricing detection.
-Assuming both buy and sell are using market orders, a configuration similar to the following might be used
+Assuming both entry and exits are using market orders, a configuration similar to the following must be used
 
 ``` jsonc
   "order_types": {
-    "buy": "market",
-    "sell": "market"
+    "entry": "market",
+    "exit": "market"
     // ...
   },
-  "bid_strategy": {
-    "price_side": "ask",
+  "entry_pricing": {
+    "price_side": "other",
     // ...
   },
-  "ask_strategy":{
-    "price_side": "bid",
+  "exit_pricing":{
+    "price_side": "other",
     // ...
   },
 ```
diff --git a/docs/index.md b/docs/index.md
index 7735117e2..2aa80c240 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -11,7 +11,7 @@
 
 ## Introduction
 
-Freqtrade is a crypto-currency algorithmic trading software developed in python (3.7+) and supported on Windows, macOS and Linux.
+Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
 
 !!! Danger "DISCLAIMER"
     This software is for educational purposes only. Do not risk money which you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS.
@@ -20,6 +20,12 @@ Freqtrade is a crypto-currency algorithmic trading software developed in python
 
     We strongly recommend you to have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms and techniques implemented in it.
 
+![freqtrade screenshot](assets/freqtrade-screenshot.png)
+
+## Sponsored promotion
+
+[![tokenbot-promo](assets/TokenBot-Freqtrade-banner.png)](https://tokenbot.com/?utm_source=github&utm_medium=freqtrade&utm_campaign=algodevs)
+
 ## Features
 
 - Develop your Strategy: Write your strategy in python, using [pandas](https://pandas.pydata.org/). Example strategies to inspire you are available in the [strategy repository](https://github.com/freqtrade/freqtrade-strategies).
@@ -29,18 +35,20 @@ Freqtrade is a crypto-currency algorithmic trading software developed in python
 - Select markets: Create your static list or use an automatic one based on top traded volumes and/or prices (not available during backtesting). You can also explicitly blacklist markets you don't want to trade.
 - Run: Test your strategy with simulated money (Dry-Run mode) or deploy it with real money (Live-Trade mode).
 - Run using Edge (optional module): The concept is to find the best historical [trade expectancy](edge.md#expectancy) by markets based on variation of the stop-loss and then allow/reject markets to trade. The sizing of the trade is based on a risk of a percentage of your capital.
-- Control/Monitor: Use Telegram or a REST API (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.).
+- Control/Monitor: Use Telegram or a WebUI (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.).
 - Analyse: Further analysis can be performed on either Backtesting data or Freqtrade trading history (SQL database), including automated standard plots, and methods to load the data into [interactive environments](data-analysis.md).
 
 ## Supported exchange marketplaces
 
 Please read the [exchange specific notes](exchanges.md) to learn about eventual, special configurations needed for each exchange.
 
-- [X] [Binance](https://www.binance.com/) ([*Note for binance users](docs/exchanges.md#binance-blacklist))
+- [X] [Binance](https://www.binance.com/)
 - [X] [Bittrex](https://bittrex.com/)
-- [X] [FTX](https://ftx.com)
-- [X] [Kraken](https://kraken.com/)
+- [X] [FTX](https://ftx.com/#a=2258149)
 - [X] [Gate.io](https://www.gate.io/ref/6266643)
+- [X] [Huobi](http://huobi.com/)
+- [X] [Kraken](https://kraken.com/)
+- [X] [OKX](https://okx.com/) (Former OKEX)
 - [ ] [potentially many others through <img alt="ccxt" width="30px" src="assets/ccxt-logo.svg" />](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
 
 ### Community tested
@@ -66,7 +74,7 @@ To run this bot we recommend you a linux cloud instance with a minimum of:
 
 Alternatively
 
-- Python 3.7+
+- Python 3.8+
 - pip (pip3)
 - git
 - TA-Lib
@@ -80,4 +88,4 @@ For any questions not covered by the documentation or for further information ab
 
 ## Ready to try?
 
-Begin by reading our installation guide [for docker](docker_quickstart.md) (recommended), or for [installation without docker](installation.md).
+Begin by reading the installation guide [for docker](docker_quickstart.md) (recommended), or for [installation without docker](installation.md).
diff --git a/docs/installation.md b/docs/installation.md
index 5e4a19d88..92aa59498 100644
--- a/docs/installation.md
+++ b/docs/installation.md
@@ -24,7 +24,7 @@ The easiest way to install and run Freqtrade is to clone the bot Github reposito
     The `stable` branch contains the code of the last release (done usually once per month on an approximately one week old snapshot of the `develop` branch to prevent packaging bugs, so potentially it's more stable).
 
 !!! Note
-    Python3.7 or higher and the corresponding `pip` are assumed to be available. The install-script will warn you and stop if that's not the case. `git` is also needed to clone the Freqtrade repository.  
+    Python3.8 or higher and the corresponding `pip` are assumed to be available. The install-script will warn you and stop if that's not the case. `git` is also needed to clone the Freqtrade repository.  
     Also, python headers (`python<yourversion>-dev` / `python<yourversion>-devel`) must be available for the installation to complete successfully.
 
 !!! Warning "Up-to-date clock"
@@ -36,9 +36,13 @@ The easiest way to install and run Freqtrade is to clone the bot Github reposito
 
 These requirements apply to both [Script Installation](#script-installation) and [Manual Installation](#manual-installation).
 
+!!! Note "ARM64 systems"
+    If you are running an ARM64 system (like a MacOS M1 or an Oracle VM), please use [docker](docker_quickstart.md) to run freqtrade.
+    While native installation is possible with some manual effort, this is not supported at the moment.
+
 ### Install guide
 
-* [Python >= 3.7.x](http://docs.python-guide.org/en/latest/starting/installation/)
+* [Python >= 3.8.x](http://docs.python-guide.org/en/latest/starting/installation/)
 * [pip](https://pip.pypa.io/en/stable/installing/)
 * [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
 * [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended)
@@ -50,7 +54,7 @@ We've included/collected install instructions for Ubuntu, MacOS, and Windows. Th
 OS Specific steps are listed first, the [Common](#common) section below is necessary for all systems.
 
 !!! Note
-    Python3.7 or higher and the corresponding pip are assumed to be available.
+    Python3.8 or higher and the corresponding pip are assumed to be available.
 
 === "Debian/Ubuntu"
     #### Install necessary dependencies
@@ -60,18 +64,18 @@ OS Specific steps are listed first, the [Common](#common) section below is neces
     sudo apt-get update
 
     # install packages
-    sudo apt install -y python3-pip python3-venv python3-dev python3-pandas git
+    sudo apt install -y python3-pip python3-venv python3-dev python3-pandas git curl
     ```
 
 === "RaspberryPi/Raspbian"
     The following assumes the latest [Raspbian Buster lite image](https://www.raspberrypi.org/downloads/raspbian/).
-    This image comes with python3.7 preinstalled, making it easy to get freqtrade up and running.
+    This image comes with python3.9 preinstalled, making it easy to get freqtrade up and running.
 
     Tested using a Raspberry Pi 3 with the Raspbian Buster lite image, all updates applied.
 
 
     ```bash
-    sudo apt-get install python3-venv libatlas-base-dev cmake
+    sudo apt-get install python3-venv libatlas-base-dev cmake curl
     # Use pywheels.org to speed up installation
     sudo echo "[global]\nextra-index-url=https://www.piwheels.org/simple" > tee /etc/pip.conf
 
@@ -113,6 +117,13 @@ git checkout develop
 
 You may later switch between branches at any time with the `git checkout stable`/`git checkout develop` commands.
 
+??? Note "Install from pypi"
+    An alternative way to install Freqtrade is from [pypi](https://pypi.org/project/freqtrade/). The downside is that this method requires ta-lib to be correctly installed beforehand, and is therefore currently not the recommended way to install Freqtrade.
+
+    ``` bash
+    pip install freqtrade
+    ```
+
 ------
 
 ## Script Installation
@@ -158,7 +169,7 @@ You can as well update, configure and reset the codebase of your bot with `./scr
 ** --install **
 
 With this option, the script will install the bot and most dependencies:
-You will need to have git and python3.7+ installed beforehand for this to work.
+You will need to have git and python3.8+ installed beforehand for this to work.
 
 * Mandatory software as: `ta-lib`
 * Setup your virtualenv under `.env/`
@@ -409,16 +420,3 @@ open /Library/Developer/CommandLineTools/Packages/macOS_SDK_headers_for_macOS_10
 ```
 
 If this file is inexistent, then you're probably on a different version of MacOS, so you may need to consult the internet for specific resolution details.
-
-### MacOS installation error with python 3.9
-
-When using python 3.9 on macOS, it's currently necessary to install some os-level modules to allow dependencies to compile.
-The errors you'll see happen during installation and are related to the installation of `tables` or `blosc`.
-
-You can install the necessary libraries with the following command:
-
-```bash
-brew install hdf5 c-blosc
-```
-
-After this, please run the installation (script) again.
diff --git a/docs/leverage.md b/docs/leverage.md
new file mode 100644
index 000000000..79d3c9842
--- /dev/null
+++ b/docs/leverage.md
@@ -0,0 +1,116 @@
+# Trading with Leverage
+
+!!! Warning "Beta feature"
+    This feature is still in it's testing phase. Should you notice something you think is wrong please let us know via Discord or via Github Issue.
+
+!!! Note "Multiple bots on one account"
+    You can't run 2 bots on the same account with leverage. For leveraged / margin trading, freqtrade assumes it's the only user of the account, and all liquidation levels are calculated based on this assumption.
+
+!!! Danger "Trading with leverage is very risky"
+    Do not trade with a leverage > 1 using a strategy that hasn't shown positive results in a live run using the spot market. Check the stoploss of your strategy. With a leverage of 2, a stoploss of 0.5 (50%) would be too low, and these trades would be liquidated before reaching that stoploss.
+    We do not assume any responsibility for eventual losses that occur from using this software or this mode.
+
+    Please only use advanced trading modes when you know how freqtrade (and your strategy) works.
+    Also, never risk more than what you can afford to lose.
+
+Please read the [strategy migration guide](strategy_migration.md#strategy-migration-between-v2-and-v3) to migrate your strategy from a freqtrade v2 strategy, to v3 strategy that can short and trade futures.
+
+## Shorting
+
+Shorting is not possible when trading with [`trading_mode`](#understand-tradingmode) set to `spot`. To short trade, `trading_mode` must be set to `margin`(currently unavailable) or [`futures`](#futures), with [`margin_mode`](#margin-mode) set to `cross`(currently unavailable) or [`isolated`](#isolated-margin-mode)
+
+For a strategy to short, the strategy class must set the class variable `can_short = True`
+
+Please read [strategy customization](strategy-customization.md#entry-signal-rules) for instructions on how to set signals to enter and exit short trades.
+
+## Understand `trading_mode`
+
+The possible values are: `spot` (default), `margin`(*Currently unavailable*) or `futures`.
+
+### Spot
+
+Regular trading mode (low risk)
+
+- Long trades only (No short trades).
+- No leverage.
+- No Liquidation.
+- Profits gained/lost are equal to the change in value of the assets (minus trading fees).
+
+### Leverage trading modes
+
+With leverage, a trader borrows capital from the exchange. The capital must be re-payed fully to the exchange (potentially with interest), and the trader keeps any profits, or pays any losses, from any trades made using the borrowed capital.
+
+Because the capital must always be re-payed, exchanges will **liquidate** (forcefully sell the traders assets) a trade made using borrowed capital when the total value of assets in the leverage account drops to a certain point (a point where the total value of losses is less than the value of the collateral that the trader actually owns in the leverage account), in order to ensure that the trader has enough capital to pay the borrowed assets back to the exchange. The exchange will also charge a **liquidation fee**, adding to the traders losses.
+
+For this reason, **DO NOT TRADE WITH LEVERAGE IF YOU DON'T KNOW EXACTLY WHAT YOUR DOING. LEVERAGE TRADING IS HIGH RISK, AND CAN RESULT IN THE VALUE OF YOUR ASSETS DROPPING TO 0 VERY QUICKLY, WITH NO CHANCE OF INCREASING IN VALUE AGAIN.**
+
+#### Margin (currently unavailable)
+
+Trading occurs on the spot market, but the exchange lends currency to you in an amount equal to the chosen leverage. You pay the amount lent to you back to the exchange with interest, and your profits/losses are multiplied by the leverage specified.
+
+#### Futures
+
+Perpetual swaps (also known as Perpetual Futures) are contracts traded at a price that is closely tied to the underlying asset they are based off of (ex.). You are not trading the actual asset but instead are trading a derivative contract. Perpetual swap contracts can last indefinitely, in contrast to futures or option contracts.
+
+In addition to the gains/losses from the change in price of the futures contract, traders also exchange _funding fees_, which are gains/losses worth an amount that is derived from the difference in price between the futures contract and the underlying asset. The difference in price between a futures contract and the underlying asset varies between exchanges.
+
+To trade in futures markets, you'll have to set `trading_mode` to "futures".
+You will also have to pick a "margin mode" (explanation below) - with freqtrade currently only supporting isolated margin.
+
+``` json
+"trading_mode": "futures",
+"margin_mode": "isolated"
+```
+
+### Margin mode
+
+The possible values are: `isolated`, or `cross`(*currently unavailable*)
+
+#### Isolated margin mode
+
+Each market(trading pair), keeps collateral in a separate account
+
+``` json
+"margin_mode": "isolated"
+```
+
+#### Cross margin mode (currently unavailable)
+
+One account is used to share collateral between markets (trading pairs). Margin is taken from total account balance to avoid liquidation when needed.
+
+``` json
+"margin_mode": "cross"
+```
+
+## Understand `liquidation_buffer`
+
+*Defaults to `0.05`*
+
+A ratio specifying how large of a safety net to place between the liquidation price and the stoploss to prevent a position from reaching the liquidation price.
+This artificial liquidation price is calculated as:
+
+`freqtrade_liquidation_price = liquidation_price ± (abs(open_rate - liquidation_price) * liquidation_buffer)`
+
+- `±` = `+` for long trades
+- `±` = `-` for short trades
+
+Possible values are any floats between 0.0 and 0.99
+
+**ex:** If a trade is entered at a price of 10 coin/USDT, and the liquidation price of this trade is 8 coin/USDT, then with `liquidation_buffer` set to `0.05` the minimum stoploss for this trade would be $8 + ((10 - 8) * 0.05) = 8 + 0.1 = 8.1$
+
+!!! Danger "A `liquidation_buffer` of 0.0, or a low `liquidation_buffer` is likely to result in liquidations, and liquidation fees"
+    Currently Freqtrade is able to calculate liquidation prices, but does not calculate liquidation fees. Setting your `liquidation_buffer` to 0.0, or using a low `liquidation_buffer` could result in your positions being liquidated. Freqtrade does not track liquidation fees, so liquidations will result in inaccurate profit/loss results for your bot. If you use a low `liquidation_buffer`, it is recommended to use `stoploss_on_exchange` if your exchange supports this.
+
+### Developer
+
+#### Margin mode
+
+For shorts, the currency which pays the interest fee for the `borrowed` currency is purchased at the same time of the closing trade (This means that the amount purchased in short closing trades is greater than the amount sold in short opening trades).
+
+For longs, the currency which pays the interest fee for the `borrowed` will already be owned by the user and does not need to be purchased. The interest is subtracted from the `close_value` of the trade.
+
+All Fees are included in `current_profit` calculations during the trade.
+
+#### Futures mode
+
+Funding fees are either added or subtracted from the total amount of a trade
diff --git a/docs/plotting.md b/docs/plotting.md
index 9fae38504..6ae0c3f11 100644
--- a/docs/plotting.md
+++ b/docs/plotting.md
@@ -14,7 +14,7 @@ pip install -U -r requirements-plot.txt
 
 The `freqtrade plot-dataframe` subcommand shows an interactive graph with three subplots:
 
-* Main plot with candlestics and indicators following price (sma/ema)
+* Main plot with candlesticks and indicators following price (sma/ema)
 * Volume bars
 * Additional indicators as specified by `--indicators2`
 
@@ -65,7 +65,7 @@ optional arguments:
                         _today.json`
   --timerange TIMERANGE
                         Specify what timerange of data to use.
-  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
+  -i TIMEFRAME, --timeframe TIMEFRAME
                         Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
   --no-trades           Skip using trades from backtesting file and DB.
 
@@ -96,7 +96,7 @@ Strategy arguments:
 Example:
 
 ``` bash
-freqtrade plot-dataframe -p BTC/ETH
+freqtrade plot-dataframe -p BTC/ETH --strategy AwesomeStrategy
 ```
 
 The `-p/--pairs` argument can be used to specify pairs you would like to plot.
@@ -107,9 +107,6 @@ The `-p/--pairs` argument can be used to specify pairs you would like to plot.
 Specify custom indicators.
 Use `--indicators1` for the main plot and `--indicators2` for the subplot below (if values are in a different range than prices).
 
-!!! Tip
-    You will almost certainly want to specify a custom strategy! This can be done by adding `-s Classname` / `--strategy ClassName` to the command.
-
 ``` bash
 freqtrade plot-dataframe --strategy AwesomeStrategy -p BTC/ETH --indicators1 sma ema --indicators2 macd
 ```
@@ -164,16 +161,17 @@ The resulting plot will have the following elements:
 
 An advanced plot configuration can be specified in the strategy in the `plot_config` parameter.
 
-Additional features when using plot_config include:
+Additional features when using `plot_config` include:
 
 * Specify colors per indicator
 * Specify additional subplots
-* Specify indicator pairs to fill area in between 
+* Specify indicator pairs to fill area in between
 
 The sample plot configuration below specifies fixed colors for the indicators. Otherwise, consecutive plots may produce different color schemes each time, making comparisons difficult.
 It also allows multiple subplots to display both MACD and RSI at the same time.
 
 Plot type can be configured using `type` key. Possible types are:
+
 * `scatter` corresponding to `plotly.graph_objects.Scatter` class (default).
 * `bar` corresponding to `plotly.graph_objects.Bar` class.
 
@@ -182,40 +180,89 @@ Extra parameters to `plotly.graph_objects.*` constructor can be specified in `pl
 Sample configuration with inline comments explaining the process:
 
 ``` python
-    plot_config = {
-        'main_plot': {
-            # Configuration for main plot indicators.
-            # Specifies `ema10` to be red, and `ema50` to be a shade of gray
-            'ema10': {'color': 'red'},
-            'ema50': {'color': '#CCCCCC'},
-            # By omitting color, a random color is selected.
-            'sar': {},
-	    # fill area between senkou_a and senkou_b
-	    'senkou_a': {
-	        'color': 'green', #optional
-	        'fill_to': 'senkou_b',
-	        'fill_label': 'Ichimoku Cloud', #optional
-	        'fill_color': 'rgba(255,76,46,0.2)', #optional
-	    },
-	    # plot senkou_b, too. Not only the area to it.
-	    'senkou_b': {}
+@property
+def plot_config(self):
+    """
+        There are a lot of solutions how to build the return dictionary.
+        The only important point is the return value.
+        Example:
+            plot_config = {'main_plot': {}, 'subplots': {}}
+
+    """
+    plot_config = {}
+    plot_config['main_plot'] = {
+        # Configuration for main plot indicators.
+        # Assumes 2 parameters, emashort and emalong to be specified.
+        f'ema_{self.emashort.value}': {'color': 'red'},
+        f'ema_{self.emalong.value}': {'color': '#CCCCCC'},
+        # By omitting color, a random color is selected.
+        'sar': {},
+        # fill area between senkou_a and senkou_b
+        'senkou_a': {
+            'color': 'green', #optional
+            'fill_to': 'senkou_b',
+            'fill_label': 'Ichimoku Cloud', #optional
+            'fill_color': 'rgba(255,76,46,0.2)', #optional
         },
-        'subplots': {
-            # Create subplot MACD
-            "MACD": {
-                'macd': {'color': 'blue', 'fill_to': 'macdhist'},
-                'macdsignal': {'color': 'orange'},
-                'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
-            },
-            # Additional subplot RSI
-            "RSI": {
-                'rsi': {'color': 'red'}
-            }
+        # plot senkou_b, too. Not only the area to it.
+        'senkou_b': {}
+    }
+    plot_config['subplots'] = {
+         # Create subplot MACD
+        "MACD": {
+            'macd': {'color': 'blue', 'fill_to': 'macdhist'},
+            'macdsignal': {'color': 'orange'},
+            'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
+        },
+        # Additional subplot RSI
+        "RSI": {
+            'rsi': {'color': 'red'}
         }
     }
 
+    return plot_config
 ```
 
+??? Note "As attribute (former method)"
+    Assigning plot_config is also possible as Attribute (this used to be the default way).
+    This has the disadvantage that strategy parameters are not available, preventing certain configurations from working.
+
+    ``` python
+        plot_config = {
+            'main_plot': {
+                # Configuration for main plot indicators.
+                # Specifies `ema10` to be red, and `ema50` to be a shade of gray
+                'ema10': {'color': 'red'},
+                'ema50': {'color': '#CCCCCC'},
+                # By omitting color, a random color is selected.
+                'sar': {},
+            # fill area between senkou_a and senkou_b
+            'senkou_a': {
+                'color': 'green', #optional
+                'fill_to': 'senkou_b',
+                'fill_label': 'Ichimoku Cloud', #optional
+                'fill_color': 'rgba(255,76,46,0.2)', #optional
+            },
+            # plot senkou_b, too. Not only the area to it.
+            'senkou_b': {}
+            },
+            'subplots': {
+                # Create subplot MACD
+                "MACD": {
+                    'macd': {'color': 'blue', 'fill_to': 'macdhist'},
+                    'macdsignal': {'color': 'orange'},
+                    'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
+                },
+                # Additional subplot RSI
+                "RSI": {
+                    'rsi': {'color': 'red'}
+                }
+            }
+        }
+
+    ```
+
+
 !!! Note
     The above configuration assumes that `ema10`, `ema50`, `senkou_a`, `senkou_b`,
     `macd`, `macdsignal`, `macdhist` and `rsi` are columns in the DataFrame created by the strategy.
@@ -223,6 +270,9 @@ Sample configuration with inline comments explaining the process:
 !!! Warning
     `plotly` arguments are only supported with plotly library and will not work with freq-ui.
 
+!!! Note "Trade position adjustments"
+    If `position_adjustment_enable` / `adjust_trade_position()` is used, the trade initial buy price is averaged over multiple orders and the trade start price will most likely appear outside the candle range.
+
 ## Plot profit
 
 ![plot-profit](assets/plot-profit.png)
@@ -233,6 +283,8 @@ The `plot-profit` subcommand shows an interactive graph with three plots:
 * The summarized profit made by backtesting.
 Note that this is not the real-world profit, but more of an estimate.
 * Profit for each individual pair.
+* Parallelism of trades.
+* Underwater (Periods of drawdown).
 
 The first graph is good to get a grip of how the overall market progresses.
 
@@ -242,6 +294,8 @@ This graph will also highlight the start (and end) of the Max drawdown period.
 
 The third graph can be useful to spot outliers, events in pairs that cause profit spikes.
 
+The forth graph can help you analyze trade parallelism, showing how often max_open_trades have been maxed out.
+
 Possible options for the `freqtrade plot-profit` subcommand:
 
 ```
@@ -261,8 +315,8 @@ optional arguments:
                         Specify what timerange of data to use.
   --export EXPORT       Export backtest results, argument are: trades.
                         Example: `--export=trades`
-  --export-filename PATH
-                        Save backtest results to the file with this filename.
+  --export-filename PATH, --backtest-filename PATH
+                        Use backtest results from this filename.
                         Requires `--export` to be set as well. Example:
                         `--export-filename=user_data/backtest_results/backtest
                         _today.json`
@@ -273,7 +327,7 @@ optional arguments:
   --trade-source {DB,file}
                         Specify the source for trades (Can be DB or file
                         (backtest file)) Default: file
-  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
+  -i TIMEFRAME, --timeframe TIMEFRAME
                         Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
   --auto-open           Automatically open generated plot.
 
diff --git a/docs/requirements-docs.txt b/docs/requirements-docs.txt
index 9b7c12a43..8d03a38c3 100644
--- a/docs/requirements-docs.txt
+++ b/docs/requirements-docs.txt
@@ -1,4 +1,5 @@
-mkdocs==1.2.2
-mkdocs-material==7.3.0
+mkdocs==1.3.0
+mkdocs-material==8.2.9
 mdx_truly_sane_lists==1.2
-pymdown-extensions==8.2
+pymdown-extensions==9.3
+jinja2==3.1.1
diff --git a/docs/rest-api.md b/docs/rest-api.md
index b9b2b29be..1ec9b6c12 100644
--- a/docs/rest-api.md
+++ b/docs/rest-api.md
@@ -38,6 +38,11 @@ Sample configuration:
 !!! Danger "Security warning"
     By default, the configuration listens on localhost only (so it's not reachable from other systems). We strongly recommend to not expose this API to the internet and choose a strong, unique password, since others will potentially be able to control your bot.
 
+??? Note "API/UI Access on a remote servers"
+    If you're running on a VPS, you should consider using either a ssh tunnel, or setup a VPN (openVPN, wireguard) to connect to your bot.
+    This will ensure that freqUI is not directly exposed to the internet, which is not recommended for security reasons (freqUI does not support https out of the box).
+    Setup of these tools is not part of this tutorial, however many good tutorials can be found on the internet.
+
 You can then access the API by going to `http://127.0.0.1:8080/api/v1/ping` in a browser to check if the API is running correctly.
 This should return the response:
 
@@ -78,7 +83,7 @@ If you run your bot using docker, you'll need to have the bot listen to incoming
     },
 ```
 
-Uncomment the following from your docker-compose file:
+Make sure that the following 2 lines are available in your docker-compose file:
 
 ```yml
     ports:
@@ -140,9 +145,10 @@ python3 scripts/rest_client.py --config rest_config.json <command> [optional par
 | `locks` | Displays currently locked pairs.
 | `delete_lock <lock_id>` | Deletes (disables) the lock by id.
 | `profit` | Display a summary of your profit/loss from close trades and some stats about your performance.
-| `forcesell <trade_id>` | Instantly sells the given trade  (Ignoring `minimum_roi`).
-| `forcesell all` | Instantly sells all open trades (Ignoring `minimum_roi`).
-| `forcebuy <pair> [rate]` | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
+| `forceexit <trade_id>` | Instantly exits the given trade  (Ignoring `minimum_roi`).
+| `forceexit all` | Instantly exits all open trades (Ignoring `minimum_roi`).
+| `forceenter <pair> [rate]` | Instantly enters the given pair. Rate is optional. (`force_entry_enable` must be set to True)
+| `forceenter <pair> <side> [rate]` | Instantly longs or shorts the given pair. Rate is optional. (`force_entry_enable` must be set to True)
 | `performance` | Show performance of each finished trade grouped by pair.
 | `balance` | Show account balance per currency.
 | `daily <n>` | Shows profit or loss per day, over the last n days (n defaults to 7).
@@ -210,8 +216,15 @@ forcebuy
         :param pair: Pair to buy (ETH/BTC)
         :param price: Optional - price to buy
 
-forcesell
-	Force-sell a trade.
+forceenter
+	Force entering a trade
+
+        :param pair: Pair to buy (ETH/BTC)
+        :param side: 'long' or 'short'
+        :param price: Optional - price to buy
+
+forceexit
+	Force-exit a trade.
 
         :param tradeid: Id of the trade (can be received via status command)
 
@@ -280,6 +293,9 @@ strategy
 
         :param strategy: Strategy class name
 
+sysinfo
+	Provides system information (CPU, RAM usage)
+
 trade
 	Return specific trade
 
@@ -330,12 +346,15 @@ Since the access token has a short timeout (15 min) - the `token/refresh` reques
 
 ### CORS
 
-All web-based front-ends are subject to [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) - Cross-Origin Resource Sharing.
-Since most of the requests to the Freqtrade API must be authenticated, a proper CORS policy is key to avoid security problems.
-Also, the standard disallows `*` CORS policies for requests with credentials, so this setting must be set appropriately.
+This whole section is only necessary in cross-origin cases (where you multiple bot API's running on `localhost:8081`, `localhost:8082`, ...), and want to combine them into one FreqUI instance.
 
-Users can configure this themselves via the `CORS_origins` configuration setting.
-It consists of a list of allowed sites that are allowed to consume resources from the bot's API.
+??? info "Technical explanation"
+    All web-based front-ends are subject to [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) - Cross-Origin Resource Sharing.
+    Since most of the requests to the Freqtrade API must be authenticated, a proper CORS policy is key to avoid security problems.
+    Also, the standard disallows `*` CORS policies for requests with credentials, so this setting must be set appropriately.
+
+Users can allow access from different origin URL's to the bot API via the `CORS_origins` configuration setting.
+It consists of a list of allowed URL's that are allowed to consume resources from the bot's API.
 
 Assuming your application is deployed as `https://frequi.freqtrade.io/home/` - this would mean that the following configuration becomes necessary:
 
@@ -348,5 +367,19 @@ Assuming your application is deployed as `https://frequi.freqtrade.io/home/` - t
 }
 ```
 
+In the following (pretty common) case, FreqUI is accessible on `http://localhost:8080/trade` (this is what you see in your navbar when navigating to freqUI).
+![freqUI url](assets/frequi_url.png)
+
+The correct configuration for this case is `http://localhost:8080` - the main part of the URL including the port.
+
+```jsonc
+{
+    //...
+    "jwt_secret_key": "somethingrandom",
+    "CORS_origins": ["http://localhost:8080"],
+    //...
+}
+```
+
 !!! Note
     We strongly recommend to also set `jwt_secret_key` to something random and known only to yourself to avoid unauthorized access to your bot.
diff --git a/docs/sandbox-testing.md b/docs/sandbox-testing.md
index 5f572eba8..2c0f306cf 100644
--- a/docs/sandbox-testing.md
+++ b/docs/sandbox-testing.md
@@ -104,16 +104,16 @@ To mitigate this, you can try to match the first order on the opposite orderbook
 
 ``` jsonc
   "order_types": {
-    "buy": "limit",
-    "sell": "limit"
+    "entry": "limit",
+    "exit": "limit"
     // ...
   },
-  "bid_strategy": {
-    "price_side": "ask",
+  "entry_pricing": {
+    "price_side": "other",
     // ...
   },
-  "ask_strategy":{
-    "price_side": "bid",
+  "exit_pricing":{
+    "price_side": "other",
     // ...
   },
   ```
diff --git a/docs/sql_cheatsheet.md b/docs/sql_cheatsheet.md
index caa3f53a6..49372b002 100644
--- a/docs/sql_cheatsheet.md
+++ b/docs/sql_cheatsheet.md
@@ -49,14 +49,14 @@ sqlite3
 SELECT * FROM trades;
 ```
 
-## Fix trade still open after a manual sell on the exchange
+## Fix trade still open after a manual exit on the exchange
 
 !!! Warning
-    Manually selling a pair on the exchange will not be detected by the bot and it will try to sell anyway. Whenever possible, forcesell <tradeid> should be used to accomplish the same thing.  
+    Manually selling a pair on the exchange will not be detected by the bot and it will try to sell anyway. Whenever possible, /forceexit <tradeid> should be used to accomplish the same thing.  
     It is strongly advised to backup your database file before making any manual changes.
 
 !!! Note
-    This should not be necessary after /forcesell, as forcesell orders are closed automatically by the bot on the next iteration.
+    This should not be necessary after /forceexit, as force_exit orders are closed automatically by the bot on the next iteration.
 
 ```sql
 UPDATE trades
@@ -65,7 +65,7 @@ SET is_open=0,
   close_rate=<close_rate>,
   close_profit = close_rate / open_rate - 1,
   close_profit_abs = (amount * <close_rate> * (1 - fee_close) - (amount * (open_rate * (1 - fee_open)))),
-  sell_reason=<sell_reason>
+  exit_reason=<exit_reason>
 WHERE id=<trade_ID_to_update>;
 ```
 
@@ -78,7 +78,7 @@ SET is_open=0,
   close_rate=0.19638016,
   close_profit=0.0496,
   close_profit_abs = (amount * 0.19638016 * (1 - fee_close) - (amount * (open_rate * (1 - fee_open)))),
-  sell_reason='force_sell'  
+  exit_reason='force_exit'  
 WHERE id=31;
 ```
 
diff --git a/docs/stoploss.md b/docs/stoploss.md
index ae191f639..573fdbd6c 100644
--- a/docs/stoploss.md
+++ b/docs/stoploss.md
@@ -2,6 +2,7 @@
 
 The `stoploss` configuration parameter is loss as ratio that should trigger a sale.
 For example, value `-0.10` will cause immediate sell if the profit dips below -10% for a given trade. This parameter is optional.
+Stoploss calculations do include fees, so a stoploss of -10% is placed exactly 10% below the entry point.
 
 Most of the strategy files already include the optimal `stoploss` value.
 
@@ -16,21 +17,21 @@ Those stoploss modes can be *on exchange* or *off exchange*.
 These modes can be configured with these values:
 
 ``` python
-    'emergencysell': 'market',
+    'emergency_exit': 'market',
     'stoploss_on_exchange': False
     'stoploss_on_exchange_interval': 60,
     'stoploss_on_exchange_limit_ratio': 0.99
 ```
 
 !!! Note
-    Stoploss on exchange is only supported for Binance (stop-loss-limit), Kraken (stop-loss-market, stop-loss-limit) and FTX (stop limit and stop-market) as of now.  
+    Stoploss on exchange is only supported for Binance (stop-loss-limit), Huobi (stop-limit), Kraken (stop-loss-market, stop-loss-limit), FTX (stop limit and stop-market) Gateio (stop-limit), and Kucoin (stop-limit and stop-market) as of now.  
     <ins>Do not set too low/tight stoploss value if using stop loss on exchange!</ins>  
     If set to low/tight then you have greater risk of missing fill on the order and stoploss will not work.
 
 ### stoploss_on_exchange and stoploss_on_exchange_limit_ratio
 
 Enable or Disable stop loss on exchange.
-If the stoploss is *on exchange* it means a stoploss limit order is placed on the exchange immediately after buy order happens successfully. This will protect you against sudden crashes in market as the order will be in the queue immediately and if market goes down then the order has more chance of being fulfilled.
+If the stoploss is *on exchange* it means a stoploss limit order is placed on the exchange immediately after buy order fills. This will protect you against sudden crashes in market, as the order execution happens purely within the exchange, and has no potential network overhead.
 
 If `stoploss_on_exchange` uses limit orders, the exchange needs 2 prices, the stoploss_price and the Limit price.  
 `stoploss` defines the stop-price where the limit order is placed - and limit should be slightly below this.  
@@ -51,30 +52,30 @@ The bot cannot do these every 5 seconds (at each iteration), otherwise it would
 So this parameter will tell the bot how often it should update the stoploss order. The default value is 60 (1 minute).
 This same logic will reapply a stoploss order on the exchange should you cancel it accidentally.
 
-### forcesell
+### force_exit
 
-`forcesell` is an optional value, which defaults to the same value as `sell` and is used when sending a `/forcesell` command from Telegram or from the Rest API.
+`force_exit` is an optional value, which defaults to the same value as `exit` and is used when sending a `/forceexit` command from Telegram or from the Rest API.
 
-### forcebuy
+### force_entry
 
-`forcebuy` is an optional value, which defaults to the same value as `buy` and is used when sending a `/forcebuy` command from Telegram or from the Rest API.
+`force_entry` is an optional value, which defaults to the same value as `entry` and is used when sending a `/forceentry` command from Telegram or from the Rest API.
 
-### emergencysell
+### emergency_exit
 
-`emergencysell` is an optional value, which defaults to `market` and is used when creating stop loss on exchange orders fails.
+`emergency_exit` is an optional value, which defaults to `market` and is used when creating stop loss on exchange orders fails.
 The below is the default which is used if not changed in strategy or configuration file.
 
 Example from strategy file:
 
 ``` python
 order_types = {
-    'buy': 'limit',
-    'sell': 'limit',
-    'emergencysell': 'market',
-    'stoploss': 'market',
-    'stoploss_on_exchange': True,
-    'stoploss_on_exchange_interval': 60,
-    'stoploss_on_exchange_limit_ratio': 0.99
+    "entry": "limit",
+    "exit": "limit",
+    "emergency_exit": "market",
+    "stoploss": "market",
+    "stoploss_on_exchange": True,
+    "stoploss_on_exchange_interval": 60,
+    "stoploss_on_exchange_limit_ratio": 0.99
 }
 ```
 
@@ -182,7 +183,7 @@ For example, simplified math:
 * the bot buys an asset at a price of 100$
 * the stop loss is defined at -10%
 * the stop loss would get triggered once the asset drops below 90$
-* stoploss will remain at 90$ unless asset increases to or above our configured offset
+* stoploss will remain at 90$ unless asset increases to or above the configured offset
 * assuming the asset now increases to 103$ (where we have the offset configured)
 * the stop loss will now be -2% of 103$ = 100.94$
 * now the asset drops in value to 101\$, the stop loss will still be 100.94$ and would trigger at 100.94$
diff --git a/docs/strategy-advanced.md b/docs/strategy-advanced.md
index b0d1937f6..374c675a2 100644
--- a/docs/strategy-advanced.md
+++ b/docs/strategy-advanced.md
@@ -49,7 +49,7 @@ from freqtrade.exchange import timeframe_to_prev_date
 
 class AwesomeStrategy(IStrategy):
     def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount: float,
-                           rate: float, time_in_force: str, sell_reason: str,
+                           rate: float, time_in_force: str, exit_reason: str,
                            current_time: 'datetime', **kwargs) -> bool:
         # Obtain pair dataframe.
         dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
@@ -77,578 +77,76 @@ class AwesomeStrategy(IStrategy):
 
 ***
 
-## Custom sell signal
-
-It is possible to define custom sell signals, indicating that specified position should be sold. This is very useful when we need to customize sell conditions for each individual trade, or if you need the trade profit to take the sell decision. 
-
-For example you could implement a 1:2 risk-reward ROI with `custom_sell()`.
-
-Using custom_sell() signals in place of stoploss though *is not recommended*. It is a inferior method to using `custom_stoploss()` in this regard - which also allows you to keep the stoploss on exchange.
-
-!!! Note
-    Returning a `string` or `True` from this method is equal to setting sell signal on a candle at specified time. This method is not called when sell signal is set already, or if sell signals are disabled (`use_sell_signal=False` or `sell_profit_only=True` while profit is below `sell_profit_offset`). `string` max length is 64 characters. Exceeding this limit will cause the message to be truncated to 64 characters.
-
-An example of how we can use different indicators depending on the current profit and also sell trades that were open longer than one day:
-
-``` python
-class AwesomeStrategy(IStrategy):
-    def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
-                    current_profit: float, **kwargs):
-        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
-        last_candle = dataframe.iloc[-1].squeeze()
-
-        # Above 20% profit, sell when rsi < 80
-        if current_profit > 0.2:
-            if last_candle['rsi'] < 80:
-                return 'rsi_below_80'
-
-        # Between 2% and 10%, sell if EMA-long above EMA-short
-        if 0.02 < current_profit < 0.1:
-            if last_candle['emalong'] > last_candle['emashort']:
-                return 'ema_long_below_80'
-
-        # Sell any positions at a loss if they are held for more than one day.
-        if current_profit < 0.0 and (current_time - trade.open_date_utc).days >= 1:
-            return 'unclog'
-```
-
-See [Dataframe access](#dataframe-access) for more information about dataframe use in strategy callbacks.
-
-## Buy Tag
+## Enter Tag
 
 When your strategy has multiple buy signals, you can name the signal that triggered.
-Then you can access you buy signal on `custom_sell`
+Then you can access you buy signal on `custom_exit`
 
 ```python
-def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
     dataframe.loc[
         (
             (dataframe['rsi'] < 35) &
             (dataframe['volume'] > 0)
         ),
-        ['buy', 'buy_tag']] = (1, 'buy_signal_rsi')
+        ['enter_long', 'enter_tag']] = (1, 'buy_signal_rsi')
 
     return dataframe
 
-def custom_sell(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
-                    current_profit: float, **kwargs):
+def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
+                current_profit: float, **kwargs):
     dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
     last_candle = dataframe.iloc[-1].squeeze()
-    if trade.buy_tag == 'buy_signal_rsi' and last_candle['rsi'] > 80:
+    if trade.enter_tag == 'buy_signal_rsi' and last_candle['rsi'] > 80:
         return 'sell_signal_rsi'
     return None
 
 ```
 
 !!! Note
-    `buy_tag` is limited to 100 characters, remaining data will be truncated.
+    `enter_tag` is limited to 100 characters, remaining data will be truncated.
 
+## Exit tag
 
-## Custom stoploss
-
-The stoploss price can only ever move upwards - if the stoploss value returned from `custom_stoploss` would result in a lower stoploss price than was previously set, it will be ignored. The traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss.
-
-The usage of the custom stoploss method must be enabled by setting `use_custom_stoploss=True` on the strategy object.
-The method must return a stoploss value (float / number) as a percentage of the current price.
-E.g. If the `current_rate` is 200 USD, then returning `0.02` will set the stoploss price 2% lower, at 196 USD.
-
-The absolute value of the return value is used (the sign is ignored), so returning `0.05` or `-0.05` have the same result, a stoploss 5% below the current price.
-
-To simulate a regular trailing stoploss of 4% (trailing 4% behind the maximum reached price) you would use the following very simple method:
+Similar to [Buy Tagging](#buy-tag), you can also specify a sell tag.
 
 ``` python
-# additional imports required
-from datetime import datetime
-from freqtrade.persistence import Trade
+def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    dataframe.loc[
+        (
+            (dataframe['rsi'] > 70) &
+            (dataframe['volume'] > 0)
+        ),
+        ['exit_long', 'exit_tag']] = (1, 'exit_rsi')
 
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    use_custom_stoploss = True
-
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
-                        current_rate: float, current_profit: float, **kwargs) -> float:
-        """
-        Custom stoploss logic, returning the new distance relative to current_rate (as ratio).
-        e.g. returning -0.05 would create a stoploss 5% below current_rate.
-        The custom stoploss can never be below self.stoploss, which serves as a hard maximum loss.
-
-        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
-
-        When not implemented by a strategy, returns the initial stoploss value
-        Only called when use_custom_stoploss is set to True.
-
-        :param pair: Pair that's currently analyzed
-        :param trade: trade object.
-        :param current_time: datetime object, containing the current datetime
-        :param current_rate: Rate, calculated based on pricing settings in ask_strategy.
-        :param current_profit: Current profit (as ratio), calculated based on current_rate.
-        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        :return float: New stoploss value, relative to the current rate
-        """
-        return -0.04
+    return dataframe
 ```
 
-Stoploss on exchange works similar to `trailing_stop`, and the stoploss on exchange is updated as configured in `stoploss_on_exchange_interval` ([More details about stoploss on exchange](stoploss.md#stop-loss-on-exchange-freqtrade)).
-
-!!! Note "Use of dates"
-    All time-based calculations should be done based on `current_time` - using `datetime.now()` or `datetime.utcnow()` is discouraged, as this will break backtesting support.
-
-!!! Tip "Trailing stoploss"
-    It's recommended to disable `trailing_stop` when using custom stoploss values. Both can work in tandem, but you might encounter the trailing stop to move the price higher while your custom function would not want this, causing conflicting behavior.
-
-### Custom stoploss examples
-
-The next section will show some examples on what's possible with the custom stoploss function.
-Of course, many more things are possible, and all examples can be combined at will.
-
-#### Time based trailing stop
-
-Use the initial stoploss for the first 60 minutes, after this change to 10% trailing stoploss, and after 2 hours (120 minutes) we use a 5% trailing stoploss.
-
-``` python
-from datetime import datetime, timedelta
-from freqtrade.persistence import Trade
-
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    use_custom_stoploss = True
-
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
-                        current_rate: float, current_profit: float, **kwargs) -> float:
-
-        # Make sure you have the longest interval first - these conditions are evaluated from top to bottom.
-        if current_time - timedelta(minutes=120) > trade.open_date_utc:
-            return -0.05
-        elif current_time - timedelta(minutes=60) > trade.open_date_utc:
-            return -0.10
-        return 1
-```
-
-#### Different stoploss per pair
-
-Use a different stoploss depending on the pair.
-In this example, we'll trail the highest price with 10% trailing stoploss for `ETH/BTC` and `XRP/BTC`, with 5% trailing stoploss for `LTC/BTC` and with 15% for all other pairs.
-
-``` python
-from datetime import datetime
-from freqtrade.persistence import Trade
-
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    use_custom_stoploss = True
-
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
-                        current_rate: float, current_profit: float, **kwargs) -> float:
-
-        if pair in ('ETH/BTC', 'XRP/BTC'):
-            return -0.10
-        elif pair in ('LTC/BTC'):
-            return -0.05
-        return -0.15
-```
-
-#### Trailing stoploss with positive offset
-
-Use the initial stoploss until the profit is above 4%, then use a trailing stoploss of 50% of the current profit with a minimum of 2.5% and a maximum of 5%.
-
-Please note that the stoploss can only increase, values lower than the current stoploss are ignored.
-
-``` python
-from datetime import datetime, timedelta
-from freqtrade.persistence import Trade
-
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    use_custom_stoploss = True
-
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
-                        current_rate: float, current_profit: float, **kwargs) -> float:
-
-        if current_profit < 0.04:
-            return -1 # return a value bigger than the initial stoploss to keep using the initial stoploss
-
-        # After reaching the desired offset, allow the stoploss to trail by half the profit
-        desired_stoploss = current_profit / 2
-
-        # Use a minimum of 2.5% and a maximum of 5%
-        return max(min(desired_stoploss, 0.05), 0.025)
-```
-
-#### Calculating stoploss relative to open price
-
-Stoploss values returned from `custom_stoploss()` always specify a percentage relative to `current_rate`. In order to set a stoploss relative to the *open* price, we need to use `current_profit` to calculate what percentage relative to the `current_rate` will give you the same result as if the percentage was specified from the open price.
-
-The helper function [`stoploss_from_open()`](strategy-customization.md#stoploss_from_open) can be used to convert from an open price relative stop, to a current price relative stop which can be returned from `custom_stoploss()`.
-
-### Calculating stoploss percentage from absolute price
-
-Stoploss values returned from `custom_stoploss()` always specify a percentage relative to `current_rate`. In order to set a stoploss at specified absolute price level, we need to use `stop_rate` to calculate what percentage relative to the `current_rate` will give you the same result as if the percentage was specified from the open price.
-
-The helper function [`stoploss_from_absolute()`](strategy-customization.md#stoploss_from_absolute) can be used to convert from an absolute price, to a current price relative stop which can be returned from `custom_stoploss()`.
-
-#### Stepped stoploss
-
-Instead of continuously trailing behind the current price, this example sets fixed stoploss price levels based on the current profit.
-
-* Use the regular stoploss until 20% profit is reached
-* Once profit is > 20% - set stoploss to 7% above open price.
-* Once profit is > 25% - set stoploss to 15% above open price.
-* Once profit is > 40% - set stoploss to 25% above open price.
-
-``` python
-from datetime import datetime
-from freqtrade.persistence import Trade
-from freqtrade.strategy import stoploss_from_open
-
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    use_custom_stoploss = True
-
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
-                        current_rate: float, current_profit: float, **kwargs) -> float:
-
-        # evaluate highest to lowest, so that highest possible stop is used
-        if current_profit > 0.40:
-            return stoploss_from_open(0.25, current_profit)
-        elif current_profit > 0.25:
-            return stoploss_from_open(0.15, current_profit)
-        elif current_profit > 0.20:
-            return stoploss_from_open(0.07, current_profit)
-
-        # return maximum stoploss value, keeping current stoploss price unchanged
-        return 1
-```
-
-#### Custom stoploss using an indicator from dataframe example
-
-Absolute stoploss value may be derived from indicators stored in dataframe. Example uses parabolic SAR below the price as stoploss.
-
-``` python
-class AwesomeStrategy(IStrategy):
-
-    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        # <...>
-        dataframe['sar'] = ta.SAR(dataframe)
-
-    use_custom_stoploss = True
-
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
-                        current_rate: float, current_profit: float, **kwargs) -> float:
-
-        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
-        last_candle = dataframe.iloc[-1].squeeze()
-
-        # Use parabolic sar as absolute stoploss price
-        stoploss_price = last_candle['sar']
-
-        # Convert absolute price to percentage relative to current_rate
-        if stoploss_price < current_rate:
-            return (stoploss_price / current_rate) - 1
-
-        # return maximum stoploss value, keeping current stoploss price unchanged
-        return 1
-```
-
-See [Dataframe access](#dataframe-access) for more information about dataframe use in strategy callbacks.
-
----
-
-## Custom order price rules
-
-By default, freqtrade use the orderbook to automatically set an order price([Relevant documentation](configuration.md#prices-used-for-orders)), you also have the option to create custom order prices based on your strategy.
-
-You can use this feature by creating a `custom_entry_price()` function in your strategy file to customize entry prices and `custom_exit_price()` for exits.
+The provided exit-tag is then used as sell-reason - and shown as such in backtest results.
 
 !!! Note
-    If your custom pricing function return None or an invalid value, price will fall back to `proposed_rate`, which is based on the regular pricing configuration.
+    `exit_reason` is limited to 100 characters, remaining data will be truncated.
 
-### Custom order entry and exit price example
+## Strategy version
+
+You can implement custom strategy versioning by using the "version" method, and returning the version you would like this strategy to have.
 
 ``` python
-from datetime import datetime, timedelta, timezone
-from freqtrade.persistence import Trade
-
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    def custom_entry_price(self, pair: str, current_time: datetime,
-                           proposed_rate, **kwargs) -> float:
-
-        dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
-                                                                timeframe=self.timeframe)
-        new_entryprice = dataframe['bollinger_10_lowerband'].iat[-1]
-        
-        return new_entryprice
-
-    def custom_exit_price(self, pair: str, trade: Trade,
-                          current_time: datetime, proposed_rate: float,
-                          current_profit: float, **kwargs) -> float:
-
-        dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
-                                                                timeframe=self.timeframe)
-        new_exitprice = dataframe['bollinger_10_upperband'].iat[-1]
-        
-        return new_exitprice
-
-```
-
-!!! Warning
-    Modifying entry and exit prices will only work for limit orders. Depending on the price chosen, this can result in a lot of unfilled orders. By default the maximum allowed distance between the current price and the custom price is 2%, this value can be changed in config with the `custom_price_max_distance_ratio` parameter.
-
-!!! Example
-    If the new_entryprice is 97, the proposed_rate is 100 and the `custom_price_max_distance_ratio` is set to 2%, The retained valid custom entry price will be 98.
-
-!!! Warning "No backtesting support"
-    Custom entry-prices are currently not supported during backtesting.
-
-## Custom order timeout rules
-
-Simple, time-based order-timeouts can be configured either via strategy or in the configuration in the `unfilledtimeout` section.
-
-However, freqtrade also offers a custom callback for both order types, which allows you to decide based on custom criteria if an order did time out or not.
-
-!!! Note
-    Unfilled order timeouts are not relevant during backtesting or hyperopt, and are only relevant during real (live) trading. Therefore these methods are only called in these circumstances.
-
-### Custom order timeout example
-
-A simple example, which applies different unfilled-timeouts depending on the price of the asset can be seen below.
-It applies a tight timeout for higher priced assets, while allowing more time to fill on cheap coins.
-
-The function must return either `True` (cancel order) or `False` (keep order alive).
-
-``` python
-from datetime import datetime, timedelta, timezone
-from freqtrade.persistence import Trade
-
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    # Set unfilledtimeout to 25 hours, since our maximum timeout from below is 24 hours.
-    unfilledtimeout = {
-        'buy': 60 * 25,
-        'sell': 60 * 25
-    }
-
-    def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
-        if trade.open_rate > 100 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=5):
-            return True
-        elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3):
-            return True
-        elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24):
-           return True
-        return False
-
-
-    def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
-        if trade.open_rate > 100 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=5):
-            return True
-        elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3):
-            return True
-        elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24):
-           return True
-        return False
+def version(self) -> str:
+    """
+    Returns version of the strategy.
+    """
+    return "1.1"
 ```
 
 !!! Note
-    For the above example, `unfilledtimeout` must be set to something bigger than 24h, otherwise that type of timeout will apply first.
-
-### Custom order timeout example (using additional data)
-
-``` python
-from datetime import datetime
-from freqtrade.persistence import Trade
-
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    # Set unfilledtimeout to 25 hours, since our maximum timeout from below is 24 hours.
-    unfilledtimeout = {
-        'buy': 60 * 25,
-        'sell': 60 * 25
-    }
-
-    def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
-        ob = self.dp.orderbook(pair, 1)
-        current_price = ob['bids'][0][0]
-        # Cancel buy order if price is more than 2% above the order.
-        if current_price > order['price'] * 1.02:
-            return True
-        return False
-
-
-    def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
-        ob = self.dp.orderbook(pair, 1)
-        current_price = ob['asks'][0][0]
-        # Cancel sell order if price is more than 2% below the order.
-        if current_price < order['price'] * 0.98:
-            return True
-        return False
-```
-
----
-
-## Bot loop start callback
-
-A simple callback which is called once at the start of every bot throttling iteration.
-This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc.
-
-``` python
-import requests
-
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    def bot_loop_start(self, **kwargs) -> None:
-        """
-        Called at the start of the bot iteration (one loop).
-        Might be used to perform pair-independent tasks
-        (e.g. gather some remote resource for comparison)
-        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        """
-        if self.config['runmode'].value in ('live', 'dry_run'):
-            # Assign this to the class by using self.*
-            # can then be used by populate_* methods
-            self.remote_data = requests.get('https://some_remote_source.example.com')
-
-```
-
-## Bot order confirmation
-
-### Trade entry (buy order) confirmation
-
-`confirm_trade_entry()` can be used to abort a trade entry at the latest second (maybe because the price is not what we expect).
-
-``` python
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
-                            time_in_force: str, current_time: datetime, **kwargs) -> bool:
-        """
-        Called right before placing a buy order.
-        Timing for this function is critical, so avoid doing heavy computations or
-        network requests in this method.
-
-        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
-
-        When not implemented by a strategy, returns True (always confirming).
-
-        :param pair: Pair that's about to be bought.
-        :param order_type: Order type (as configured in order_types). usually limit or market.
-        :param amount: Amount in target (quote) currency that's going to be traded.
-        :param rate: Rate that's going to be used when using limit orders
-        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
-        :param current_time: datetime object, containing the current datetime
-        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        :return bool: When True is returned, then the buy-order is placed on the exchange.
-            False aborts the process
-        """
-        return True
-
-```
-
-### Trade exit (sell order) confirmation
-
-`confirm_trade_exit()` can be used to abort a trade exit (sell) at the latest second (maybe because the price is not what we expect).
-
-``` python
-from freqtrade.persistence import Trade
-
-
-class AwesomeStrategy(IStrategy):
-
-    # ... populate_* methods
-
-    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
-                           rate: float, time_in_force: str, sell_reason: str,
-                           current_time: datetime, **kwargs) -> bool:
-        """
-        Called right before placing a regular sell order.
-        Timing for this function is critical, so avoid doing heavy computations or
-        network requests in this method.
-
-        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
-
-        When not implemented by a strategy, returns True (always confirming).
-
-        :param pair: Pair that's about to be sold.
-        :param order_type: Order type (as configured in order_types). usually limit or market.
-        :param amount: Amount in quote currency.
-        :param rate: Rate that's going to be used when using limit orders
-        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
-        :param sell_reason: Sell reason.
-            Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
-                           'sell_signal', 'force_sell', 'emergency_sell']
-        :param current_time: datetime object, containing the current datetime
-        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        :return bool: When True is returned, then the sell-order is placed on the exchange.
-            False aborts the process
-        """
-        if sell_reason == 'force_sell' and trade.calc_profit_ratio(rate) < 0:
-            # Reject force-sells with negative profit
-            # This is just a sample, please adjust to your needs
-            # (this does not necessarily make sense, assuming you know when you're force-selling)
-            return False
-        return True
-
-```
-
-### Stake size management
-
-It is possible to manage your risk by reducing or increasing stake amount when placing a new trade.
-
-```python
-class AwesomeStrategy(IStrategy):
-    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
-                            proposed_stake: float, min_stake: float, max_stake: float,
-                            **kwargs) -> float:
-
-        dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
-        current_candle = dataframe.iloc[-1].squeeze()
-
-        if current_candle['fastk_rsi_1h'] > current_candle['fastd_rsi_1h']:
-            if self.config['stake_amount'] == 'unlimited':
-                # Use entire available wallet during favorable conditions when in compounding mode.
-                return max_stake
-            else:
-                # Compound profits during favorable conditions instead of using a static stake.
-                return self.wallets.get_total_stake_amount() / self.config['max_open_trades']
-
-        # Use default stake amount.
-        return proposed_stake
-```
-
-Freqtrade will fall back to the `proposed_stake` value should your code raise an exception. The exception itself will be logged.
-
-!!! Tip
-    You do not _have_ to ensure that `min_stake <= returned_value <= max_stake`. Trades will succeed as the returned value will be clamped to supported range and this acton will be logged.
-
-!!! Tip
-    Returning `0` or `None` will prevent trades from being placed.
-
----
+    You should make sure to implement proper version control (like a git repository) alongside this, as freqtrade will not keep historic versions of your strategy, so it's up to the user to be able to eventually roll back to a prior version of the strategy.
 
 ## Derived strategies
 
 The strategies can be derived from other strategies. This avoids duplication of your custom strategy code. You can use this technique to override small parts of your main strategy, leaving the rest untouched:
 
-``` python
+``` python title="user_data/strategies/myawesomestrategy.py"
 class MyAwesomeStrategy(IStrategy):
     ...
     stoploss = 0.13
@@ -657,6 +155,10 @@ class MyAwesomeStrategy(IStrategy):
     # should be in any custom strategy...
     ...
 
+```
+
+``` python title="user_data/strategies/MyAwesomeStrategy2.py"
+from myawesomestrategy import MyAwesomeStrategy
 class MyAwesomeStrategy2(MyAwesomeStrategy):
     # Override something
     stoploss = 0.08
@@ -665,16 +167,7 @@ class MyAwesomeStrategy2(MyAwesomeStrategy):
 
 Both attributes and methods may be overridden, altering behavior of the original strategy in a way you need.
 
-!!! Note "Parent-strategy in different files"
-    If you have the parent-strategy in a different file, you'll need to add the following to the top of your "child"-file to ensure proper loading, otherwise freqtrade may not be able to load the parent strategy correctly.
-
-    ``` python
-    import sys
-    from pathlib import Path
-    sys.path.append(str(Path(__file__).parent))
-
-    from myawesomestrategy import MyAwesomeStrategy
-    ```
+While keeping the subclass in the same file is technically possible, it can lead to some problems with hyperopt parameter files, we therefore recommend to use separate strategy files, and import the parent strategy as shown above.
 
 ## Embedding Strategies
 
@@ -724,9 +217,9 @@ should be rewritten to
 ```python
 frames = [dataframe]
 for val in self.buy_ema_short.range:
-    frames.append({
+    frames.append(DataFrame({
         f'ema_short_{val}': ta.EMA(dataframe, timeperiod=val)
-    })
+    }))
 
 # Append columns to existing dataframe
 merged_frame = pd.concat(frames, axis=1)
diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md
new file mode 100644
index 000000000..7ec600a58
--- /dev/null
+++ b/docs/strategy-callbacks.md
@@ -0,0 +1,718 @@
+# Strategy Callbacks
+
+While the main strategy functions (`populate_indicators()`, `populate_entry_trend()`, `populate_exit_trend()`) should be used in a vectorized way, and are only called [once during backtesting](bot-basics.md#backtesting-hyperopt-execution-logic), callbacks are called "whenever needed".
+
+As such, you should avoid doing heavy calculations in callbacks to avoid delays during operations.
+Depending on the callback used, they may be called when entering / exiting a trade, or throughout the duration of a trade.
+
+Currently available callbacks:
+
+* [`bot_loop_start()`](#bot-loop-start)
+* [`custom_stake_amount()`](#stake-size-management)
+* [`custom_exit()`](#custom-exit-signal)
+* [`custom_stoploss()`](#custom-stoploss)
+* [`custom_entry_price()` and `custom_exit_price()`](#custom-order-price-rules)
+* [`check_entry_timeout()` and `check_exit_timeout()`](#custom-order-timeout-rules)
+* [`confirm_trade_entry()`](#trade-entry-buy-order-confirmation)
+* [`confirm_trade_exit()`](#trade-exit-sell-order-confirmation)
+* [`adjust_trade_position()`](#adjust-trade-position)
+* [`leverage()`](#leverage-callback)
+
+!!! Tip "Callback calling sequence"
+    You can find the callback calling sequence in [bot-basics](bot-basics.md#bot-execution-logic)
+
+## Bot loop start
+
+A simple callback which is called once at the start of every bot throttling iteration (roughly every 5 seconds, unless configured differently).
+This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc.
+
+``` python
+import requests
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def bot_loop_start(self, **kwargs) -> None:
+        """
+        Called at the start of the bot iteration (one loop).
+        Might be used to perform pair-independent tasks
+        (e.g. gather some remote resource for comparison)
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        """
+        if self.config['runmode'].value in ('live', 'dry_run'):
+            # Assign this to the class by using self.*
+            # can then be used by populate_* methods
+            self.remote_data = requests.get('https://some_remote_source.example.com')
+
+```
+
+### Stake size management
+
+Called before entering a trade, makes it possible to manage your position size when placing a new trade.
+
+```python
+class AwesomeStrategy(IStrategy):
+    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
+                            proposed_stake: float, min_stake: float, max_stake: float,
+                            entry_tag: Optional[str], side: str, **kwargs) -> float:
+
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
+        current_candle = dataframe.iloc[-1].squeeze()
+
+        if current_candle['fastk_rsi_1h'] > current_candle['fastd_rsi_1h']:
+            if self.config['stake_amount'] == 'unlimited':
+                # Use entire available wallet during favorable conditions when in compounding mode.
+                return max_stake
+            else:
+                # Compound profits during favorable conditions instead of using a static stake.
+                return self.wallets.get_total_stake_amount() / self.config['max_open_trades']
+
+        # Use default stake amount.
+        return proposed_stake
+```
+
+Freqtrade will fall back to the `proposed_stake` value should your code raise an exception. The exception itself will be logged.
+
+!!! Tip
+    You do not _have_ to ensure that `min_stake <= returned_value <= max_stake`. Trades will succeed as the returned value will be clamped to supported range and this action will be logged.
+
+!!! Tip
+    Returning `0` or `None` will prevent trades from being placed.
+
+## Custom exit signal
+
+Called for open trade every throttling iteration (roughly every 5 seconds) until a trade is closed.
+
+Allows to define custom exit signals, indicating that specified position should be sold. This is very useful when we need to customize exit conditions for each individual trade, or if you need trade data to make an exit decision.
+
+For example you could implement a 1:2 risk-reward ROI with `custom_exit()`.
+
+Using `custom_exit()` signals in place of stoploss though *is not recommended*. It is a inferior method to using `custom_stoploss()` in this regard - which also allows you to keep the stoploss on exchange.
+
+!!! Note
+    Returning a (none-empty) `string` or `True` from this method is equal to setting exit signal on a candle at specified time. This method is not called when exit signal is set already, or if exit signals are disabled (`use_exit_signal=False`). `string` max length is 64 characters. Exceeding this limit will cause the message to be truncated to 64 characters.
+    `custom_exit()` will ignore `exit_profit_only`, and will always be called unless `use_exit_signal=False`, even if there is a new enter signal.
+
+An example of how we can use different indicators depending on the current profit and also exit trades that were open longer than one day:
+
+``` python
+class AwesomeStrategy(IStrategy):
+    def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
+                    current_profit: float, **kwargs):
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last_candle = dataframe.iloc[-1].squeeze()
+
+        # Above 20% profit, sell when rsi < 80
+        if current_profit > 0.2:
+            if last_candle['rsi'] < 80:
+                return 'rsi_below_80'
+
+        # Between 2% and 10%, sell if EMA-long above EMA-short
+        if 0.02 < current_profit < 0.1:
+            if last_candle['emalong'] > last_candle['emashort']:
+                return 'ema_long_below_80'
+
+        # Sell any positions at a loss if they are held for more than one day.
+        if current_profit < 0.0 and (current_time - trade.open_date_utc).days >= 1:
+            return 'unclog'
+```
+
+See [Dataframe access](strategy-advanced.md#dataframe-access) for more information about dataframe use in strategy callbacks.
+
+## Custom stoploss
+
+Called for open trade every throttling iteration (roughly every 5 seconds) until a trade is closed.
+
+The usage of the custom stoploss method must be enabled by setting `use_custom_stoploss=True` on the strategy object.
+
+The stoploss price can only ever move upwards - if the stoploss value returned from `custom_stoploss` would result in a lower stoploss price than was previously set, it will be ignored. The traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss (before this method is called for the first time for a trade).
+
+The method must return a stoploss value (float / number) as a percentage of the current price.
+E.g. If the `current_rate` is 200 USD, then returning `0.02` will set the stoploss price 2% lower, at 196 USD.
+
+The absolute value of the return value is used (the sign is ignored), so returning `0.05` or `-0.05` have the same result, a stoploss 5% below the current price.
+
+To simulate a regular trailing stoploss of 4% (trailing 4% behind the maximum reached price) you would use the following very simple method:
+
+``` python
+# additional imports required
+from datetime import datetime
+from freqtrade.persistence import Trade
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    use_custom_stoploss = True
+
+    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+                        current_rate: float, current_profit: float, **kwargs) -> float:
+        """
+        Custom stoploss logic, returning the new distance relative to current_rate (as ratio).
+        e.g. returning -0.05 would create a stoploss 5% below current_rate.
+        The custom stoploss can never be below self.stoploss, which serves as a hard maximum loss.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns the initial stoploss value
+        Only called when use_custom_stoploss is set to True.
+
+        :param pair: Pair that's currently analyzed
+        :param trade: trade object.
+        :param current_time: datetime object, containing the current datetime
+        :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
+        :param current_profit: Current profit (as ratio), calculated based on current_rate.
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return float: New stoploss value, relative to the current rate
+        """
+        return -0.04
+```
+
+Stoploss on exchange works similar to `trailing_stop`, and the stoploss on exchange is updated as configured in `stoploss_on_exchange_interval` ([More details about stoploss on exchange](stoploss.md#stop-loss-on-exchange-freqtrade)).
+
+!!! Note "Use of dates"
+    All time-based calculations should be done based on `current_time` - using `datetime.now()` or `datetime.utcnow()` is discouraged, as this will break backtesting support.
+
+!!! Tip "Trailing stoploss"
+    It's recommended to disable `trailing_stop` when using custom stoploss values. Both can work in tandem, but you might encounter the trailing stop to move the price higher while your custom function would not want this, causing conflicting behavior.
+
+### Custom stoploss examples
+
+The next section will show some examples on what's possible with the custom stoploss function.
+Of course, many more things are possible, and all examples can be combined at will.
+
+#### Time based trailing stop
+
+Use the initial stoploss for the first 60 minutes, after this change to 10% trailing stoploss, and after 2 hours (120 minutes) we use a 5% trailing stoploss.
+
+``` python
+from datetime import datetime, timedelta
+from freqtrade.persistence import Trade
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    use_custom_stoploss = True
+
+    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+                        current_rate: float, current_profit: float, **kwargs) -> float:
+
+        # Make sure you have the longest interval first - these conditions are evaluated from top to bottom.
+        if current_time - timedelta(minutes=120) > trade.open_date_utc:
+            return -0.05
+        elif current_time - timedelta(minutes=60) > trade.open_date_utc:
+            return -0.10
+        return 1
+```
+
+#### Different stoploss per pair
+
+Use a different stoploss depending on the pair.
+In this example, we'll trail the highest price with 10% trailing stoploss for `ETH/BTC` and `XRP/BTC`, with 5% trailing stoploss for `LTC/BTC` and with 15% for all other pairs.
+
+``` python
+from datetime import datetime
+from freqtrade.persistence import Trade
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    use_custom_stoploss = True
+
+    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+                        current_rate: float, current_profit: float, **kwargs) -> float:
+
+        if pair in ('ETH/BTC', 'XRP/BTC'):
+            return -0.10
+        elif pair in ('LTC/BTC'):
+            return -0.05
+        return -0.15
+```
+
+#### Trailing stoploss with positive offset
+
+Use the initial stoploss until the profit is above 4%, then use a trailing stoploss of 50% of the current profit with a minimum of 2.5% and a maximum of 5%.
+
+Please note that the stoploss can only increase, values lower than the current stoploss are ignored.
+
+``` python
+from datetime import datetime, timedelta
+from freqtrade.persistence import Trade
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    use_custom_stoploss = True
+
+    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+                        current_rate: float, current_profit: float, **kwargs) -> float:
+
+        if current_profit < 0.04:
+            return -1 # return a value bigger than the initial stoploss to keep using the initial stoploss
+
+        # After reaching the desired offset, allow the stoploss to trail by half the profit
+        desired_stoploss = current_profit / 2
+
+        # Use a minimum of 2.5% and a maximum of 5%
+        return max(min(desired_stoploss, 0.05), 0.025)
+```
+
+#### Stepped stoploss
+
+Instead of continuously trailing behind the current price, this example sets fixed stoploss price levels based on the current profit.
+
+* Use the regular stoploss until 20% profit is reached
+* Once profit is > 20% - set stoploss to 7% above open price.
+* Once profit is > 25% - set stoploss to 15% above open price.
+* Once profit is > 40% - set stoploss to 25% above open price.
+
+``` python
+from datetime import datetime
+from freqtrade.persistence import Trade
+from freqtrade.strategy import stoploss_from_open
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    use_custom_stoploss = True
+
+    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+                        current_rate: float, current_profit: float, **kwargs) -> float:
+
+        # evaluate highest to lowest, so that highest possible stop is used
+        if current_profit > 0.40:
+            return stoploss_from_open(0.25, current_profit, is_short=trade.is_short)
+        elif current_profit > 0.25:
+            return stoploss_from_open(0.15, current_profit, is_short=trade.is_short)
+        elif current_profit > 0.20:
+            return stoploss_from_open(0.07, current_profit, is_short=trade.is_short)
+
+        # return maximum stoploss value, keeping current stoploss price unchanged
+        return 1
+```
+
+#### Custom stoploss using an indicator from dataframe example
+
+Absolute stoploss value may be derived from indicators stored in dataframe. Example uses parabolic SAR below the price as stoploss.
+
+``` python
+class AwesomeStrategy(IStrategy):
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # <...>
+        dataframe['sar'] = ta.SAR(dataframe)
+
+    use_custom_stoploss = True
+
+    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+                        current_rate: float, current_profit: float, **kwargs) -> float:
+
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last_candle = dataframe.iloc[-1].squeeze()
+
+        # Use parabolic sar as absolute stoploss price
+        stoploss_price = last_candle['sar']
+
+        # Convert absolute price to percentage relative to current_rate
+        if stoploss_price < current_rate:
+            return (stoploss_price / current_rate) - 1
+
+        # return maximum stoploss value, keeping current stoploss price unchanged
+        return 1
+```
+
+See [Dataframe access](strategy-advanced.md#dataframe-access) for more information about dataframe use in strategy callbacks.
+
+### Common helpers for stoploss calculations
+
+#### Stoploss relative to open price
+
+Stoploss values returned from `custom_stoploss()` always specify a percentage relative to `current_rate`. In order to set a stoploss relative to the *open* price, we need to use `current_profit` to calculate what percentage relative to the `current_rate` will give you the same result as if the percentage was specified from the open price.
+
+The helper function [`stoploss_from_open()`](strategy-customization.md#stoploss_from_open) can be used to convert from an open price relative stop, to a current price relative stop which can be returned from `custom_stoploss()`.
+
+#### Stoploss percentage from absolute price
+
+Stoploss values returned from `custom_stoploss()` always specify a percentage relative to `current_rate`. In order to set a stoploss at specified absolute price level, we need to use `stop_rate` to calculate what percentage relative to the `current_rate` will give you the same result as if the percentage was specified from the open price.
+
+The helper function [`stoploss_from_absolute()`](strategy-customization.md#stoploss_from_absolute) can be used to convert from an absolute price, to a current price relative stop which can be returned from `custom_stoploss()`.
+
+---
+
+## Custom order price rules
+
+By default, freqtrade use the orderbook to automatically set an order price([Relevant documentation](configuration.md#prices-used-for-orders)), you also have the option to create custom order prices based on your strategy.
+
+You can use this feature by creating a `custom_entry_price()` function in your strategy file to customize entry prices and `custom_exit_price()` for exits.
+
+Each of these methods are called right before placing an order on the exchange.
+
+!!! Note
+    If your custom pricing function return None or an invalid value, price will fall back to `proposed_rate`, which is based on the regular pricing configuration.
+
+### Custom order entry and exit price example
+
+``` python
+from datetime import datetime, timedelta, timezone
+from freqtrade.persistence import Trade
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float, 
+                           entry_tag: Optional[str], side: str, **kwargs) -> float:
+
+        dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
+                                                                timeframe=self.timeframe)
+        new_entryprice = dataframe['bollinger_10_lowerband'].iat[-1]
+        
+        return new_entryprice
+
+    def custom_exit_price(self, pair: str, trade: Trade,
+                          current_time: datetime, proposed_rate: float,
+                          current_profit: float, **kwargs) -> float:
+
+        dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
+                                                                timeframe=self.timeframe)
+        new_exitprice = dataframe['bollinger_10_upperband'].iat[-1]
+        
+        return new_exitprice
+
+```
+
+!!! Warning
+    Modifying entry and exit prices will only work for limit orders. Depending on the price chosen, this can result in a lot of unfilled orders. By default the maximum allowed distance between the current price and the custom price is 2%, this value can be changed in config with the `custom_price_max_distance_ratio` parameter.  
+    **Example**:  
+    If the new_entryprice is 97, the proposed_rate is 100 and the `custom_price_max_distance_ratio` is set to 2%, The retained valid custom entry price will be 98, which is 2% below the current (proposed) rate.
+
+!!! Warning "Backtesting"
+    Custom prices are supported in backtesting (starting with 2021.12), and orders will fill if the price falls within the candle's low/high range.
+    Orders that don't fill immediately are subject to regular timeout handling, which happens once per (detail) candle.
+    `custom_exit_price()` is only called for sells of type exit_signal and Custom exit. All other exit-types will use regular backtesting prices.
+
+## Custom order timeout rules
+
+Simple, time-based order-timeouts can be configured either via strategy or in the configuration in the `unfilledtimeout` section.
+
+However, freqtrade also offers a custom callback for both order types, which allows you to decide based on custom criteria if an order did time out or not.
+
+!!! Note
+    Backtesting fills orders if their price falls within the candle's low/high range.
+    The below callbacks will be called once per (detail) candle for orders that don't fill immediately (which use custom pricing).
+
+### Custom order timeout example
+
+Called for every open order until that order is either filled or cancelled.
+`check_entry_timeout()` is called for trade entries, while `check_exit_timeout()` is called for trade exit orders.
+
+A simple example, which applies different unfilled-timeouts depending on the price of the asset can be seen below.
+It applies a tight timeout for higher priced assets, while allowing more time to fill on cheap coins.
+
+The function must return either `True` (cancel order) or `False` (keep order alive).
+
+``` python
+from datetime import datetime, timedelta
+from freqtrade.persistence import Trade, Order
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    # Set unfilledtimeout to 25 hours, since the maximum timeout from below is 24 hours.
+    unfilledtimeout = {
+        'entry': 60 * 25,
+        'exit': 60 * 25
+    }
+
+    def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order', 
+                            current_time: datetime, **kwargs) -> bool:
+        if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
+            return True
+        elif trade.open_rate > 10 and trade.open_date_utc < current_time - timedelta(minutes=3):
+            return True
+        elif trade.open_rate < 1 and trade.open_date_utc < current_time - timedelta(hours=24):
+           return True
+        return False
+
+
+    def check_exit_timeout(self, pair: str, trade: Trade, order: 'Order',
+                           current_time: datetime, **kwargs) -> bool:
+        if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
+            return True
+        elif trade.open_rate > 10 and trade.open_date_utc < current_time - timedelta(minutes=3):
+            return True
+        elif trade.open_rate < 1 and trade.open_date_utc < current_time - timedelta(hours=24):
+           return True
+        return False
+```
+
+!!! Note
+    For the above example, `unfilledtimeout` must be set to something bigger than 24h, otherwise that type of timeout will apply first.
+
+### Custom order timeout example (using additional data)
+
+``` python
+from datetime import datetime
+from freqtrade.persistence import Trade, Order
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    # Set unfilledtimeout to 25 hours, since the maximum timeout from below is 24 hours.
+    unfilledtimeout = {
+        'entry': 60 * 25,
+        'exit': 60 * 25
+    }
+
+    def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order',
+                            current_time: datetime, **kwargs) -> bool:
+        ob = self.dp.orderbook(pair, 1)
+        current_price = ob['bids'][0][0]
+        # Cancel buy order if price is more than 2% above the order.
+        if current_price > order.price * 1.02:
+            return True
+        return False
+
+
+    def check_exit_timeout(self, pair: str, trade: 'Trade', order: 'Order',
+                           current_time: datetime, **kwargs) -> bool:
+        ob = self.dp.orderbook(pair, 1)
+        current_price = ob['asks'][0][0]
+        # Cancel sell order if price is more than 2% below the order.
+        if current_price < order.price * 0.98:
+            return True
+        return False
+```
+
+---
+
+## Bot order confirmation
+
+Confirm trade entry / exits.
+This are the last methods that will be called before an order is placed.
+
+### Trade entry (buy order) confirmation
+
+`confirm_trade_entry()` can be used to abort a trade entry at the latest second (maybe because the price is not what we expect).
+
+``` python
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
+                            time_in_force: str, current_time: datetime, entry_tag: Optional[str], 
+                            side: str, **kwargs) -> bool:
+        """
+        Called right before placing a entry order.
+        Timing for this function is critical, so avoid doing heavy computations or
+        network requests in this method.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns True (always confirming).
+
+        :param pair: Pair that's about to be bought/shorted.
+        :param order_type: Order type (as configured in order_types). usually limit or market.
+        :param amount: Amount in target (quote) currency that's going to be traded.
+        :param rate: Rate that's going to be used when using limit orders
+        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+        :param current_time: datetime object, containing the current datetime
+        :param side: 'long' or 'short' - indicating the direction of the proposed trade
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the buy-order is placed on the exchange.
+            False aborts the process
+        """
+        return True
+
+```
+
+### Trade exit (sell order) confirmation
+
+`confirm_trade_exit()` can be used to abort a trade exit (sell) at the latest second (maybe because the price is not what we expect).
+
+``` python
+from freqtrade.persistence import Trade
+
+
+class AwesomeStrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
+                           rate: float, time_in_force: str, exit_reason: str,
+                           current_time: datetime, **kwargs) -> bool:
+        """
+        Called right before placing a regular sell order.
+        Timing for this function is critical, so avoid doing heavy computations or
+        network requests in this method.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns True (always confirming).
+
+        :param pair: Pair that's about to be sold.
+        :param order_type: Order type (as configured in order_types). usually limit or market.
+        :param amount: Amount in quote currency.
+        :param rate: Rate that's going to be used when using limit orders
+        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+        :param exit_reason: Exit reason.
+            Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
+                           'exit_signal', 'force_exit', 'emergency_exit']
+        :param current_time: datetime object, containing the current datetime
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the exit-order is placed on the exchange.
+            False aborts the process
+        """
+        if exit_reason == 'force_exit' and trade.calc_profit_ratio(rate) < 0:
+            # Reject force-sells with negative profit
+            # This is just a sample, please adjust to your needs
+            # (this does not necessarily make sense, assuming you know when you're force-selling)
+            return False
+        return True
+
+```
+
+## Adjust trade position
+
+The `position_adjustment_enable` strategy property enables the usage of `adjust_trade_position()` callback in the strategy.
+For performance reasons, it's disabled by default and freqtrade will show a warning message on startup if enabled.
+`adjust_trade_position()` can be used to perform additional orders, for example to manage risk with DCA (Dollar Cost Averaging).
+
+`max_entry_position_adjustment` property is used to limit the number of additional buys per trade (on top of the first buy) that the bot can execute. By default, the value is -1 which means the bot have no limit on number of adjustment buys.
+
+The strategy is expected to return a stake_amount (in stake currency) between `min_stake` and `max_stake` if and when an additional buy order should be made (position is increased).
+If there are not enough funds in the wallet (the return value is above `max_stake`) then the signal will be ignored.
+Additional orders also result in additional fees and those orders don't count towards `max_open_trades`.
+
+This callback is **not** called when there is an open order (either buy or sell) waiting for execution, or when you have reached the maximum amount of extra buys that you have set on `max_entry_position_adjustment`.
+`adjust_trade_position()` is called very frequently for the duration of a trade, so you must keep your implementation as performant as possible.
+
+Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position, no matter if it's a long or short trade. Modifications to leverage are not possible.
+
+!!! Note "About stake size"
+    Using fixed stake size means it will be the amount used for the first order, just like without position adjustment.
+    If you wish to buy additional orders with DCA, then make sure to leave enough funds in the wallet for that.
+    Using 'unlimited' stake amount with DCA orders requires you to also implement the `custom_stake_amount()` callback to avoid allocating all funds to the initial order.
+
+!!! Warning
+    Stoploss is still calculated from the initial opening price, not averaged price.
+
+!!! Warning "/stopbuy"
+    While `/stopbuy` command stops the bot from entering new trades, the position adjustment feature will continue buying new orders on existing trades.
+
+!!! Warning "Backtesting"
+    During backtesting this callback is called for each candle in `timeframe` or `timeframe_detail`, so performance will be affected.
+
+``` python
+from freqtrade.persistence import Trade
+
+
+class DigDeeperStrategy(IStrategy):
+    
+    position_adjustment_enable = True
+    
+    # Attempts to handle large drops with DCA. High stoploss is required.
+    stoploss = -0.30
+    
+    # ... populate_* methods
+    
+    # Example specific variables
+    max_entry_position_adjustment = 3
+    # This number is explained a bit further down
+    max_dca_multiplier = 5.5
+    
+    # This is called when placing the initial order (opening trade)
+    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
+                            proposed_stake: float, min_stake: float, max_stake: float,
+                            entry_tag: Optional[str], side: str, **kwargs) -> float:
+        
+        # We need to leave most of the funds for possible further DCA orders
+        # This also applies to fixed stakes
+        return proposed_stake / self.max_dca_multiplier
+        
+    def adjust_trade_position(self, trade: Trade, current_time: datetime,
+                              current_rate: float, current_profit: float, min_stake: float,
+                              max_stake: float, **kwargs):
+        """
+        Custom trade adjustment logic, returning the stake amount that a trade should be increased.
+        This means extra buy orders with additional fees.
+ 
+        :param trade: trade object.
+        :param current_time: datetime object, containing the current datetime
+        :param current_rate: Current buy rate.
+        :param current_profit: Current profit (as ratio), calculated based on current_rate.
+        :param min_stake: Minimal stake size allowed by exchange.
+        :param max_stake: Balance available for trading.
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return float: Stake amount to adjust your trade
+        """
+        
+        if current_profit > -0.05:
+            return None
+
+        # Obtain pair dataframe (just to show how to access it)
+        dataframe, _ = self.dp.get_analyzed_dataframe(trade.pair, self.timeframe)
+        # Only buy when not actively falling price.
+        last_candle = dataframe.iloc[-1].squeeze()
+        previous_candle = dataframe.iloc[-2].squeeze()
+        if last_candle['close'] < previous_candle['close']:
+            return None
+
+        filled_entries = trade.select_filled_orders(trade.entry_side)
+        count_of_entries = trade.nr_of_successful_entries
+        # Allow up to 3 additional increasingly larger buys (4 in total)
+        # Initial buy is 1x
+        # If that falls to -5% profit, we buy 1.25x more, average profit should increase to roughly -2.2%
+        # If that falls down to -5% again, we buy 1.5x more
+        # If that falls once again down to -5%, we buy 1.75x more
+        # Total stake for this trade would be 1 + 1.25 + 1.5 + 1.75 = 5.5x of the initial allowed stake.
+        # That is why max_dca_multiplier is 5.5
+        # Hope you have a deep wallet!
+        try:
+            # This returns first order stake size
+            stake_amount = filled_entries[0].cost
+            # This then calculates current safety order size
+            stake_amount = stake_amount * (1 + (count_of_entries * 0.25))
+            return stake_amount
+        except Exception as exception:
+            return None
+
+        return None
+
+```
+
+## Leverage Callback
+
+When trading in markets that allow leverage, this method must return the desired Leverage (Defaults to 1 -> No leverage).
+
+Assuming a capital of 500USDT, a trade with leverage=3 would result in a position with 500 x 3 = 1500 USDT.
+
+Values that are above `max_leverage` will be adjusted to `max_leverage`.
+For markets / exchanges that don't support leverage, this method is ignored.
+
+``` python
+class AwesomeStrategy(IStrategy):
+    def leverage(self, pair: str, current_time: 'datetime', current_rate: float,
+                 proposed_leverage: float, max_leverage: float, side: str,
+                 **kwargs) -> float:
+        """
+        Customize leverage for each new trade.
+
+        :param pair: Pair that's currently analyzed
+        :param current_time: datetime object, containing the current datetime
+        :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
+        :param proposed_leverage: A leverage proposed by the bot.
+        :param max_leverage: Max leverage allowed on this pair
+        :param side: 'long' or 'short' - indicating the direction of the proposed trade
+        :return: A leverage amount, which is between 1.0 and max_leverage.
+        """
+        return 1.0
+```
diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md
index 110365208..6947380dd 100644
--- a/docs/strategy-customization.md
+++ b/docs/strategy-customization.md
@@ -4,40 +4,30 @@ This page explains how to customize your strategies, add new indicators and set
 
 Please familiarize yourself with [Freqtrade basics](bot-basics.md) first, which provides overall info on how the bot operates.
 
-## Install a custom strategy file
-
-This is very simple. Copy paste your strategy file into the directory `user_data/strategies`.
-
-Let assume you have a class called `AwesomeStrategy` in the file `AwesomeStrategy.py`:
-
-1. Move your file into `user_data/strategies` (you should have `user_data/strategies/AwesomeStrategy.py`
-2. Start the bot with the param `--strategy AwesomeStrategy` (the parameter is the class name)
-
-```bash
-freqtrade trade --strategy AwesomeStrategy
-```
-
 ## Develop your own strategy
 
 The bot includes a default strategy file.
 Also, several other strategies are available in the [strategy repository](https://github.com/freqtrade/freqtrade-strategies).
 
 You will however most likely have your own idea for a strategy.
-This document intends to help you develop one for yourself.
+This document intends to help you convert your strategy idea into your own strategy.
 
-To get started, use `freqtrade new-strategy --strategy AwesomeStrategy`.
+To get started, use `freqtrade new-strategy --strategy AwesomeStrategy` (you can obviously use your own naming for your strategy).
 This will create a new strategy file from a template, which will be located under `user_data/strategies/AwesomeStrategy.py`.
 
 !!! Note
     This is just a template file, which will most likely not be profitable out of the box.
 
+??? Hint "Different template levels"
+    `freqtrade new-strategy` has an additional parameter, `--template`, which controls the amount of pre-build information you get in the created strategy. Use `--template minimal` to get an empty strategy without any indicator examples, or `--template advanced` to get a template with most callbacks defined.
+
 ### Anatomy of a strategy
 
 A strategy file contains all the information needed to build a good strategy:
 
 - Indicators
-- Buy strategy rules
-- Sell strategy rules
+- Entry strategy rules
+- Exit strategy rules
 - Minimal ROI recommended
 - Stoploss strongly recommended
 
@@ -45,7 +35,7 @@ The bot also include a sample strategy called `SampleStrategy` you can update: `
 You can test it with the parameter: `--strategy SampleStrategy`
 
 Additionally, there is an attribute called `INTERFACE_VERSION`, which defines the version of the strategy interface the bot should use.
-The current version is 2 - which is also the default when it's not set explicitly in the strategy.
+The current version is 3 - which is also the default when it's not set explicitly in the strategy.
 
 Future versions will require this to be set.
 
@@ -67,11 +57,51 @@ file as reference.**
     needs to take care to avoid having the strategy utilize data from the future.
     Some common patterns for this are listed in the [Common Mistakes](#common-mistakes-when-developing-strategies) section of this document.
 
+### Dataframe
+
+Freqtrade uses [pandas](https://pandas.pydata.org/) to store/provide the candlestick (OHLCV) data.
+Pandas is a great library developed for processing large amounts of data.
+
+Each row in a dataframe corresponds to one candle on a chart, with the latest candle always being the last in the dataframe (sorted by date).
+
+``` output
+> dataframe.head()
+                       date      open      high       low     close     volume
+0 2021-11-09 23:25:00+00:00  67279.67  67321.84  67255.01  67300.97   44.62253
+1 2021-11-09 23:30:00+00:00  67300.97  67301.34  67183.03  67187.01   61.38076
+2 2021-11-09 23:35:00+00:00  67187.02  67187.02  67031.93  67123.81  113.42728
+3 2021-11-09 23:40:00+00:00  67123.80  67222.40  67080.33  67160.48   78.96008
+4 2021-11-09 23:45:00+00:00  67160.48  67160.48  66901.26  66943.37  111.39292
+```
+
+Pandas provides fast ways to calculate metrics. To benefit from this speed, it's advised to not use loops, but use vectorized methods instead.
+
+Vectorized operations perform calculations across the whole range of data and are therefore, compared to looping through each row, a lot faster when calculating indicators.
+
+As a dataframe is a table, simple python comparisons like the following will not work
+
+``` python
+    if dataframe['rsi'] > 30:
+        dataframe['enter_long'] = 1
+```
+
+The above section will fail with `The truth value of a Series is ambiguous. [...]`.
+
+This must instead be written in a pandas-compatible way, so the operation is performed across the whole dataframe.
+
+``` python
+    dataframe.loc[
+        (dataframe['rsi'] > 30)
+    , 'enter_long'] = 1
+```
+
+With this section, you have a new column in your dataframe, which has `1` assigned whenever RSI is above 30.
+
 ### Customize Indicators
 
-Buy and sell strategies need indicators. You can add more indicators by extending the list contained in the method `populate_indicators()` from your strategy file.
+Buy and sell signals need indicators. You can add more indicators by extending the list contained in the method `populate_indicators()` from your strategy file.
 
-You should only add the indicators used in either `populate_buy_trend()`, `populate_sell_trend()`, or to populate another indicator, otherwise performance may suffer.
+You should only add the indicators used in either `populate_entry_trend()`, `populate_exit_trend()`, or to populate another indicator, otherwise performance may suffer.
 
 It's important to always return the dataframe without removing/modifying the columns `"open", "high", "low", "close", "volume"`, otherwise these fields would contain something unexpected.
 
@@ -122,9 +152,19 @@ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame
     Look into the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py).
     Then uncomment indicators you need.
 
+#### Indicator libraries
+
+Out of the box, freqtrade installs the following technical libraries:
+
+* [ta-lib](http://mrjbq7.github.io/ta-lib/)
+* [pandas-ta](https://twopirllc.github.io/pandas-ta/)
+* [technical](https://github.com/freqtrade/technical/)
+
+Additional technical libraries can be installed as necessary, or custom indicators may be written / invented by the strategy author.
+
 ### Strategy startup period
 
-Most indicators have an instable startup period, in which they are either not available, or the calculation is incorrect. This can lead to inconsistencies, since Freqtrade does not know how long this instable period should be.
+Most indicators have an instable startup period, in which they are either not available (NaN), or the calculation is incorrect. This can lead to inconsistencies, since Freqtrade does not know how long this instable period should be.
 To account for this, the strategy can be assigned the `startup_candle_count` attribute.
 This should be set to the maximum number of candles that the strategy requires to calculate stable indicators.
 
@@ -136,8 +176,14 @@ In this example strategy, this should be set to 100 (`startup_candle_count = 100
 
 By letting the bot know how much history is needed, backtest trades can start at the specified timerange during backtesting and hyperopt.
 
+!!! Warning "Using x calls to get OHLCV"
+    If you receive a warning like `WARNING - Using 3 calls to get OHLCV. This can result in slower operations for the bot. Please check if you really need 1500 candles for your strategy` - you should consider if you really need this much historic data for your signals.
+    Having this will cause Freqtrade to make multiple calls for the same pair, which will obviously be slower than one network request.
+    As a consequence, Freqtrade will take longer to refresh candles - and should therefore be avoided if possible.
+    This is capped to 5 total calls to avoid overloading the exchange, or make freqtrade too slow.
+
 !!! Warning
-    `startup_candle_count` should be below `ohlcv_candle_limit` (which is 500 for most exchanges) - since only this amount of candles will be available during Dry-Run/Live Trade operations.
+    `startup_candle_count` should be below `ohlcv_candle_limit * 5` (which is 500 * 5 for most exchanges) - since only this amount of candles will be available during Dry-Run/Live Trade operations.
 
 #### Example
 
@@ -153,18 +199,18 @@ If this data is available, indicators will be calculated with this extended time
 !!! Note
     If data for the startup period is not available, then the timerange will be adjusted to account for this startup period - so Backtesting would start at 2019-01-01 08:30:00.
 
-### Buy signal rules
+### Entry signal rules
 
-Edit the method `populate_buy_trend()` in your strategy file to update your buy strategy.
+Edit the method `populate_entry_trend()` in your strategy file to update your entry strategy.
 
 It's important to always return the dataframe without removing/modifying the columns `"open", "high", "low", "close", "volume"`, otherwise these fields would contain something unexpected.
 
-This method will also define a new column, `"buy"`, which needs to contain 1 for buys, and 0 for "no action".
+This method will also define a new column, `"enter_long"` (`"enter_short"` for shorts), which needs to contain 1 for entries, and 0 for "no action". `enter_long` is a mandatory column that must be set even if the strategy is shorting only.
 
 Sample from `user_data/strategies/sample_strategy.py`:
 
 ```python
-def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
     """
     Based on TA indicators, populates the buy signal for the given dataframe
     :param dataframe: DataFrame populated with indicators
@@ -178,29 +224,58 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
             (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard
             (dataframe['volume'] > 0)  # Make sure Volume is not 0
         ),
-        'buy'] = 1
+        ['enter_long', 'enter_tag']] = (1, 'rsi_cross')
 
     return dataframe
 ```
 
+??? Note "Enter short trades"
+    Short-entries can be created by setting `enter_short` (corresponds to `enter_long` for long trades).
+    The `enter_tag` column remains identical.
+    Short-trades need to be supported by your exchange and market configuration!
+    Please make sure to set [`can_short`]() appropriately on your strategy if you intend to short.
+
+    ```python
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+                (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard
+                (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            ['enter_long', 'enter_tag']] = (1, 'rsi_cross')
+
+        dataframe.loc[
+            (
+                (qtpylib.crossed_below(dataframe['rsi'], 70)) &  # Signal: RSI crosses below 70
+                (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard
+                (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            ['enter_short', 'enter_tag']] = (1, 'rsi_cross')
+
+        return dataframe
+    ```
+
 !!! Note
     Buying requires sellers to buy from - therefore volume needs to be > 0 (`dataframe['volume'] > 0`) to make sure that the bot does not buy/sell in no-activity periods.
 
-### Sell signal rules
+### Exit signal rules
 
-Edit the method `populate_sell_trend()` into your strategy file to update your sell strategy.
-Please note that the sell-signal is only used if `use_sell_signal` is set to true in the configuration.
+Edit the method `populate_exit_trend()` into your strategy file to update your exit strategy.
+Please note that the exit-signal is only used if `use_exit_signal` is set to true in the configuration.
 
 It's important to always return the dataframe without removing/modifying the columns `"open", "high", "low", "close", "volume"`, otherwise these fields would contain something unexpected.
 
-This method will also define a new column, `"sell"`, which needs to contain 1 for sells, and 0 for "no action".
+This method will also define a new column, `"exit_long"` (`"exit_short"` for shorts), which needs to contain 1 for exits, and 0 for "no action".
 
 Sample from `user_data/strategies/sample_strategy.py`:
 
 ```python
-def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
     """
-    Based on TA indicators, populates the sell signal for the given dataframe
+    Based on TA indicators, populates the exit signal for the given dataframe
     :param dataframe: DataFrame populated with indicators
     :param metadata: Additional information, like the currently traded pair
     :return: DataFrame with buy column
@@ -212,13 +287,39 @@ def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame
             (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard
             (dataframe['volume'] > 0)  # Make sure Volume is not 0
         ),
-        'sell'] = 1
+        ['exit_long', 'exit_tag']] = (1, 'rsi_too_high')
     return dataframe
 ```
 
+??? Note "Exit short trades"
+    Short-exits can be created by setting `exit_short` (corresponds to `exit_long`).
+    The `exit_tag` column remains identical.
+    Short-trades need to be supported by your exchange and market configuration!
+
+    ```python
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                (qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+                (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard
+                (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            ['exit_long', 'exit_tag']] = (1, 'rsi_too_high')
+        dataframe.loc[
+            (
+                (qtpylib.crossed_below(dataframe['rsi'], 30)) &  # Signal: RSI crosses below 30
+                (dataframe['tema'] < dataframe['bb_middleband']) &  # Guard
+                (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            ['exit_short', 'exit_tag']] = (1, 'rsi_too_low')
+        return dataframe
+    ```
+
 ### Minimal ROI
 
-This dict defines the minimal Return On Investment (ROI) a trade should reach before selling, independent from the sell signal.
+This dict defines the minimal Return On Investment (ROI) a trade should reach before exiting, independent from the exit signal.
 
 It is of the following format, with the dict key (left side of the colon) being the minutes passed since the trade opened, and the value (right side of the colon) being the percentage.
 
@@ -233,10 +334,10 @@ minimal_roi = {
 
 The above configuration would therefore mean:
 
-- Sell whenever 4% profit was reached
-- Sell when 2% profit was reached (in effect after 20 minutes)
-- Sell when 1% profit was reached (in effect after 30 minutes)
-- Sell when trade is non-loosing (in effect after 40 minutes)
+- Exit whenever 4% profit was reached
+- Exit when 2% profit was reached (in effect after 20 minutes)
+- Exit when 1% profit was reached (in effect after 30 minutes)
+- Exit when trade is non-loosing (in effect after 40 minutes)
 
 The calculation does include fees.
 
@@ -248,7 +349,7 @@ minimal_roi = {
 }
 ```
 
-While technically not completely disabled, this would sell once the trade reaches 10000% Profit.
+While technically not completely disabled, this would exit once the trade reaches 10000% Profit.
 
 To use times based on candle duration (timeframe), the following snippet can be handy.
 This will allow you to change the timeframe for the strategy, and ROI times will still be set as candles (e.g. after 3 candles ...)
@@ -271,38 +372,51 @@ class AwesomeStrategy(IStrategy):
 
 Setting a stoploss is highly recommended to protect your capital from strong moves against you.
 
-Sample:
+Sample of setting a 10% stoploss:
 
 ``` python
 stoploss = -0.10
 ```
 
-This would signify a stoploss of -10%.
-
 For the full documentation on stoploss features, look at the dedicated [stoploss page](stoploss.md).
 
-If your exchange supports it, it's recommended to also set `"stoploss_on_exchange"` in the order_types dictionary, so your stoploss is on the exchange and cannot be missed due to network problems, high load or other reasons.
-
-For more information on order_types please look [here](configuration.md#understand-order_types).
-
-### Timeframe (formerly ticker interval)
+### Timeframe
 
 This is the set of candles the bot should download and use for the analysis.
 Common values are `"1m"`, `"5m"`, `"15m"`, `"1h"`, however all values supported by your exchange should work.
 
-Please note that the same buy/sell signals may work well with one timeframe, but not with the others.
+Please note that the same entry/exit signals may work well with one timeframe, but not with the others.
 
 This setting is accessible within the strategy methods as the `self.timeframe` attribute.
 
+### Can short
+
+To use short signals in futures markets, you will have to let us know to do so by setting `can_short=True`.
+Strategies which enable this will fail to load on spot markets.
+Disabling of this will have short signals ignored (also in futures markets).
+
 ### Metadata dict
 
-The metadata-dict (available for `populate_buy_trend`, `populate_sell_trend`, `populate_indicators`) contains additional information.
+The metadata-dict (available for `populate_entry_trend`, `populate_exit_trend`, `populate_indicators`) contains additional information.
 Currently this is `pair`, which can be accessed using `metadata['pair']` - and will return a pair in the format `XRP/BTC`.
 
 The Metadata-dict should not be modified and does not persist information across multiple calls.
-Instead, have a look at the section [Storing information](strategy-advanced.md#Storing-information)
+Instead, have a look at the [Storing information](strategy-advanced.md#Storing-information) section.
 
-## Additional data (informative_pairs)
+## Strategy file loading
+
+By default, freqtrade will attempt to load strategies from all `.py` files within `user_data/strategies`.
+
+Assuming your strategy is called `AwesomeStrategy`, stored in the file `user_data/strategies/AwesomeStrategy.py`, then you can start freqtrade with `freqtrade trade --strategy AwesomeStrategy`.
+Note that we're using the class-name, not the file name.
+
+You can use `freqtrade list-strategies` to see a list of all strategies Freqtrade is able to load (all strategies in the correct folder).
+It will also include a "status" field, highlighting potential problems.
+
+??? Hint "Customize strategy directory"
+    You can use a different directory by using `--strategy-path user_data/otherPath`. This parameter is available to all commands that require a strategy.
+
+## Informative Pairs
 
 ### Get data for non-tradeable pairs
 
@@ -329,8 +443,150 @@ A full sample can be found [in the DataProvider section](#complete-data-provider
     It is however better to use resampling to longer timeframes whenever possible
     to avoid hammering the exchange with too many requests and risk being blocked.
 
+??? Note "Alternative candle types"
+    Informative_pairs can also provide a 3rd tuple element defining the candle type explicitly.
+    Availability of alternative candle-types will depend on the trading-mode and the exchange. Details about this can be found in the exchange documentation.
+
+    ``` python
+    def informative_pairs(self):
+        return [
+            ("ETH/USDT", "5m", ""),   # Uses default candletype, depends on trading_mode 
+            ("ETH/USDT", "5m", "spot"),   # Forces usage of spot candles
+            ("BTC/TUSD", "15m", "futures"),  # Uses futures candles
+            ("BTC/TUSD", "15m", "mark"),  # Uses mark candles
+        ]
+    ```
 ***
 
+### Informative pairs decorator (`@informative()`)
+
+In most common case it is possible to easily define informative pairs by using a decorator. All decorated `populate_indicators_*` methods run in isolation,
+not having access to data from other informative pairs, in the end all informative dataframes are merged and passed to main `populate_indicators()` method.
+When hyperopting, use of hyperoptable parameter `.value` attribute is not supported. Please use `.range` attribute. See [optimizing an indicator parameter](hyperopt.md#optimizing-an-indicator-parameter)
+for more information.
+
+??? info "Full documentation"
+    ``` python
+    def informative(timeframe: str, asset: str = '',
+                    fmt: Optional[Union[str, Callable[[KwArg(str)], str]]] = None,
+                    *,
+                    candle_type: Optional[CandleType] = None,
+                    ffill: bool = True) -> Callable[[PopulateIndicators], PopulateIndicators]:
+        """
+        A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
+        define informative indicators.
+
+        Example usage:
+
+            @informative('1h')
+            def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+                dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+                return dataframe
+
+        :param timeframe: Informative timeframe. Must always be equal or higher than strategy timeframe.
+        :param asset: Informative asset, for example BTC, BTC/USDT, ETH/BTC. Do not specify to use
+        current pair.
+        :param fmt: Column format (str) or column formatter (callable(name, asset, timeframe)). When not
+        specified, defaults to:
+        * {base}_{quote}_{column}_{timeframe} if asset is specified. 
+        * {column}_{timeframe} if asset is not specified.
+        Format string supports these format variables:
+        * {asset} - full name of the asset, for example 'BTC/USDT'.
+        * {base} - base currency in lower case, for example 'eth'.
+        * {BASE} - same as {base}, except in upper case.
+        * {quote} - quote currency in lower case, for example 'usdt'.
+        * {QUOTE} - same as {quote}, except in upper case.
+        * {column} - name of dataframe column.
+        * {timeframe} - timeframe of informative dataframe.
+        :param ffill: ffill dataframe after merging informative pair.
+        :param candle_type: '', mark, index, premiumIndex, or funding_rate
+        """
+    ```
+
+??? Example "Fast and easy way to define informative pairs"
+
+    Most of the time we do not need power and flexibility offered by `merge_informative_pair()`, therefore we can use a decorator to quickly define informative pairs.
+
+    ``` python
+
+    from datetime import datetime
+    from freqtrade.persistence import Trade
+    from freqtrade.strategy import IStrategy, informative
+
+    class AwesomeStrategy(IStrategy):
+        
+        # This method is not required. 
+        # def informative_pairs(self): ...
+
+        # Define informative upper timeframe for each pair. Decorators can be stacked on same 
+        # method. Available in populate_indicators as 'rsi_30m' and 'rsi_1h'.
+        @informative('30m')
+        @informative('1h')
+        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+
+        # Define BTC/STAKE informative pair. Available in populate_indicators and other methods as
+        # 'btc_rsi_1h'. Current stake currency should be specified as {stake} format variable 
+        # instead of hard-coding actual stake currency. Available in populate_indicators and other 
+        # methods as 'btc_usdt_rsi_1h' (when stake currency is USDT).
+        @informative('1h', 'BTC/{stake}')
+        def populate_indicators_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+
+        # Define BTC/ETH informative pair. You must specify quote currency if it is different from
+        # stake currency. Available in populate_indicators and other methods as 'eth_btc_rsi_1h'.
+        @informative('1h', 'ETH/BTC')
+        def populate_indicators_eth_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+    
+        # Define BTC/STAKE informative pair. A custom formatter may be specified for formatting
+        # column names. A callable `fmt(**kwargs) -> str` may be specified, to implement custom
+        # formatting. Available in populate_indicators and other methods as 'rsi_upper'.
+        @informative('1h', 'BTC/{stake}', '{column}')
+        def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi_upper'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+    
+        def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            # Strategy timeframe indicators for current pair.
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            # Informative pairs are available in this method.
+            dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h']
+            return dataframe
+
+    ```
+
+!!! Note
+    Do not use `@informative` decorator if you need to use data of one informative pair when generating another informative pair. Instead, define informative pairs
+    manually as described [in the DataProvider section](#complete-data-provider-sample).
+
+!!! Note
+    Use string formatting when accessing informative dataframes of other pairs. This will allow easily changing stake currency in config without having to adjust strategy code.
+
+    ``` python
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        stake = self.config['stake_currency']
+        dataframe.loc[
+            (
+                (dataframe[f'btc_{stake}_rsi_1h'] < 35)
+                &
+                (dataframe['volume'] > 0)
+            ),
+            ['enter_long', 'enter_tag']] = (1, 'buy_signal_rsi')
+    
+        return dataframe
+    ```
+
+    Alternatively column renaming may be used to remove stake currency from column names: `@informative('1h', 'BTC/{stake}', fmt='{base}_{column}_{timeframe}')`.
+
+!!! Warning "Duplicate method names"
+    Methods tagged with `@informative()` decorator must always have unique names! Re-using same name (for example when copy-pasting already defined informative method)
+    will overwrite previously defined method and not produce any errors due to limitations of Python programming language. In such cases you will find that indicators
+    created in earlier-defined methods are not available in the dataframe. Carefully review method names and make sure they are unique!
+
 ## Additional data (DataProvider)
 
 The strategy provides access to the `DataProvider`. This allows you to get additional data to use in your strategy.
@@ -374,9 +630,9 @@ The strategy might look something like this:
 
 *Scan through the top 10 pairs by volume using the `VolumePairList` every 5 minutes and use a 14 day RSI to buy and sell.*
 
-Due to the limited available data, it's very difficult to resample our `5m` candles into daily candles for use in a 14 day RSI. Most exchanges limit us to just 500 candles which effectively gives us around 1.74 daily candles. We need 14 days at least!
+Due to the limited available data, it's very difficult to resample `5m` candles into daily candles for use in a 14 day RSI. Most exchanges limit us to just 500 candles which effectively gives us around 1.74 daily candles. We need 14 days at least!
 
-Since we can't resample our data we will have to use an informative pair; and since our whitelist will be dynamic we don't know which pair(s) to use.
+Since we can't resample the data we will have to use an informative pair; and since the whitelist will be dynamic we don't know which pair(s) to use.
 
 This is where calling `self.dp.current_whitelist()` comes in handy.
 
@@ -526,7 +782,7 @@ class SampleStrategy(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
         dataframe.loc[
             (
@@ -534,7 +790,7 @@ class SampleStrategy(IStrategy):
                 (dataframe['rsi_1d'] < 30) &                     # Ensure daily RSI is < 30
                 (dataframe['volume'] > 0)                        # Ensure this candle had volume (important for backtesting)
             ),
-            'buy'] = 1
+            ['enter_long', 'enter_tag']] = (1, 'rsi_cross')
 
 ```
 
@@ -611,7 +867,7 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati
 
     Say the open price was $100, and `current_price` is $121 (`current_profit` will be `0.21`).  
 
-    If we want a stop price at 7% above the open price we can call `stoploss_from_open(0.07, current_profit)` which will return `0.1157024793`.  11.57% below $121 is $107, which is the same as 7% above $100.
+    If we want a stop price at 7% above the open price we can call `stoploss_from_open(0.07, current_profit, False)` which will return `0.1157024793`.  11.57% below $121 is $107, which is the same as 7% above $100.
 
 
     ``` python
@@ -631,7 +887,7 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati
 
             # once the profit has risen above 10%, keep the stoploss at 7% above the open price
             if current_profit > 0.10:
-                return stoploss_from_open(0.07, current_profit)
+                return stoploss_from_open(0.07, current_profit, is_short=trade.is_short)
 
             return 1
 
@@ -642,7 +898,7 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati
 !!! Note
     Providing invalid input to `stoploss_from_open()` may produce "CustomStoploss function did not return valid stoploss" warnings.
     This may happen if `current_profit` parameter is below specified `open_relative_stop`. Such situations may arise when closing trade
-    is blocked by `confirm_trade_exit()` method. Warnings can be solved by never blocking stop loss sells by checking `sell_reason` in
+    is blocked by `confirm_trade_exit()` method. Warnings can be solved by never blocking stop loss sells by checking `exit_reason` in
     `confirm_trade_exit()`, or by using `return stoploss_from_open(...) or 1` idiom, which will request to not change stop loss when
     `current_profit < open_relative_stop`.
 
@@ -652,13 +908,13 @@ In some situations it may be confusing to deal with stops relative to current ra
 
 ??? Example "Returning a stoploss using absolute price from the custom stoploss function"
 
-    If we want to trail a stop price at 2xATR below current proce we can call `stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate)`.
+    If we want to trail a stop price at 2xATR below current price we can call `stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate, is_short=trade.is_short)`.
 
     ``` python
 
     from datetime import datetime
     from freqtrade.persistence import Trade
-    from freqtrade.strategy import IStrategy, stoploss_from_open
+    from freqtrade.strategy import IStrategy, stoploss_from_absolute
 
     class AwesomeStrategy(IStrategy):
 
@@ -672,135 +928,10 @@ In some situations it may be confusing to deal with stops relative to current ra
                             current_rate: float, current_profit: float, **kwargs) -> float:
             dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
             candle = dataframe.iloc[-1].squeeze()
-            return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate)
+            return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate, is_short=trade.is_short)
 
     ```
 
-### *@informative()*
-
-``` python
-def informative(timeframe: str, asset: str = '',
-                fmt: Optional[Union[str, Callable[[KwArg(str)], str]]] = None,
-                ffill: bool = True) -> Callable[[PopulateIndicators], PopulateIndicators]:
-    """
-    A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
-    define informative indicators.
-
-    Example usage:
-
-        @informative('1h')
-        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
-            return dataframe
-
-    :param timeframe: Informative timeframe. Must always be equal or higher than strategy timeframe.
-    :param asset: Informative asset, for example BTC, BTC/USDT, ETH/BTC. Do not specify to use
-    current pair.
-    :param fmt: Column format (str) or column formatter (callable(name, asset, timeframe)). When not
-    specified, defaults to:
-    * {base}_{quote}_{column}_{timeframe} if asset is specified. 
-    * {column}_{timeframe} if asset is not specified.
-    Format string supports these format variables:
-    * {asset} - full name of the asset, for example 'BTC/USDT'.
-    * {base} - base currency in lower case, for example 'eth'.
-    * {BASE} - same as {base}, except in upper case.
-    * {quote} - quote currency in lower case, for example 'usdt'.
-    * {QUOTE} - same as {quote}, except in upper case.
-    * {column} - name of dataframe column.
-    * {timeframe} - timeframe of informative dataframe.
-    :param ffill: ffill dataframe after merging informative pair.
-    """
-```
-
-In most common case it is possible to easily define informative pairs by using a decorator. All decorated `populate_indicators_*` methods run in isolation,
-not having access to data from other informative pairs, in the end all informative dataframes are merged and passed to main `populate_indicators()` method.
-When hyperopting, use of hyperoptable parameter `.value` attribute is not supported. Please use `.range` attribute. See [optimizing an indicator parameter](hyperopt.md#optimizing-an-indicator-parameter)
-for more information.
-
-??? Example "Fast and easy way to define informative pairs"
-
-    Most of the time we do not need power and flexibility offered by `merge_informative_pair()`, therefore we can use a decorator to quickly define informative pairs.
-
-    ``` python
-
-    from datetime import datetime
-    from freqtrade.persistence import Trade
-    from freqtrade.strategy import IStrategy, informative
-
-    class AwesomeStrategy(IStrategy):
-        
-        # This method is not required. 
-        # def informative_pairs(self): ...
-
-        # Define informative upper timeframe for each pair. Decorators can be stacked on same 
-        # method. Available in populate_indicators as 'rsi_30m' and 'rsi_1h'.
-        @informative('30m')
-        @informative('1h')
-        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
-            return dataframe
-
-        # Define BTC/STAKE informative pair. Available in populate_indicators and other methods as
-        # 'btc_rsi_1h'. Current stake currency should be specified as {stake} format variable 
-        # instead of hardcoding actual stake currency. Available in populate_indicators and other 
-        # methods as 'btc_usdt_rsi_1h' (when stake currency is USDT).
-        @informative('1h', 'BTC/{stake}')
-        def populate_indicators_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
-            return dataframe
-
-        # Define BTC/ETH informative pair. You must specify quote currency if it is different from
-        # stake currency. Available in populate_indicators and other methods as 'eth_btc_rsi_1h'.
-        @informative('1h', 'ETH/BTC')
-        def populate_indicators_eth_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
-            return dataframe
-    
-        # Define BTC/STAKE informative pair. A custom formatter may be specified for formatting
-        # column names. A callable `fmt(**kwargs) -> str` may be specified, to implement custom
-        # formatting. Available in populate_indicators and other methods as 'rsi_upper'.
-        @informative('1h', 'BTC/{stake}', '{column}')
-        def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-            dataframe['rsi_upper'] = ta.RSI(dataframe, timeperiod=14)
-            return dataframe
-    
-        def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-            # Strategy timeframe indicators for current pair.
-            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
-            # Informative pairs are available in this method.
-            dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h']
-            return dataframe
-
-    ```
-
-!!! Note
-    Do not use `@informative` decorator if you need to use data of one informative pair when generating another informative pair. Instead, define informative pairs
-    manually as described [in the DataProvider section](#complete-data-provider-sample).
-
-!!! Note
-    Use string formatting when accessing informative dataframes of other pairs. This will allow easily changing stake currency in config without having to adjust strategy code.
-
-    ``` python
-    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        stake = self.config['stake_currency']
-        dataframe.loc[
-            (
-                (dataframe[f'btc_{stake}_rsi_1h'] < 35)
-                &
-                (dataframe['volume'] > 0)
-            ),
-            ['buy', 'buy_tag']] = (1, 'buy_signal_rsi')
-    
-        return dataframe
-    ```
-
-    Alternatively column renaming may be used to remove stake currency from column names: `@informative('1h', 'BTC/{stake}', fmt='{base}_{column}_{timeframe}')`.
-
-!!! Warning "Duplicate method names"
-    Methods tagged with `@informative()` decorator must always have unique names! Re-using same name (for example when copy-pasting already defined informative method)
-    will overwrite previously defined method and not produce any errors due to limitations of Python programming language. In such cases you will find that indicators
-    created in earlier-defined methods are not available in the dataframe. Carefully review method names and make sure they are unique!
-
 ## Additional data (Wallets)
 
 The strategy provides access to the `Wallets` object. This contains the current balances on the exchange.
@@ -865,7 +996,7 @@ if self.config['runmode'].value in ('live', 'dry_run'):
 Sample return value: ETH/BTC had 5 trades, with a total profit of 1.5% (ratio of 0.015).
 
 ``` json
-{'pair': "ETH/BTC", 'profit': 0.015, 'count': 5}
+{"pair": "ETH/BTC", "profit": 0.015, "count": 5}
 ```
 
 !!! Warning
@@ -884,7 +1015,8 @@ Sometimes it may be desired to lock a pair after certain events happen (e.g. mul
 Freqtrade has an easy method to do this from within the strategy, by calling `self.lock_pair(pair, until, [reason])`.
 `until` must be a datetime object in the future, after which trading will be re-enabled for that pair, while `reason` is an optional string detailing why the pair was locked.
 
-Locks can also be lifted manually, by calling `self.unlock_pair(pair)`.
+Locks can also be lifted manually, by calling `self.unlock_pair(pair)` or `self.unlock_reason(<reason>)` - providing reason the pair was locked with.
+`self.unlock_reason(<reason>)` will unlock all pairs currently locked with the provided reason.
 
 To verify if a pair is currently locked, use `self.is_pair_locked(pair)`.
 
@@ -918,16 +1050,16 @@ if self.config['runmode'].value in ('live', 'dry_run'):
 
 ## Print created dataframe
 
-To inspect the created dataframe, you can issue a print-statement in either `populate_buy_trend()` or `populate_sell_trend()`.
+To inspect the created dataframe, you can issue a print-statement in either `populate_entry_trend()` or `populate_exit_trend()`.
 You may also want to print the pair so it's clear what data is currently shown.
 
 ``` python
-def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
     dataframe.loc[
         (
             #>> whatever condition<<<
         ),
-        'buy'] = 1
+        ['enter_long', 'enter_tag']] = (1, 'somestring')
 
     # Print the Analyzed pair
     print(f"result for {metadata['pair']}")
@@ -954,9 +1086,18 @@ The following lists some common patterns which should be avoided to prevent frus
 - don't use `dataframe['volume'].mean()`. This uses the full DataFrame for backtesting, including data from the future. Use `dataframe['volume'].rolling(<window>).mean()` instead
 - don't use `.resample('1h')`. This uses the left border of the interval, so moves data from an hour to the start of the hour. Use `.resample('1h', label='right')` instead.
 
+### Colliding signals
+
+When conflicting signals collide (e.g. both `'enter_long'` and `'exit_long'` are 1), freqtrade will do nothing and ignore the entry signal. This will avoid trades that enter, and exit immediately. Obviously, this can potentially lead to missed entries.
+
+The following rules apply, and entry signals will be ignored if more than one of the 3 signals is set:
+
+- `enter_long` -> `exit_long`, `enter_short`
+- `enter_short` -> `exit_short`, `enter_long`
+
 ## Further strategy ideas
 
-To get additional Ideas for strategies, head over to our [strategy repository](https://github.com/freqtrade/freqtrade-strategies). Feel free to use them as they are - but results will depend on the current market situation, pairs used etc. - therefore please backtest the strategy for your exchange/desired pairs first, evaluate carefully, use at your own risk.
+To get additional Ideas for strategies, head over to the [strategy repository](https://github.com/freqtrade/freqtrade-strategies). Feel free to use them as they are - but results will depend on the current market situation, pairs used etc. - therefore please backtest the strategy for your exchange/desired pairs first, evaluate carefully, use at your own risk.
 Feel free to use any of them as inspiration for your own strategies.
 We're happy to accept Pull Requests containing new Strategies to that repo.
 
diff --git a/docs/strategy_analysis_example.md b/docs/strategy_analysis_example.md
index dd7e07824..2fa84a6df 100644
--- a/docs/strategy_analysis_example.md
+++ b/docs/strategy_analysis_example.md
@@ -50,7 +50,9 @@ candles.head()
 ```python
 # Load strategy using values set above
 from freqtrade.resolvers import StrategyResolver
+from freqtrade.data.dataprovider import DataProvider
 strategy = StrategyResolver.load_strategy(config)
+strategy.dp = DataProvider(config, None, None)
 
 # Generate buy/sell signals using strategy
 df = strategy.analyze_ticker(candles, {'pair': pair})
@@ -71,7 +73,7 @@ df.tail()
 
 ```python
 # Report results
-print(f"Generated {df['buy'].sum()} buy signals")
+print(f"Generated {df['enter_long'].sum()} entry signals")
 data = df.set_index('date', drop=False)
 data.tail()
 ```
@@ -127,7 +129,7 @@ print(stats['strategy_comparison'])
 trades = load_backtest_data(backtest_dir)
 
 # Show value-counts per pair
-trades.groupby("pair")["sell_reason"].value_counts()
+trades.groupby("pair")["exit_reason"].value_counts()
 ```
 
 ## Plotting daily profit / equity line
@@ -180,7 +182,7 @@ from freqtrade.data.btanalysis import load_trades_from_db
 trades = load_trades_from_db("sqlite:///tradesv3.sqlite")
 
 # Display results
-trades.groupby("pair")["sell_reason"].value_counts()
+trades.groupby("pair")["exit_reason"].value_counts()
 ```
 
 ## Analyze the loaded trades for trade parallelism
@@ -228,7 +230,7 @@ graph = generate_candlestick_graph(pair=pair,
 # Show graph inline
 # graph.show()
 
-# Render graph in a separate window
+# Render graph in a seperate window
 graph.show(renderer="browser")
 
 ```
@@ -242,7 +244,7 @@ import plotly.figure_factory as ff
 hist_data = [trades.profit_ratio]
 group_labels = ['profit_ratio']  # name of the dataset
 
-fig = ff.create_distplot(hist_data, group_labels,bin_size=0.01)
+fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)
 fig.show()
 
 ```
diff --git a/docs/strategy_migration.md b/docs/strategy_migration.md
new file mode 100644
index 000000000..458e80d0e
--- /dev/null
+++ b/docs/strategy_migration.md
@@ -0,0 +1,471 @@
+# Strategy Migration between V2 and V3
+
+To support new markets and trade-types (namely short trades / trades with leverage), some things had to change in the interface.
+If you intend on using markets other than spot markets, please migrate your strategy to the new format.
+
+We have put a great effort into keeping compatibility with existing strategies, so if you just want to continue using freqtrade in __spot markets__, there should be no changes necessary for now.
+
+You can use the quick summary as checklist. Please refer to the detailed sections below for full migration details.
+
+## Quick summary / migration checklist
+
+Note : `forcesell`, `forcebuy`, `emergencysell` are changed to `force_exit`, `force_enter`, `emergency_exit` respectively.
+
+* Strategy methods:
+  * [`populate_buy_trend()` -> `populate_entry_trend()`](#populate_buy_trend)
+  * [`populate_sell_trend()` -> `populate_exit_trend()`](#populate_sell_trend)
+  * [`custom_sell()` -> `custom_exit()`](#custom_sell)
+  * [`check_buy_timeout()` -> `check_entry_timeout()`](#custom_entry_timeout)
+  * [`check_sell_timeout()` -> `check_exit_timeout()`](#custom_entry_timeout)
+  * New `side` argument to callbacks without trade object
+    * [`custom_stake_amount`](#custom-stake-amount)
+    * [`confirm_trade_entry`](#confirm_trade_entry)
+    * [`custom_entry_price`](#custom_entry_price)
+  * [Changed argument name in `confirm_trade_exit`](#confirm_trade_exit)
+* Dataframe columns:
+  * [`buy` -> `enter_long`](#populate_buy_trend)
+  * [`sell` -> `exit_long`](#populate_sell_trend)
+  * [`buy_tag` -> `enter_tag` (used for both long and short trades)](#populate_buy_trend)
+  * [New column `enter_short` and corresponding new column `exit_short`](#populate_sell_trend)
+* trade-object now has the following new properties:
+  * `is_short`
+  * `entry_side`
+  * `exit_side`
+  * `trade_direction`
+  * renamed: `sell_reason` -> `exit_reason`
+* [Renamed `trade.nr_of_successful_buys` to `trade.nr_of_successful_entries` (mostly relevant for `adjust_trade_position()`)](#adjust-trade-position-changes)
+* Introduced new [`leverage` callback](strategy-callbacks.md#leverage-callback).
+* Informative pairs can now pass a 3rd element in the Tuple, defining the candle type.
+* `@informative` decorator now takes an optional `candle_type` argument.
+* [helper methods](#helper-methods) `stoploss_from_open` and `stoploss_from_absolute` now take `is_short` as additional argument.
+* `INTERFACE_VERSION` should be set to 3.
+* [Strategy/Configuration settings](#strategyconfiguration-settings).
+  * `order_time_in_force` buy -> entry, sell -> exit.
+  * `order_types` buy -> entry, sell -> exit.
+  * `unfilledtimeout` buy -> entry, sell -> exit.
+* Terminology changes
+  * Sell reasons changed to reflect the new naming of "exit" instead of sells. Be careful in your strategy if you're using `exit_reason` checks and eventually update your strategy.
+    * `sell_signal` -> `exit_signal`
+    * `custom_sell` -> `custom_exit`
+    * `force_sell` -> `force_exit`
+    * `emergency_sell` -> `emergency_exit`
+  * Webhook terminology changed from "sell" to "exit", and from "buy" to entry
+    * `webhookbuy` -> `webhookentry`
+    * `webhookbuyfill` -> `webhookentryfill`
+    * `webhookbuycancel` -> `webhookentrycancel`
+    * `webhooksell` -> `webhookexit`
+    * `webhooksellfill` -> `webhookexitfill`
+    * `webhooksellcancel` -> `webhookexitcancel`
+  * Telegram notification settings
+    * `buy` -> `entry`
+    * `buy_fill` -> `entry_fill`
+    * `buy_cancel` -> `entry_cancel`
+    * `sell` -> `exit`
+    * `sell_fill` -> `exit_fill`
+    * `sell_cancel` -> `exit_cancel`
+  * Strategy/config settings:
+    * `use_sell_signal` -> `use_exit_signal`
+    * `sell_profit_only` -> `exit_profit_only`
+    * `sell_profit_offset` -> `exit_profit_offset`
+    * `ignore_roi_if_buy_signal` -> `ignore_roi_if_entry_signal`
+    * `forcebuy_enable` -> `force_entry_enable`
+
+## Extensive explanation
+
+### `populate_buy_trend`
+
+In `populate_buy_trend()` - you will want to change the columns you assign from `'buy`' to `'enter_long'`, as well as the method name from `populate_buy_trend` to `populate_entry_trend`.
+
+```python hl_lines="1 9"
+def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    dataframe.loc[
+        (
+            (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+            (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard
+            (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard
+            (dataframe['volume'] > 0)  # Make sure Volume is not 0
+        ),
+        ['buy', 'buy_tag']] = (1, 'rsi_cross')
+
+    return dataframe
+```
+
+After:
+
+```python hl_lines="1 9"
+def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    dataframe.loc[
+        (
+            (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+            (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard
+            (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard
+            (dataframe['volume'] > 0)  # Make sure Volume is not 0
+        ),
+        ['enter_long', 'enter_tag']] = (1, 'rsi_cross')
+
+    return dataframe
+```
+
+Please refer to the [Strategy documentation](strategy-customization.md#entry-signal-rules) on how to enter and exit short trades.
+
+### `populate_sell_trend`
+
+Similar to `populate_buy_trend`, `populate_sell_trend()` will be renamed to `populate_exit_trend()`.
+We'll also change the column from `'sell'` to `'exit_long'`.
+
+``` python hl_lines="1 9"
+def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    dataframe.loc[
+        (
+            (qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+            (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard
+            (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard
+            (dataframe['volume'] > 0)  # Make sure Volume is not 0
+        ),
+        ['sell', 'exit_tag']] = (1, 'some_exit_tag')
+    return dataframe
+```
+
+After
+
+``` python hl_lines="1 9"
+def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    dataframe.loc[
+        (
+            (qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+            (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard
+            (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard
+            (dataframe['volume'] > 0)  # Make sure Volume is not 0
+        ),
+        ['exit_long', 'exit_tag']] = (1, 'some_exit_tag')
+    return dataframe
+```
+
+Please refer to the [Strategy documentation](strategy-customization.md#exit-signal-rules) on how to enter and exit short trades.
+
+### `custom_sell`
+
+`custom_sell` has been renamed to `custom_exit`.
+It's now also being called for every iteration, independent of current profit and `exit_profit_only` settings.
+
+``` python hl_lines="2"
+class AwesomeStrategy(IStrategy):
+    def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
+                    current_profit: float, **kwargs):
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last_candle = dataframe.iloc[-1].squeeze()
+        # ...
+```
+
+``` python hl_lines="2"
+class AwesomeStrategy(IStrategy):
+    def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
+                    current_profit: float, **kwargs):
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+        last_candle = dataframe.iloc[-1].squeeze()
+        # ...
+```
+
+### `custom_entry_timeout`
+
+`check_buy_timeout()` has been renamed to `check_entry_timeout()`, and `check_sell_timeout()` has been renamed to `check_exit_timeout()`.
+
+``` python hl_lines="2 6"
+class AwesomeStrategy(IStrategy):
+    def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, 
+                            current_time: datetime, **kwargs) -> bool:
+        return False
+
+    def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, 
+                            current_time: datetime, **kwargs) -> bool:
+        return False 
+```
+
+``` python hl_lines="2 6"
+class AwesomeStrategy(IStrategy):
+    def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order', 
+                            current_time: datetime, **kwargs) -> bool:
+        return False
+
+    def check_exit_timeout(self, pair: str, trade: 'Trade', order: 'Order', 
+                            current_time: datetime, **kwargs) -> bool:
+        return False 
+```
+
+### Custom-stake-amount
+
+New string argument `side` - which can be either `"long"` or `"short"`.
+
+``` python hl_lines="4"
+class AwesomeStrategy(IStrategy):
+    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
+                            proposed_stake: float, min_stake: float, max_stake: float,
+                            entry_tag: Optional[str], **kwargs) -> float:
+        # ... 
+        return proposed_stake
+```
+
+``` python hl_lines="4"
+class AwesomeStrategy(IStrategy):
+    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
+                            proposed_stake: float, min_stake: float, max_stake: float,
+                            entry_tag: Optional[str], side: str, **kwargs) -> float:
+        # ... 
+        return proposed_stake
+```
+
+### `confirm_trade_entry`
+
+New string argument `side` - which can be either `"long"` or `"short"`.
+
+``` python hl_lines="4"
+class AwesomeStrategy(IStrategy):
+    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
+                            time_in_force: str, current_time: datetime, entry_tag: Optional[str], 
+                            **kwargs) -> bool:
+      return True
+```
+
+After: 
+
+``` python hl_lines="4"
+class AwesomeStrategy(IStrategy):
+    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
+                            time_in_force: str, current_time: datetime, entry_tag: Optional[str], 
+                            side: str, **kwargs) -> bool:
+      return True
+```
+
+### `confirm_trade_exit`
+
+Changed argument `sell_reason` to `exit_reason`.
+For compatibility, `sell_reason` will still be provided for a limited time.
+
+``` python hl_lines="3"
+class AwesomeStrategy(IStrategy):
+    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
+                           rate: float, time_in_force: str, sell_reason: str,
+                           current_time: datetime, **kwargs) -> bool:
+    return True
+```
+
+After:
+
+``` python hl_lines="3"
+class AwesomeStrategy(IStrategy):
+    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
+                           rate: float, time_in_force: str, exit_reason: str,
+                           current_time: datetime, **kwargs) -> bool:
+    return True
+```
+
+### `custom_entry_price`
+
+New string argument `side` - which can be either `"long"` or `"short"`.
+
+``` python hl_lines="3"
+class AwesomeStrategy(IStrategy):
+    def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
+                           entry_tag: Optional[str], **kwargs) -> float:
+      return proposed_rate
+```
+
+After:
+
+``` python hl_lines="3"
+class AwesomeStrategy(IStrategy):
+    def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
+                           entry_tag: Optional[str], side: str, **kwargs) -> float:
+      return proposed_rate
+```
+
+### Adjust trade position changes
+
+While adjust-trade-position itself did not change, you should no longer use `trade.nr_of_successful_buys` - and instead use `trade.nr_of_successful_entries`, which will also include short entries.
+
+### Helper methods
+
+Added argument "is_short" to `stoploss_from_open` and `stoploss_from_absolute`.
+This should be given the value of `trade.is_short`.
+
+``` python hl_lines="5 7"
+    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+                        current_rate: float, current_profit: float, **kwargs) -> float:
+        # once the profit has risen above 10%, keep the stoploss at 7% above the open price
+        if current_profit > 0.10:
+            return stoploss_from_open(0.07, current_profit)
+
+        return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate)
+
+        return 1
+
+```
+
+After:
+
+``` python hl_lines="5 7"
+    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+                        current_rate: float, current_profit: float, **kwargs) -> float:
+        # once the profit has risen above 10%, keep the stoploss at 7% above the open price
+        if current_profit > 0.10:
+            return stoploss_from_open(0.07, current_profit, is_short=trade.is_short)
+
+        return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate, is_short=trade.is_short)
+
+
+```
+
+### Strategy/Configuration settings
+
+#### `order_time_in_force`
+
+`order_time_in_force` attributes changed from `"buy"` to `"entry"` and `"sell"` to `"exit"`.
+
+``` python
+    order_time_in_force: Dict = {
+        "buy": "gtc",
+        "sell": "gtc",
+    }
+```
+
+After:
+
+``` python hl_lines="2 3"
+    order_time_in_force: Dict = {
+        "entry": "gtc",
+        "exit": "gtc",
+    }
+```
+
+#### `order_types`
+
+`order_types` have changed all wordings from `buy` to `entry` - and `sell` to `exit`.
+And two words are joined with `_`. 
+
+``` python hl_lines="2-6"
+    order_types = {
+        "buy": "limit",
+        "sell": "limit",
+        "emergencysell": "market",
+        "forcesell": "market",
+        "forcebuy": "market",
+        "stoploss": "market",
+        "stoploss_on_exchange": false,
+        "stoploss_on_exchange_interval": 60
+    }
+```
+
+After:
+
+``` python hl_lines="2-6"
+    order_types = {
+        "entry": "limit",
+        "exit": "limit",
+        "emergency_exit": "market",
+        "force_exit": "market",
+        "force_entry": "market",
+        "stoploss": "market",
+        "stoploss_on_exchange": false,
+        "stoploss_on_exchange_interval": 60
+    }
+```
+
+#### Strategy level settings
+
+* `use_sell_signal` -> `use_exit_signal`
+* `sell_profit_only` -> `exit_profit_only`
+* `sell_profit_offset` -> `exit_profit_offset`
+* `ignore_roi_if_buy_signal` -> `ignore_roi_if_entry_signal`
+
+``` python hl_lines="2-5"
+    # These values can be overridden in the config.
+    use_sell_signal = True
+    sell_profit_only = True
+    sell_profit_offset: 0.01
+    ignore_roi_if_buy_signal = False
+```
+
+After:
+
+``` python hl_lines="2-5"
+    # These values can be overridden in the config.
+    use_exit_signal = True
+    exit_profit_only = True
+    exit_profit_offset: 0.01
+    ignore_roi_if_entry_signal = False
+```
+
+#### `unfilledtimeout`
+
+`unfilledtimeout` have changed all wordings from `buy` to `entry` - and `sell` to `exit`.
+
+``` python hl_lines="2-3"
+unfilledtimeout = {
+        "buy": 10,
+        "sell": 10,
+        "exit_timeout_count": 0,
+        "unit": "minutes"
+    }
+```
+
+After:
+
+``` python hl_lines="2-3"
+unfilledtimeout = {
+        "entry": 10,
+        "exit": 10,
+        "exit_timeout_count": 0,
+        "unit": "minutes"
+    }
+```
+
+#### `order pricing`
+
+Order pricing changed in 2 ways. `bid_strategy` was renamed to `entry_pricing` and `ask_strategy` was renamed to `exit_pricing`.
+The attributes `ask_last_balance` -> `price_last_balance` and `bid_last_balance` -> `price_last_balance` were renamed as well.
+Also, price-side can now be defined as `ask`, `bid`, `same` or `other`.
+Please refer to the [pricing documentation](configuration.md#prices-used-for-orders) for more information.
+
+``` json hl_lines="2-3 6 12-13 16"
+{
+    "bid_strategy": {
+        "price_side": "bid",
+        "use_order_book": true,
+        "order_book_top": 1,
+        "ask_last_balance": 0.0,
+        "check_depth_of_market": {
+            "enabled": false,
+            "bids_to_ask_delta": 1
+        }
+    },
+    "ask_strategy":{
+        "price_side": "ask",
+        "use_order_book": true,
+        "order_book_top": 1,
+        "bid_last_balance": 0.0
+    }
+}
+```
+
+after:
+
+``` json  hl_lines="2-3 6 12-13 16"
+{
+    "entry_pricing": {
+        "price_side": "same",
+        "use_order_book": true,
+        "order_book_top": 1,
+        "price_last_balance": 0.0,
+        "check_depth_of_market": {
+            "enabled": false,
+            "bids_to_ask_delta": 1
+        }
+    },
+    "exit_pricing":{
+        "price_side": "same",
+        "use_order_book": true,
+        "order_book_top": 1,
+        "price_last_balance": 0.0
+    }
+}
+```
diff --git a/docs/telegram-usage.md b/docs/telegram-usage.md
index b9d01a236..27f5f91b6 100644
--- a/docs/telegram-usage.md
+++ b/docs/telegram-usage.md
@@ -58,6 +58,8 @@ For the Freqtrade configuration, you can then use the the full value (including
 ```json
    "chat_id": "-1001332619709"
 ```
+!!! Warning "Using telegram groups"
+    When using telegram groups, you're giving every member of the telegram group access to your freqtrade bot and to all commands possible via telegram. Please make sure that you can trust everyone in the telegram group to avoid unpleasent surprises.
 
 ## Control telegram noise
 
@@ -79,21 +81,21 @@ Example configuration showing the different settings:
         "status": "silent",
         "warning": "on",
         "startup": "off",
-        "buy": "silent",
-        "sell": {
+        "entry": "silent",
+        "exit": {
             "roi": "silent",
-            "emergency_sell": "on",
-            "force_sell": "on",
-            "sell_signal": "silent",
+            "emergency_exit": "on",
+            "force_exit": "on",
+            "exit_signal": "silent",
             "trailing_stop_loss": "on",
             "stop_loss": "on",
             "stoploss_on_exchange": "on",
-            "custom_sell": "silent"
+            "custom_exit": "silent"
         },
-        "buy_cancel": "silent",
-        "sell_cancel": "on",
-        "buy_fill": "off",
-        "sell_fill": "off",
+        "entry_cancel": "silent",
+        "exit_cancel": "on",
+        "entry_fill": "off",
+        "exit_fill": "off",
         "protection_trigger": "off",
         "protection_trigger_global": "on"
     },
@@ -102,8 +104,8 @@ Example configuration showing the different settings:
 },
 ```
 
-`buy` notifications are sent when the order is placed, while `buy_fill` notifications are sent when the order is filled on the exchange.
-`sell` notifications are sent when the order is placed, while `sell_fill` notifications are sent when the order is filled on the exchange.
+`entry` notifications are sent when the order is placed, while `entry_fill` notifications are sent when the order is filled on the exchange.
+`exit` notifications are sent when the order is placed, while `exit_fill` notifications are sent when the order is filled on the exchange.
 `*_fill` notifications are off by default and must be explicitly enabled.
 `protection_trigger` notifications are sent when a protection triggers and `protection_trigger_global` notifications trigger when global protections are triggered.
 
@@ -169,13 +171,19 @@ official commands. You can ask at any moment for help with `/help`.
 | `/locks` | Show currently locked pairs.
 | `/unlock <pair or lock_id>` | Remove the lock for this pair (or for this lock id).
 | `/profit [<n>]` | Display a summary of your profit/loss from close trades and some stats about your performance, over the last n days (all trades by default)
-| `/forcesell <trade_id>` | Instantly sells the given trade  (Ignoring `minimum_roi`).
-| `/forcesell all` | Instantly sells all open trades (Ignoring `minimum_roi`).
-| `/forcebuy <pair> [rate]` | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
+| `/forceexit <trade_id>` | Instantly exits the given trade  (Ignoring `minimum_roi`).
+| `/forceexit all` | Instantly exits all open trades (Ignoring `minimum_roi`).
+| `/fx` | alias for `/forceexit`
+| `/forcelong <pair> [rate]` | Instantly buys the given pair. Rate is optional and only applies to limit orders. (`force_entry_enable` must be set to True)
+| `/forceshort <pair> [rate]` | Instantly shorts the given pair. Rate is optional and only applies to limit orders. This will only work on non-spot markets. (`force_entry_enable` must be set to True)
 | `/performance` | Show performance of each finished trade grouped by pair
 | `/balance` | Show account balance per currency
 | `/daily <n>` | Shows profit or loss per day, over the last n days (n defaults to 7)
-| `/stats` | Shows Wins / losses by Sell reason as well as Avg. holding durations for buys and sells
+| `/weekly <n>` | Shows profit or loss per week, over the last n weeks (n defaults to 8)
+| `/monthly <n>` | Shows profit or loss per month, over the last n months (n defaults to 6)
+| `/stats` | Shows Wins / losses by Exit reason as well as Avg. holding durations for buys and sells
+| `/exits` | Shows Wins / losses by Exit reason as well as Avg. holding durations for buys and sells
+| `/entries` | Shows Wins / losses by Exit reason as well as Avg. holding durations for buys and sells
 | `/whitelist` | Show the current whitelist
 | `/blacklist [pair]` | Show the current blacklist, or adds a pair to the blacklist.
 | `/edge` | Show validated pairs by Edge if it is enabled.
@@ -212,11 +220,14 @@ Once all positions are sold, run `/stop` to completely stop the bot.
 ### /status
 
 For each open trade, the bot will send you the following message.
+Enter Tag is configurable via Strategy.
 
 > **Trade ID:** `123` `(since 1 days ago)`  
 > **Current Pair:** CVC/BTC  
-> **Open Since:** `1 days ago`  
+> **Direction:** Long
+> **Leverage:** 1.0
 > **Amount:** `26.64180098`  
+> **Enter Tag:** Awesome Long Signal
 > **Open Rate:** `0.00007489`  
 > **Current Rate:** `0.00007489`  
 > **Current Profit:** `12.95%`  
@@ -227,10 +238,10 @@ For each open trade, the bot will send you the following message.
 Return the status of all open trades in a table format.
 
 ```
-   ID  Pair      Since    Profit
-----  --------  -------  --------
-  67  SC/BTC    1 d      13.33%
- 123  CVC/BTC   1 h      12.95%
+ID L/S    Pair     Since   Profit
+----    --------  -------  --------
+  67 L   SC/BTC    1 d      13.33%
+ 123 S   CVC/BTC   1 h      12.95%
 ```
 
 ### /count
@@ -264,21 +275,27 @@ The relative profit of `1.2%` is the average profit per trade.
 The relative profit of `15.2 Σ%` is be based on the starting capital - so in this case, the starting capital was `0.00485701 * 1.152 = 0.00738 BTC`.
 Starting capital is either taken from the `available_capital` setting, or calculated by using current wallet size - profits.
 
-### /forcesell <trade_id>
+### /forceexit <trade_id>
 
-> **BITTREX:** Selling BTC/LTC with limit `0.01650000 (profit: ~-4.07%, -0.00008168)`
+> **BINANCE:** Exiting BTC/LTC with limit `0.01650000 (profit: ~-4.07%, -0.00008168)`
 
-### /forcebuy <pair> [rate]
+!!! Tip
+    You can get a list of all open trades by calling `/forceexit` without parameter, which will show a list of buttons to simply exit a trade.
 
-> **BITTREX:** Buying ETH/BTC with limit `0.03400000` (`1.000000 ETH`, `225.290 USD`)
+### /forcelong <pair> [rate] | /forceshort <pair> [rate]
 
-Omitting the pair will open a query asking for the pair to buy (based on the current whitelist).
+`/forcebuy <pair> [rate]` is also supported for longs but should be considered deprecated.
+
+> **BINANCE:** Long ETH/BTC with limit `0.03400000` (`1.000000 ETH`, `225.290 USD`)
+
+Omitting the pair will open a query asking for the pair to trade (based on the current whitelist).
+Trades created through `/forcelong` will have the buy-tag of `force_entry`.
 
 ![Telegram force-buy screenshot](assets/telegram_forcebuy.png)
 
-Note that for this to work, `forcebuy_enable` needs to be set to true.
+Note that for this to work, `force_entry_enable` needs to be set to true.
 
-[More details](configuration.md#understand-forcebuy_enable)
+[More details](configuration.md#understand-force_entry_enable)
 
 ### /performance
 
@@ -307,8 +324,7 @@ Return the balance of all crypto-currency your have on the exchange.
 
 ### /daily <n>
 
-Per default `/daily` will return the 7 last days.
-The example below if for `/daily 3`:
+Per default `/daily` will return the 7 last days. The example below if for `/daily 3`:
 
 > **Daily Profit over the last 3 days:**
 ```
@@ -319,6 +335,34 @@ Day         Profit BTC      Profit USD
 2018-01-01  0.00269130 BTC  34.986 USD
 ```
 
+### /weekly <n>
+
+Per default `/weekly` will return the 8 last weeks, including the current week. Each week starts
+from Monday. The example below if for `/weekly 3`:
+
+> **Weekly Profit over the last 3 weeks (starting from Monday):**
+```
+Monday         Profit BTC      Profit USD
+----------  --------------  ------------
+2018-01-03  0.00224175 BTC  29,142 USD
+2017-12-27  0.00033131 BTC   4,307 USD
+2017-12-20  0.00269130 BTC  34.986 USD
+```
+
+### /monthly <n>
+
+Per default `/monthly` will return the 6 last months, including the current month. The example below
+if for `/monthly 3`:
+
+> **Monthly Profit over the last 3 months:**
+```
+Month         Profit BTC      Profit USD
+----------  --------------  ------------
+2018-01     0.00224175 BTC  29,142 USD
+2017-12     0.00033131 BTC   4,307 USD
+2017-11     0.00269130 BTC  34.986 USD
+```
+
 ### /whitelist
 
 Shows the current whitelist
diff --git a/docs/updating.md b/docs/updating.md
index b23ce32dc..1839edc4c 100644
--- a/docs/updating.md
+++ b/docs/updating.md
@@ -2,6 +2,10 @@
 
 To update your freqtrade installation, please use one of the below methods, corresponding to your installation method.
 
+!!! Note "Tracking changes"
+    Breaking changes / changed behavior will be documented in the changelog that is posted alongside every release.
+    For the develop branch, please follow PR's to avoid being surprised by changes.
+
 ## docker-compose
 
 !!! Note "Legacy installations using the `master` image"
diff --git a/docs/utils.md b/docs/utils.md
index d8fbcacb7..5ef5646c3 100644
--- a/docs/utils.md
+++ b/docs/utils.md
@@ -59,7 +59,7 @@ $ freqtrade new-config --config config_binance.json
 ? Do you want to enable Dry-run (simulated trades)?  Yes
 ? Please insert your stake currency: BTC
 ? Please insert your stake amount: 0.05
-? Please insert max_open_trades (Integer or 'unlimited'): 3
+? Please insert max_open_trades (Integer or -1 for unlimited open trades): 3
 ? Please insert your desired timeframe (e.g. 5m): 5m
 ? Please insert your display Currency (for reporting): USD
 ? Select exchange  binance
@@ -281,7 +281,7 @@ bitmax              True     missing opt: fetchMyTrades
 bitmex              False    Various reasons.
 bitpanda            True
 bitso               False    missing: fetchOHLCV
-bitstamp            False    Does not provide history. Details in https://github.com/freqtrade/freqtrade/issues/1983
+bitstamp            True     missing opt: fetchTickers
 bitstamp1           False    missing: fetchOrder, fetchOHLCV
 bittrex             True
 bitvavo             True
@@ -439,14 +439,15 @@ usage: freqtrade list-markets [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                               [-d PATH] [--userdir PATH] [--exchange EXCHANGE]
                               [--print-list] [--print-json] [-1] [--print-csv]
                               [--base BASE_CURRENCY [BASE_CURRENCY ...]]
-                              [--quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]]
-                              [-a]
+                              [--quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]] [-a]
+                              [--trading-mode {spot,margin,futures}]
 
 usage: freqtrade list-pairs [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                             [-d PATH] [--userdir PATH] [--exchange EXCHANGE]
                             [--print-list] [--print-json] [-1] [--print-csv]
                             [--base BASE_CURRENCY [BASE_CURRENCY ...]]
                             [--quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]] [-a]
+                            [--trading-mode {spot,margin,futures}]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -463,6 +464,8 @@ optional arguments:
                         Specify quote currency(-ies). Space-separated list.
   -a, --all             Print all pairs or market symbols. By default only
                         active ones are shown.
+  --trading-mode {spot,margin,futures}
+                        Select Trading mode
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
@@ -517,20 +520,25 @@ Requires a configuration with specified `pairlists` attribute.
 Can be used to generate static pairlists to be used during backtesting / hyperopt.
 
 ```
-usage: freqtrade test-pairlist [-h] [-c PATH]
+usage: freqtrade test-pairlist [-h] [-v] [-c PATH]
                                [--quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]]
-                               [-1] [--print-json]
+                               [-1] [--print-json] [--exchange EXCHANGE]
 
 optional arguments:
   -h, --help            show this help message and exit
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
   -c PATH, --config PATH
-                        Specify configuration file (default: `config.json`).
-                        Multiple --config options may be used. Can be set to
-                        `-` to read config from stdin.
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
   --quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]
                         Specify quote currency(-ies). Space-separated list.
   -1, --one-column      Print output in one column.
   --print-json          Print list of pairs or market symbols in JSON format.
+  --exchange EXCHANGE   Exchange name (default: `bittrex`). Only valid if no
+                        config is provided.
+
 ```
 
 ### Examples
@@ -577,6 +585,46 @@ Common arguments:
 
 ```
 
+## Show previous Backtest results
+
+Allows you to show previous backtest results.
+Adding `--show-pair-list` outputs a sorted pair list you can easily copy/paste into your configuration (omitting bad pairs).
+
+??? Warning "Strategy overfitting"
+    Only using winning pairs can lead to an overfitted strategy, which will not work well on future data. Make sure to extensively test your strategy in dry-run before risking real money.
+
+```
+usage: freqtrade backtesting-show [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                                  [-d PATH] [--userdir PATH]
+                                  [--export-filename PATH] [--show-pair-list]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --export-filename PATH
+                        Save backtest results to the file with this filename.
+                        Requires `--export` to be set as well. Example:
+                        `--export-filename=user_data/backtest_results/backtest
+                        _today.json`
+  --show-pair-list      Show backtesting pairlist sorted by profit.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+```
+
 ## List Hyperopt results
 
 You can list the hyperoptimization epochs the Hyperopt module evaluated previously with the `hyperopt-list` sub-command.
@@ -667,6 +715,7 @@ usage: freqtrade hyperopt-show [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                                [--profitable] [-n INT] [--print-json]
                                [--hyperopt-filename FILENAME] [--no-header]
                                [--disable-param-export]
+                               [--breakdown {day,week,month} [{day,week,month} ...]]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -680,6 +729,8 @@ optional arguments:
   --no-header           Do not print epoch details header.
   --disable-param-export
                         Disable automatic hyperopt parameter export.
+  --breakdown {day,week,month} [{day,week,month} ...]
+                        Show backtesting breakdown per [day, week, month].
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
diff --git a/docs/webhook-config.md b/docs/webhook-config.md
index 288afc384..5f5933b47 100644
--- a/docs/webhook-config.md
+++ b/docs/webhook-config.md
@@ -10,33 +10,33 @@ Sample configuration (tested using IFTTT).
   "webhook": {
         "enabled": true,
         "url": "https://maker.ifttt.com/trigger/<YOUREVENT>/with/key/<YOURKEY>/",
-        "webhookbuy": {
+        "webhookentry": {
             "value1": "Buying {pair}",
             "value2": "limit {limit:8f}",
             "value3": "{stake_amount:8f} {stake_currency}"
         },
-        "webhookbuycancel": {
+        "webhookentrycancel": {
             "value1": "Cancelling Open Buy Order for {pair}",
             "value2": "limit {limit:8f}",
             "value3": "{stake_amount:8f} {stake_currency}"
         },
-         "webhookbuyfill": {
+         "webhookentryfill": {
             "value1": "Buy Order for {pair} filled",
             "value2": "at {open_rate:8f}",
             "value3": ""
         },
-        "webhooksell": {
-            "value1": "Selling {pair}",
+        "webhookexit": {
+            "value1": "Exiting {pair}",
             "value2": "limit {limit:8f}",
             "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
         },
-        "webhooksellcancel": {
-            "value1": "Cancelling Open Sell Order for {pair}",
+        "webhookexitcancel": {
+            "value1": "Cancelling Open Exit Order for {pair}",
             "value2": "limit {limit:8f}",
             "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
         },
-        "webhooksellfill": {
-            "value1": "Sell Order for {pair} filled",
+        "webhookexitfill": {
+            "value1": "Exit Order for {pair} filled",
             "value2": "at {close_rate:8f}.",
             "value3": ""
         },
@@ -48,9 +48,9 @@ Sample configuration (tested using IFTTT).
     },
 ```
 
-The url in `webhook.url` should point to the correct url for your webhook. If you're using [IFTTT](https://ifttt.com) (as shown in the sample above) please insert our event and key to the url.
+The url in `webhook.url` should point to the correct url for your webhook. If you're using [IFTTT](https://ifttt.com) (as shown in the sample above) please insert your event and key to the url.
 
-You can set the POST body format to Form-Encoded (default) or JSON-Encoded. Use `"format": "form"` or `"format": "json"` respectively. Example configuration for Mattermost Cloud integration:
+You can set the POST body format to Form-Encoded (default), JSON-Encoded, or raw data. Use `"format": "form"`, `"format": "json"`, or `"format": "raw"` respectively. Example configuration for Mattermost Cloud integration:
 
 ```json
   "webhook": {
@@ -63,70 +63,113 @@ You can set the POST body format to Form-Encoded (default) or JSON-Encoded. Use
     },
 ```
 
-The result would be POST request with e.g. `{"text":"Status: running"}` body and `Content-Type: application/json` header which results `Status: running` message in the Mattermost channel.
+The result would be a POST request with e.g. `{"text":"Status: running"}` body and `Content-Type: application/json` header which results `Status: running` message in the Mattermost channel.
+
+When using the Form-Encoded or JSON-Encoded configuration you can configure any number of payload values, and both the key and value will be ouput in the POST request. However, when using the raw data format you can only configure one value and it **must** be named `"data"`. In this instance the data key will not be output in the POST request, only the value. For example:
+
+```json
+  "webhook": {
+        "enabled": true,
+        "url": "https://<YOURHOOKURL>",
+        "format": "raw",
+        "webhookstatus": {
+            "data": "Status: {status}"
+        }
+    },
+```
+
+The result would be a POST request with e.g. `Status: running` body and `Content-Type: text/plain` header.
+
+Optional parameters are available to enable automatic retries for webhook messages. The `webhook.retries` parameter can be set for the maximum number of retries the webhook request should attempt if it is unsuccessful (i.e. HTTP response status is not 200). By default this is set to `0` which is disabled. An additional `webhook.retry_delay` parameter can be set to specify the time in seconds between retry attempts. By default this is set to `0.1` (i.e. 100ms). Note that increasing the number of retries or retry delay may slow down the trader if there are connectivity issues with the webhook. Example configuration for retries:
+
+```json
+  "webhook": {
+        "enabled": true,
+        "url": "https://<YOURHOOKURL>",
+        "retries": 3,
+        "retry_delay": 0.2,
+        "webhookstatus": {
+            "status": "Status: {status}"
+        }
+    },
+```
 
 Different payloads can be configured for different events. Not all fields are necessary, but you should configure at least one of the dicts, otherwise the webhook will never be called.
 
-### Webhookbuy
+### Webhookentry
 
-The fields in `webhook.webhookbuy` are filled when the bot executes a buy. Parameters are filled using string.format.
-Possible parameters are:
-
-* `trade_id`
-* `exchange`
-* `pair`
-* `limit`
-* `amount`
-* `open_date`
-* `stake_amount`
-* `stake_currency`
-* `fiat_currency`
-* `order_type`
-* `current_rate`
-* `buy_tag`
-
-### Webhookbuycancel
-
-The fields in `webhook.webhookbuycancel` are filled when the bot cancels a buy order. Parameters are filled using string.format.
-Possible parameters are:
-
-* `trade_id`
-* `exchange`
-* `pair`
-* `limit`
-* `amount`
-* `open_date`
-* `stake_amount`
-* `stake_currency`
-* `fiat_currency`
-* `order_type`
-* `current_rate`
-* `buy_tag`
-
-### Webhookbuyfill
-
-The fields in `webhook.webhookbuyfill` are filled when the bot filled a buy order. Parameters are filled using string.format.
+The fields in `webhook.webhookentry` are filled when the bot executes a long/short. Parameters are filled using string.format.
 Possible parameters are:
 
 * `trade_id`
 * `exchange`
 * `pair`
+* `direction`
+* `leverage`
+* ~~`limit` # Deprecated - should no longer be used.~~
 * `open_rate`
 * `amount`
 * `open_date`
 * `stake_amount`
 * `stake_currency`
+* `base_currency`
 * `fiat_currency`
-* `buy_tag`
+* `order_type`
+* `current_rate`
+* `enter_tag`
 
-### Webhooksell
+### Webhookentrycancel
 
-The fields in `webhook.webhooksell` are filled when the bot sells a trade. Parameters are filled using string.format.
+The fields in `webhook.webhookentrycancel` are filled when the bot cancels a long/short order. Parameters are filled using string.format.
 Possible parameters are:
 
 * `trade_id`
 * `exchange`
 * `pair`
+* `direction`
+* `leverage`
+* `limit`
+* `amount`
+* `open_date`
+* `stake_amount`
+* `stake_currency`
+* `base_currency`
+* `fiat_currency`
+* `order_type`
+* `current_rate`
+* `enter_tag`
+
+### Webhookentryfill
+
+The fields in `webhook.webhookentryfill` are filled when the bot filled a long/short order. Parameters are filled using string.format.
+Possible parameters are:
+
+* `trade_id`
+* `exchange`
+* `pair`
+* `direction`
+* `leverage`
+* `open_rate`
+* `amount`
+* `open_date`
+* `stake_amount`
+* `stake_currency`
+* `base_currency`
+* `fiat_currency`
+* `order_type`
+* `current_rate`
+* `enter_tag`
+
+### Webhookexit
+
+The fields in `webhook.webhookexit` are filled when the bot exits a trade. Parameters are filled using string.format.
+Possible parameters are:
+
+* `trade_id`
+* `exchange`
+* `pair`
+* `direction`
+* `leverage`
 * `gain`
 * `limit`
 * `amount`
@@ -134,20 +177,23 @@ Possible parameters are:
 * `profit_amount`
 * `profit_ratio`
 * `stake_currency`
+* `base_currency`
 * `fiat_currency`
-* `sell_reason`
+* `exit_reason`
 * `order_type`
 * `open_date`
 * `close_date`
 
-### Webhooksellfill
+### Webhookexitfill
 
-The fields in `webhook.webhooksellfill` are filled when the bot fills a sell order (closes a Trae). Parameters are filled using string.format.
+The fields in `webhook.webhookexitfill` are filled when the bot fills a exit order (closes a Trade). Parameters are filled using string.format.
 Possible parameters are:
 
 * `trade_id`
 * `exchange`
 * `pair`
+* `direction`
+* `leverage`
 * `gain`
 * `close_rate`
 * `amount`
@@ -156,20 +202,23 @@ Possible parameters are:
 * `profit_amount`
 * `profit_ratio`
 * `stake_currency`
+* `base_currency`
 * `fiat_currency`
-* `sell_reason`
+* `exit_reason`
 * `order_type`
 * `open_date`
 * `close_date`
 
-### Webhooksellcancel
+### Webhookexitcancel
 
-The fields in `webhook.webhooksellcancel` are filled when the bot cancels a sell order. Parameters are filled using string.format.
+The fields in `webhook.webhookexitcancel` are filled when the bot cancels a exit order. Parameters are filled using string.format.
 Possible parameters are:
 
 * `trade_id`
 * `exchange`
 * `pair`
+* `direction`
+* `leverage`
 * `gain`
 * `limit`
 * `amount`
@@ -178,8 +227,9 @@ Possible parameters are:
 * `profit_amount`
 * `profit_ratio`
 * `stake_currency`
+* `base_currency`
 * `fiat_currency`
-* `sell_reason`
+* `exit_reason`
 * `order_type`
 * `open_date`
 * `close_date`
diff --git a/docs/windows_installation.md b/docs/windows_installation.md
index 2db0ae913..242c994c4 100644
--- a/docs/windows_installation.md
+++ b/docs/windows_installation.md
@@ -23,9 +23,9 @@ git clone https://github.com/freqtrade/freqtrade.git
 
 Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7/ta-lib#windows).
 
-As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib-0.4.21-cp38-cp38-win_amd64.whl` (make sure to use the version matching your python version).
+As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib-0.4.24-cp38-cp38-win_amd64.whl` (make sure to use the version matching your python version).
 
-Freqtrade provides these dependencies for the latest 2 Python versions (3.7 and 3.8) and for 64bit Windows.
+Freqtrade provides these dependencies for the latest 3 Python versions (3.8, 3.9 and 3.10) and for 64bit Windows.
 Other versions must be downloaded from the above link.
 
 ``` powershell
@@ -54,6 +54,8 @@ error: Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++
 
 Unfortunately, many packages requiring compilation don't provide a pre-built wheel. It is therefore mandatory to have a C/C++ compiler installed and available for your python environment to use.
 
-The easiest way is to download install Microsoft Visual Studio Community [here](https://visualstudio.microsoft.com/downloads/) and make sure to install "Common Tools for Visual C++" to enable building C code on Windows. Unfortunately, this is a heavy download / dependency (~4Gb) so you might want to consider WSL or [docker compose](docker_quickstart.md) first.
+You can download the Visual C++ build tools from [here](https://visualstudio.microsoft.com/visual-cpp-build-tools/) and install "Desktop development with C++" in it's default configuration. Unfortunately, this is a heavy download / dependency so you might want to consider WSL2 or [docker compose](docker_quickstart.md) first.
+
+![Windows installation](assets/windows_install.png)
 
 ---
diff --git a/environment.yml b/environment.yml
index f58434c15..f2f961894 100644
--- a/environment.yml
+++ b/environment.yml
@@ -4,7 +4,7 @@ channels:
 # - defaults
 dependencies:
 # 1/4 req main
-    - python>=3.7,<3.9
+    - python>=3.8,<=3.10
     - numpy
     - pandas
     - pip
@@ -16,7 +16,6 @@ dependencies:
     - cachetools
     - requests
     - urllib3
-    - wrapt
     - jsonschema
     - TA-Lib
     - tabulate
@@ -26,9 +25,13 @@ dependencies:
     - fastapi
     - uvicorn
     - pyjwt
+    - aiofiles
+    - psutil
     - colorama
     - questionary
     - prompt-toolkit
+    - schedule
+    - python-dateutil
 
 
     # ============================
@@ -64,7 +67,6 @@ dependencies:
         - py_find_1st
         - tables
         - pytest-random-order
-        - flake8-type-annotations
         - ccxt
         - flake8-tidy-imports
         - -e .
diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py
index 2747efc96..f8be8f66f 100644
--- a/freqtrade/__init__.py
+++ b/freqtrade/__init__.py
@@ -1,27 +1,14 @@
 """ Freqtrade bot """
 __version__ = 'develop'
 
-if __version__ == 'develop':
-
+if 'dev' in __version__:
     try:
         import subprocess
 
-        __version__ = 'develop-' + subprocess.check_output(
+        __version__ = __version__ + '-' + subprocess.check_output(
             ['git', 'log', '--format="%h"', '-n 1'],
             stderr=subprocess.DEVNULL).decode("utf-8").rstrip().strip('"')
 
-        # from datetime import datetime
-        # last_release = subprocess.check_output(
-        #     ['git', 'tag']
-        # ).decode('utf-8').split()[-1].split(".")
-        # # Releases are in the format "2020.1" - we increment the latest version for dev.
-        # prefix = f"{last_release[0]}.{int(last_release[1]) + 1}"
-        # dev_version = int(datetime.now().timestamp() // 1000)
-        # __version__ = f"{prefix}.dev{dev_version}"
-
-        #  subprocess.check_output(
-        #     ['git', 'log', '--format="%h"', '-n 1'],
-        #     stderr=subprocess.DEVNULL).decode("utf-8").rstrip().strip('"')
     except Exception:  # pragma: no cover
         # git not available, ignore
         try:
diff --git a/freqtrade/__main__.py b/freqtrade/__main__.py
index ab4c7a110..fc45bdf61 100644
--- a/freqtrade/__main__.py
+++ b/freqtrade/__main__.py
@@ -3,7 +3,7 @@
 __main__.py for Freqtrade
 To launch Freqtrade as a module
 
-> python -m freqtrade (with Python >= 3.7)
+> python -m freqtrade (with Python >= 3.8)
 """
 
 from freqtrade import main
diff --git a/freqtrade/commands/__init__.py b/freqtrade/commands/__init__.py
index a6f14cff7..129836000 100644
--- a/freqtrade/commands/__init__.py
+++ b/freqtrade/commands/__init__.py
@@ -8,15 +8,16 @@ Note: Be careful with file-scoped imports in these subfiles.
 """
 from freqtrade.commands.arguments import Arguments
 from freqtrade.commands.build_config_commands import start_new_config
-from freqtrade.commands.data_commands import (start_convert_data, start_download_data,
-                                              start_list_data)
+from freqtrade.commands.data_commands import (start_convert_data, start_convert_trades,
+                                              start_download_data, start_list_data)
 from freqtrade.commands.deploy_commands import (start_create_userdir, start_install_ui,
                                                 start_new_strategy)
 from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show
 from freqtrade.commands.list_commands import (start_list_exchanges, start_list_markets,
                                               start_list_strategies, start_list_timeframes,
                                               start_show_trades)
-from freqtrade.commands.optimize_commands import start_backtesting, start_edge, start_hyperopt
+from freqtrade.commands.optimize_commands import (start_backtesting, start_backtesting_show,
+                                                  start_edge, start_hyperopt)
 from freqtrade.commands.pairlist_commands import start_test_pairlist
 from freqtrade.commands.plot_commands import start_plot_dataframe, start_plot_profit
 from freqtrade.commands.trade_commands import start_trading
diff --git a/freqtrade/commands/arguments.py b/freqtrade/commands/arguments.py
index d424f3ce7..7d4624bd1 100644
--- a/freqtrade/commands/arguments.py
+++ b/freqtrade/commands/arguments.py
@@ -23,7 +23,8 @@ ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange", "dataformat_ohlcv",
 
 ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions",
                                         "enable_protections", "dry_run_wallet", "timeframe_detail",
-                                        "strategy_list", "export", "exportfilename"]
+                                        "strategy_list", "export", "exportfilename",
+                                        "backtest_breakdown", "backtest_cache"]
 
 ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
                                         "position_stacking", "use_max_market_positions",
@@ -31,7 +32,8 @@ ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
                                         "epochs", "spaces", "print_all",
                                         "print_colorized", "print_json", "hyperopt_jobs",
                                         "hyperopt_random_state", "hyperopt_min_trades",
-                                        "hyperopt_loss", "disableparamexport"]
+                                        "hyperopt_loss", "disableparamexport",
+                                        "hyperopt_ignore_missing_space"]
 
 ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
 
@@ -39,15 +41,18 @@ ARGS_LIST_STRATEGIES = ["strategy_path", "print_one_column", "print_colorized"]
 
 ARGS_LIST_HYPEROPTS = ["hyperopt_path", "print_one_column", "print_colorized"]
 
+ARGS_BACKTEST_SHOW = ["exportfilename", "backtest_show_pair_list"]
+
 ARGS_LIST_EXCHANGES = ["print_one_column", "list_exchanges_all"]
 
 ARGS_LIST_TIMEFRAMES = ["exchange", "print_one_column"]
 
 ARGS_LIST_PAIRS = ["exchange", "print_list", "list_pairs_print_json", "print_one_column",
-                   "print_csv", "base_currencies", "quote_currencies", "list_pairs_all"]
+                   "print_csv", "base_currencies", "quote_currencies", "list_pairs_all",
+                   "trading_mode"]
 
 ARGS_TEST_PAIRLIST = ["verbosity", "config", "quote_currencies", "print_one_column",
-                      "list_pairs_print_json"]
+                      "list_pairs_print_json", "exchange"]
 
 ARGS_CREATE_USERDIR = ["user_data_dir", "reset"]
 
@@ -56,22 +61,26 @@ ARGS_BUILD_CONFIG = ["config"]
 ARGS_BUILD_STRATEGY = ["user_data_dir", "strategy", "template"]
 
 ARGS_CONVERT_DATA = ["pairs", "format_from", "format_to", "erase"]
-ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes"]
 
-ARGS_LIST_DATA = ["exchange", "dataformat_ohlcv", "pairs"]
+ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes", "exchange", "trading_mode",
+                                               "candle_types"]
 
-ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "new_pairs_days", "timerange",
-                      "download_trades", "exchange", "timeframes", "erase", "dataformat_ohlcv",
-                      "dataformat_trades"]
+ARGS_CONVERT_TRADES = ["pairs", "timeframes", "exchange", "dataformat_ohlcv", "dataformat_trades"]
+
+ARGS_LIST_DATA = ["exchange", "dataformat_ohlcv", "pairs", "trading_mode"]
+
+ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "new_pairs_days", "include_inactive",
+                      "timerange", "download_trades", "exchange", "timeframes",
+                      "erase", "dataformat_ohlcv", "dataformat_trades", "trading_mode"]
 
 ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit",
                        "db_url", "trade_source", "export", "exportfilename",
                        "timerange", "timeframe", "no_trades"]
 
 ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url",
-                    "trade_source", "timeframe", "plot_auto_open"]
+                    "trade_source", "timeframe", "plot_auto_open", ]
 
-ARGS_INSTALL_UI = ["erase_ui_only"]
+ARGS_INSTALL_UI = ["erase_ui_only", 'ui_version']
 
 ARGS_SHOW_TRADES = ["db_url", "trade_ids", "print_json"]
 
@@ -86,12 +95,12 @@ ARGS_HYPEROPT_LIST = ["hyperopt_list_best", "hyperopt_list_profitable",
 
 ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperopt_show_index",
                       "print_json", "hyperoptexportfilename", "hyperopt_show_no_header",
-                      "disableparamexport"]
+                      "disableparamexport", "backtest_breakdown"]
 
 NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
                     "list-markets", "list-pairs", "list-strategies", "list-data",
-                    "hyperopt-list", "hyperopt-show",
-                    "plot-dataframe", "plot-profit", "show-trades"]
+                    "hyperopt-list", "hyperopt-show", "backtest-filter",
+                    "plot-dataframe", "plot-profit", "show-trades", "trades-to-ohlcv"]
 
 NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
 
@@ -169,14 +178,15 @@ class Arguments:
         self.parser = argparse.ArgumentParser(description='Free, open source crypto trading bot')
         self._build_args(optionlist=['version'], parser=self.parser)
 
-        from freqtrade.commands import (start_backtesting, start_convert_data, start_create_userdir,
-                                        start_download_data, start_edge, start_hyperopt,
-                                        start_hyperopt_list, start_hyperopt_show, start_install_ui,
-                                        start_list_data, start_list_exchanges, start_list_markets,
-                                        start_list_strategies, start_list_timeframes,
-                                        start_new_config, start_new_strategy, start_plot_dataframe,
-                                        start_plot_profit, start_show_trades, start_test_pairlist,
-                                        start_trading, start_webserver)
+        from freqtrade.commands import (start_backtesting, start_backtesting_show,
+                                        start_convert_data, start_convert_trades,
+                                        start_create_userdir, start_download_data, start_edge,
+                                        start_hyperopt, start_hyperopt_list, start_hyperopt_show,
+                                        start_install_ui, start_list_data, start_list_exchanges,
+                                        start_list_markets, start_list_strategies,
+                                        start_list_timeframes, start_new_config, start_new_strategy,
+                                        start_plot_dataframe, start_plot_profit, start_show_trades,
+                                        start_test_pairlist, start_trading, start_webserver)
 
         subparsers = self.parser.add_subparsers(dest='command',
                                                 # Use custom message when no subhandler is added
@@ -236,6 +246,15 @@ class Arguments:
         convert_trade_data_cmd.set_defaults(func=partial(start_convert_data, ohlcv=False))
         self._build_args(optionlist=ARGS_CONVERT_DATA, parser=convert_trade_data_cmd)
 
+        # Add trades-to-ohlcv subcommand
+        convert_trade_data_cmd = subparsers.add_parser(
+            'trades-to-ohlcv',
+            help='Convert trade data to OHLCV data.',
+            parents=[_common_parser],
+        )
+        convert_trade_data_cmd.set_defaults(func=start_convert_trades)
+        self._build_args(optionlist=ARGS_CONVERT_TRADES, parser=convert_trade_data_cmd)
+
         # Add list-data subcommand
         list_data_cmd = subparsers.add_parser(
             'list-data',
@@ -251,6 +270,15 @@ class Arguments:
         backtesting_cmd.set_defaults(func=start_backtesting)
         self._build_args(optionlist=ARGS_BACKTEST, parser=backtesting_cmd)
 
+        # Add backtesting-show subcommand
+        backtesting_show_cmd = subparsers.add_parser(
+            'backtesting-show',
+            help='Show past Backtest results',
+            parents=[_common_parser],
+        )
+        backtesting_show_cmd.set_defaults(func=start_backtesting_show)
+        self._build_args(optionlist=ARGS_BACKTEST_SHOW, parser=backtesting_show_cmd)
+
         # Add edge subcommand
         edge_cmd = subparsers.add_parser('edge', help='Edge module.',
                                          parents=[_common_parser, _strategy_parser])
diff --git a/freqtrade/commands/build_config_commands.py b/freqtrade/commands/build_config_commands.py
index faa8a98f4..be881c8ed 100644
--- a/freqtrade/commands/build_config_commands.py
+++ b/freqtrade/commands/build_config_commands.py
@@ -76,18 +76,23 @@ def ask_user_config() -> Dict[str, Any]:
         {
             "type": "text",
             "name": "max_open_trades",
-            "message": f"Please insert max_open_trades (Integer or '{UNLIMITED_STAKE_AMOUNT}'):",
+            "message": "Please insert max_open_trades (Integer or -1 for unlimited open trades):",
             "default": "3",
-            "validate": lambda val: val == UNLIMITED_STAKE_AMOUNT or validate_is_int(val),
-            "filter": lambda val: '"' + UNLIMITED_STAKE_AMOUNT + '"'
-            if val == UNLIMITED_STAKE_AMOUNT
-            else val
+            "validate": lambda val: validate_is_int(val)
+        },
+        {
+            "type": "select",
+            "name": "timeframe_in_config",
+            "message": "Time",
+            "choices": ["Have the strategy define timeframe.", "Override in configuration."]
         },
         {
             "type": "text",
             "name": "timeframe",
             "message": "Please insert your desired timeframe (e.g. 5m):",
             "default": "5m",
+            "when": lambda x: x["timeframe_in_config"] == 'Override in configuration.'
+
         },
         {
             "type": "text",
@@ -99,18 +104,28 @@ def ask_user_config() -> Dict[str, Any]:
             "type": "select",
             "name": "exchange_name",
             "message": "Select exchange",
-            "choices": [
+            "choices": lambda x: [
                 "binance",
                 "binanceus",
                 "bittrex",
-                "kraken",
                 "ftx",
-                "kucoin",
                 "gateio",
-                Separator(),
+                "huobi",
+                "kraken",
+                "kucoin",
+                "okx",
+                Separator("------------------"),
                 "other",
             ],
         },
+        {
+            "type": "confirm",
+            "name": "trading_mode",
+            "message": "Do you want to trade Perpetual Swaps (perpetual futures)?",
+            "default": False,
+            "filter": lambda val: 'futures' if val else 'spot',
+            "when": lambda x: x["exchange_name"] in ['binance', 'gateio', 'okx'],
+        },
         {
             "type": "autocomplete",
             "name": "exchange_name",
@@ -134,7 +149,7 @@ def ask_user_config() -> Dict[str, Any]:
             "type": "password",
             "name": "exchange_key_password",
             "message": "Insert Exchange API Key password",
-            "when": lambda x: not x['dry_run'] and x['exchange_name'] == 'kucoin'
+            "when": lambda x: not x['dry_run'] and x['exchange_name'] in ('kucoin', 'okx')
         },
         {
             "type": "confirm",
@@ -163,7 +178,8 @@ def ask_user_config() -> Dict[str, Any]:
         {
             "type": "text",
             "name": "api_server_listen_addr",
-            "message": "Insert Api server Listen Address (best left untouched default!)",
+            "message": ("Insert Api server Listen Address (0.0.0.0 for docker, "
+                        "otherwise best left untouched)"),
             "default": "127.0.0.1",
             "when": lambda x: x['api_server']
         },
@@ -186,7 +202,13 @@ def ask_user_config() -> Dict[str, Any]:
     if not answers:
         # Interrupted questionary sessions return an empty dict.
         raise OperationalException("User interrupted interactive questions.")
-
+    # Ensure default is set for non-futures exchanges
+    answers['trading_mode'] = answers.get('trading_mode', "spot")
+    answers['margin_mode'] = (
+        'isolated'
+        if answers.get('trading_mode') == 'futures'
+        else ''
+    )
     # Force JWT token to be a random string
     answers['api_server_jwt_key'] = secrets.token_hex()
 
diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py
index e3c7fe464..61890d650 100644
--- a/freqtrade/commands/cli_options.py
+++ b/freqtrade/commands/cli_options.py
@@ -5,6 +5,7 @@ from argparse import SUPPRESS, ArgumentTypeError
 
 from freqtrade import __version__, constants
 from freqtrade.constants import HYPEROPT_LOSS_BUILTIN
+from freqtrade.enums import CandleType
 
 
 def check_int_positive(value: str) -> int:
@@ -117,7 +118,7 @@ AVAILABLE_CLI_OPTIONS = {
     ),
     # Optimize common
     "timeframe": Arg(
-        '-i', '--timeframe', '--ticker-interval',
+        '-i', '--timeframe',
         help='Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).',
     ),
     "timerange": Arg(
@@ -152,6 +153,12 @@ AVAILABLE_CLI_OPTIONS = {
         action='store_false',
         default=True,
     ),
+    "backtest_show_pair_list": Arg(
+        '--show-pair-list',
+        help='Show backtesting pairlist sorted by profit.',
+        action='store_true',
+        default=False,
+    ),
     "enable_protections": Arg(
         '--enable-protections', '--enableprotections',
         help='Enable protections for backtesting.'
@@ -163,7 +170,7 @@ AVAILABLE_CLI_OPTIONS = {
     "strategy_list": Arg(
         '--strategy-list',
         help='Provide a space-separated list of strategies to backtest. '
-        'Please note that ticker-interval needs to be set either in config '
+        'Please note that timeframe needs to be set either in config '
         'or via command line. When using this together with `--export trades`, '
         'the strategy-name is injected into the filename '
         '(so `backtest-data.json` becomes `backtest-data-SampleStrategy.json`',
@@ -173,14 +180,14 @@ AVAILABLE_CLI_OPTIONS = {
         '--export',
         help='Export backtest results (default: trades).',
         choices=constants.EXPORT_OPTIONS,
-
     ),
     "exportfilename": Arg(
-        '--export-filename',
-        help='Save backtest results to the file with this filename. '
-        'Requires `--export` to be set as well. '
-        'Example: `--export-filename=user_data/backtest_results/backtest_today.json`',
-        metavar='PATH',
+        "--export-filename",
+        "--backtest-filename",
+        help="Use this filename for backtest results."
+        "Requires `--export` to be set as well. "
+        "Example: `--export-filename=user_data/backtest_results/backtest_today.json`",
+        metavar="PATH",
     ),
     "disableparamexport": Arg(
         '--disable-param-export',
@@ -193,6 +200,18 @@ AVAILABLE_CLI_OPTIONS = {
         type=float,
         metavar='FLOAT',
     ),
+    "backtest_breakdown": Arg(
+        '--breakdown',
+        help='Show backtesting breakdown per [day, week, month].',
+        nargs='+',
+        choices=constants.BACKTEST_BREAKDOWNS
+    ),
+    "backtest_cache": Arg(
+        '--cache',
+        help='Load a cached backtest result no older than specified age (default: %(default)s).',
+        default=constants.BACKTEST_CACHE_DEFAULT,
+        choices=constants.BACKTEST_CACHE_AGE,
+    ),
     # Edge
     "stoploss_range": Arg(
         '--stoplosses',
@@ -337,6 +356,17 @@ AVAILABLE_CLI_OPTIONS = {
         nargs='+',
         metavar='BASE_CURRENCY',
     ),
+    "trading_mode": Arg(
+        '--trading-mode',
+        help='Select Trading mode',
+        choices=constants.TRADING_MODES,
+    ),
+    "candle_types": Arg(
+        '--candle-types',
+        help='Select candle type to use',
+        choices=[c.value for c in CandleType],
+        nargs='+',
+    ),
     # Script options
     "pairs": Arg(
         '-p', '--pairs',
@@ -355,6 +385,11 @@ AVAILABLE_CLI_OPTIONS = {
         type=check_int_positive,
         metavar='INT',
     ),
+    "include_inactive": Arg(
+        '--include-inactive-pairs',
+        help='Also download data from inactive pairs.',
+        action='store_true',
+    ),
     "new_pairs_days": Arg(
         '--new-pairs-days',
         help='Download data of new pairs for given number of days. Default: `%(default)s`.',
@@ -381,12 +416,12 @@ AVAILABLE_CLI_OPTIONS = {
     ),
     "dataformat_ohlcv": Arg(
         '--data-format-ohlcv',
-        help='Storage format for downloaded candle (OHLCV) data. (default: `%(default)s`).',
+        help='Storage format for downloaded candle (OHLCV) data. (default: `json`).',
         choices=constants.AVAILABLE_DATAHANDLERS,
     ),
     "dataformat_trades": Arg(
         '--data-format-trades',
-        help='Storage format for downloaded trades data. (default: `%(default)s`).',
+        help='Storage format for downloaded trades data. (default: `jsongz`).',
         choices=constants.AVAILABLE_DATAHANDLERS,
     ),
     "exchange": Arg(
@@ -414,6 +449,12 @@ AVAILABLE_CLI_OPTIONS = {
         action='store_true',
         default=False,
     ),
+    "ui_version": Arg(
+        '--ui-version',
+        help=('Specify a specific version of FreqUI to install. '
+              'Not specifying this installs the latest version.'),
+        type=str,
+    ),
     # Templating options
     "template": Arg(
         '--template',
@@ -552,4 +593,10 @@ AVAILABLE_CLI_OPTIONS = {
         help='Do not print epoch details header.',
         action='store_true',
     ),
+    "hyperopt_ignore_missing_space": Arg(
+        "--ignore-missing-spaces", "--ignore-unparameterized-spaces",
+        help=("Suppress errors for any requested Hyperopt spaces "
+              "that do not contain any parameters."),
+        action="store_true",
+    ),
 }
diff --git a/freqtrade/commands/data_commands.py b/freqtrade/commands/data_commands.py
index 141e85f14..e41512ccc 100644
--- a/freqtrade/commands/data_commands.py
+++ b/freqtrade/commands/data_commands.py
@@ -8,9 +8,10 @@ from freqtrade.configuration import TimeRange, setup_utils_configuration
 from freqtrade.data.converter import convert_ohlcv_format, convert_trades_format
 from freqtrade.data.history import (convert_trades_to_ohlcv, refresh_backtest_ohlcv_data,
                                     refresh_backtest_trades_data)
-from freqtrade.enums import RunMode
+from freqtrade.enums import CandleType, RunMode, TradingMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.exchange import timeframe_to_minutes
+from freqtrade.exchange.exchange import market_is_active
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.resolvers import ExchangeResolver
 
@@ -47,11 +48,13 @@ def start_download_data(args: Dict[str, Any]) -> None:
 
     # Init exchange
     exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
+    markets = [p for p, m in exchange.markets.items() if market_is_active(m)
+               or config.get('include_inactive')]
+    expanded_pairs = expand_pairlist(config['pairs'], markets)
+
     # Manual validations of relevant settings
     if not config['exchange'].get('skip_pair_validation', False):
-        exchange.validate_pairs(config['pairs'])
-    expanded_pairs = expand_pairlist(config['pairs'], list(exchange.markets))
-
+        exchange.validate_pairs(expanded_pairs)
     logger.info(f"About to download pairs: {expanded_pairs}, "
                 f"intervals: {config['timeframes']} to {config['datadir']}")
 
@@ -61,6 +64,8 @@ def start_download_data(args: Dict[str, Any]) -> None:
     try:
 
         if config.get('download_trades'):
+            if config.get('trading_mode') == 'futures':
+                raise OperationalException("Trade download not supported for futures.")
             pairs_not_available = refresh_backtest_trades_data(
                 exchange, pairs=expanded_pairs, datadir=config['datadir'],
                 timerange=timerange, new_pairs_days=config['new_pairs_days'],
@@ -78,7 +83,9 @@ def start_download_data(args: Dict[str, Any]) -> None:
                 exchange, pairs=expanded_pairs, timeframes=config['timeframes'],
                 datadir=config['datadir'], timerange=timerange,
                 new_pairs_days=config['new_pairs_days'],
-                erase=bool(config.get('erase')), data_format=config['dataformat_ohlcv'])
+                erase=bool(config.get('erase')), data_format=config['dataformat_ohlcv'],
+                trading_mode=config.get('trading_mode', 'spot'),
+            )
 
     except KeyboardInterrupt:
         sys.exit("SIGINT received, aborting ...")
@@ -89,15 +96,52 @@ def start_download_data(args: Dict[str, Any]) -> None:
                         f"on exchange {exchange.name}.")
 
 
+def start_convert_trades(args: Dict[str, Any]) -> None:
+
+    config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
+
+    timerange = TimeRange()
+
+    # Remove stake-currency to skip checks which are not relevant for datadownload
+    config['stake_currency'] = ''
+
+    if 'pairs' not in config:
+        raise OperationalException(
+            "Downloading data requires a list of pairs. "
+            "Please check the documentation on how to configure this.")
+
+    # Init exchange
+    exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
+    # Manual validations of relevant settings
+    if not config['exchange'].get('skip_pair_validation', False):
+        exchange.validate_pairs(config['pairs'])
+    expanded_pairs = expand_pairlist(config['pairs'], list(exchange.markets))
+
+    logger.info(f"About to Convert pairs: {expanded_pairs}, "
+                f"intervals: {config['timeframes']} to {config['datadir']}")
+
+    for timeframe in config['timeframes']:
+        exchange.validate_timeframes(timeframe)
+    # Convert downloaded trade data to different timeframes
+    convert_trades_to_ohlcv(
+        pairs=expanded_pairs, timeframes=config['timeframes'],
+        datadir=config['datadir'], timerange=timerange, erase=bool(config.get('erase')),
+        data_format_ohlcv=config['dataformat_ohlcv'],
+        data_format_trades=config['dataformat_trades'],
+    )
+
+
 def start_convert_data(args: Dict[str, Any], ohlcv: bool = True) -> None:
     """
     Convert data from one format to another
     """
     config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
     if ohlcv:
-        convert_ohlcv_format(config,
-                             convert_from=args['format_from'], convert_to=args['format_to'],
-                             erase=args['erase'])
+        candle_types = [CandleType.from_string(ct) for ct in config.get('candle_types', ['spot'])]
+        for candle_type in candle_types:
+            convert_ohlcv_format(config,
+                                 convert_from=args['format_from'], convert_to=args['format_to'],
+                                 erase=args['erase'], candle_type=candle_type)
     else:
         convert_trades_format(config,
                               convert_from=args['format_from'], convert_to=args['format_to'],
@@ -116,17 +160,26 @@ def start_list_data(args: Dict[str, Any]) -> None:
     from freqtrade.data.history.idatahandler import get_datahandler
     dhc = get_datahandler(config['datadir'], config['dataformat_ohlcv'])
 
-    paircombs = dhc.ohlcv_get_available_data(config['datadir'])
+    paircombs = dhc.ohlcv_get_available_data(
+        config['datadir'],
+        config.get('trading_mode', TradingMode.SPOT)
+        )
 
     if args['pairs']:
         paircombs = [comb for comb in paircombs if comb[0] in args['pairs']]
 
     print(f"Found {len(paircombs)} pair / timeframe combinations.")
     groupedpair = defaultdict(list)
-    for pair, timeframe in sorted(paircombs, key=lambda x: (x[0], timeframe_to_minutes(x[1]))):
-        groupedpair[pair].append(timeframe)
+    for pair, timeframe, candle_type in sorted(
+        paircombs,
+        key=lambda x: (x[0], timeframe_to_minutes(x[1]), x[2])
+    ):
+        groupedpair[(pair, candle_type)].append(timeframe)
 
     if groupedpair:
-        print(tabulate([(pair, ', '.join(timeframes)) for pair, timeframes in groupedpair.items()],
-                       headers=("Pair", "Timeframe"),
-                       tablefmt='psql', stralign='right'))
+        print(tabulate([
+            (pair, ', '.join(timeframes), candle_type)
+            for (pair, candle_type), timeframes in groupedpair.items()
+        ],
+            headers=("Pair", "Timeframe", "Type"),
+            tablefmt='psql', stralign='right'))
diff --git a/freqtrade/commands/deploy_commands.py b/freqtrade/commands/deploy_commands.py
index 4f9e5bbad..92c9adf66 100644
--- a/freqtrade/commands/deploy_commands.py
+++ b/freqtrade/commands/deploy_commands.py
@@ -128,7 +128,7 @@ def download_and_install_ui(dest_folder: Path, dl_url: str, version: str):
         f.write(version)
 
 
-def get_ui_download_url() -> Tuple[str, str]:
+def get_ui_download_url(version: Optional[str] = None) -> Tuple[str, str]:
     base_url = 'https://api.github.com/repos/freqtrade/frequi/'
     # Get base UI Repo path
 
@@ -136,8 +136,16 @@ def get_ui_download_url() -> Tuple[str, str]:
     resp.raise_for_status()
     r = resp.json()
 
-    latest_version = r[0]['name']
-    assets = r[0].get('assets', [])
+    if version:
+        tmp = [x for x in r if x['name'] == version]
+        if tmp:
+            latest_version = tmp[0]['name']
+            assets = tmp[0].get('assets', [])
+        else:
+            raise ValueError("UI-Version not found.")
+    else:
+        latest_version = r[0]['name']
+        assets = r[0].get('assets', [])
     dl_url = ''
     if assets and len(assets) > 0:
         dl_url = assets[0]['browser_download_url']
@@ -156,7 +164,7 @@ def start_install_ui(args: Dict[str, Any]) -> None:
 
     dest_folder = Path(__file__).parents[1] / 'rpc/api_server/ui/installed/'
     # First make sure the assets are removed.
-    dl_url, latest_version = get_ui_download_url()
+    dl_url, latest_version = get_ui_download_url(args.get('ui_version'))
 
     curr_version = read_ui_version(dest_folder)
     if curr_version == latest_version and not args.get('erase_ui_only'):
diff --git a/freqtrade/commands/hyperopt_commands.py b/freqtrade/commands/hyperopt_commands.py
index 614c4b3f5..344828282 100755
--- a/freqtrade/commands/hyperopt_commands.py
+++ b/freqtrade/commands/hyperopt_commands.py
@@ -96,7 +96,7 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None:
         if 'strategy_name' in metrics:
             strategy_name = metrics['strategy_name']
             show_backtest_result(strategy_name, metrics,
-                                 metrics['stake_currency'])
+                                 metrics['stake_currency'], config.get('backtest_breakdown', []))
 
             HyperoptTools.try_export_params(config, strategy_name, val)
 
diff --git a/freqtrade/commands/list_commands.py b/freqtrade/commands/list_commands.py
index 38fb098a0..c4bd0bf4d 100644
--- a/freqtrade/commands/list_commands.py
+++ b/freqtrade/commands/list_commands.py
@@ -131,7 +131,7 @@ def start_list_markets(args: Dict[str, Any], pairs_only: bool = False) -> None:
     try:
         pairs = exchange.get_markets(base_currencies=base_currencies,
                                      quote_currencies=quote_currencies,
-                                     pairs_only=pairs_only,
+                                     tradable_only=pairs_only,
                                      active_only=active_only)
         # Sort the pairs/markets by symbol
         pairs = dict(sorted(pairs.items()))
@@ -151,15 +151,19 @@ def start_list_markets(args: Dict[str, Any], pairs_only: bool = False) -> None:
                         if quote_currencies else ""))
 
         headers = ["Id", "Symbol", "Base", "Quote", "Active",
-                   *(['Is pair'] if not pairs_only else [])]
+                   "Spot", "Margin", "Future", "Leverage"]
 
-        tabular_data = []
-        for _, v in pairs.items():
-            tabular_data.append({'Id': v['id'], 'Symbol': v['symbol'],
-                                 'Base': v['base'], 'Quote': v['quote'],
-                                 'Active': market_is_active(v),
-                                 **({'Is pair': exchange.market_is_tradable(v)}
-                                    if not pairs_only else {})})
+        tabular_data = [{
+                'Id': v['id'],
+                'Symbol': v['symbol'],
+                'Base': v['base'],
+                'Quote': v['quote'],
+                'Active': market_is_active(v),
+                'Spot': 'Spot' if exchange.market_is_spot(v) else '',
+                'Margin': 'Margin' if exchange.market_is_margin(v) else '',
+                'Future': 'Future' if exchange.market_is_future(v) else '',
+                'Leverage': exchange.get_max_leverage(v['symbol'], 20)
+            } for _, v in pairs.items()]
 
         if (args.get('print_one_column', False) or
                 args.get('list_pairs_print_json', False) or
diff --git a/freqtrade/commands/optimize_commands.py b/freqtrade/commands/optimize_commands.py
index 08174bde6..1bfd384fc 100644
--- a/freqtrade/commands/optimize_commands.py
+++ b/freqtrade/commands/optimize_commands.py
@@ -25,12 +25,16 @@ def setup_optimize_configuration(args: Dict[str, Any], method: RunMode) -> Dict[
         RunMode.HYPEROPT: 'hyperoptimization',
     }
     if method in no_unlimited_runmodes.keys():
+        wallet_size = config['dry_run_wallet'] * config['tradable_balance_ratio']
+        # tradable_balance_ratio
         if (config['stake_amount'] != constants.UNLIMITED_STAKE_AMOUNT
-                and config['stake_amount'] > config['dry_run_wallet']):
-            wallet = round_coin_value(config['dry_run_wallet'], config['stake_currency'])
+                and config['stake_amount'] > wallet_size):
+            wallet = round_coin_value(wallet_size, config['stake_currency'])
             stake = round_coin_value(config['stake_amount'], config['stake_currency'])
-            raise OperationalException(f"Starting balance ({wallet}) "
-                                       f"is smaller than stake_amount {stake}.")
+            raise OperationalException(
+                f"Starting balance ({wallet}) is smaller than stake_amount {stake}. "
+                f"Wallet is calculated as `dry_run_wallet * tradable_balance_ratio`."
+                )
 
     return config
 
@@ -54,6 +58,22 @@ def start_backtesting(args: Dict[str, Any]) -> None:
     backtesting.start()
 
 
+def start_backtesting_show(args: Dict[str, Any]) -> None:
+    """
+    Show previous backtest result
+    """
+
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    from freqtrade.data.btanalysis import load_backtest_stats
+    from freqtrade.optimize.optimize_reports import show_backtest_results, show_sorted_pairlist
+
+    results = load_backtest_stats(config['exportfilename'])
+
+    show_backtest_results(config, results)
+    show_sorted_pairlist(config, results)
+
+
 def start_hyperopt(args: Dict[str, Any]) -> None:
     """
     Start hyperopt script
diff --git a/freqtrade/configuration/PeriodicCache.py b/freqtrade/configuration/PeriodicCache.py
index 25c0c47f3..1a535440d 100644
--- a/freqtrade/configuration/PeriodicCache.py
+++ b/freqtrade/configuration/PeriodicCache.py
@@ -1,6 +1,6 @@
 from datetime import datetime, timezone
 
-from cachetools.ttl import TTLCache
+from cachetools import TTLCache
 
 
 class PeriodicCache(TTLCache):
@@ -16,4 +16,4 @@ class PeriodicCache(TTLCache):
             return ts - offset
 
         # Init with smlight offset
-        super().__init__(maxsize=maxsize, ttl=ttl-1e-5, timer=local_timer, getsizeof=getsizeof)
+        super().__init__(maxsize=maxsize, ttl=ttl - 1e-5, timer=local_timer, getsizeof=getsizeof)
diff --git a/freqtrade/configuration/config_validation.py b/freqtrade/configuration/config_validation.py
index 85ff4408f..6e4a4b0ef 100644
--- a/freqtrade/configuration/config_validation.py
+++ b/freqtrade/configuration/config_validation.py
@@ -6,7 +6,8 @@ from jsonschema import Draft4Validator, validators
 from jsonschema.exceptions import ValidationError, best_match
 
 from freqtrade import constants
-from freqtrade.enums import RunMode
+from freqtrade.configuration.deprecated_settings import process_deprecated_setting
+from freqtrade.enums import RunMode, TradingMode
 from freqtrade.exceptions import OperationalException
 
 
@@ -80,6 +81,7 @@ def validate_config_consistency(conf: Dict[str, Any]) -> None:
     _validate_protections(conf)
     _validate_unlimited_amount(conf)
     _validate_ask_orderbook(conf)
+    validate_migrated_strategy_settings(conf)
 
     # validate configuration before returning
     logger.info('Validating configuration ...')
@@ -92,8 +94,8 @@ def _validate_unlimited_amount(conf: Dict[str, Any]) -> None:
     :raise: OperationalException if config validation failed
     """
     if (not conf.get('edge', {}).get('enabled')
-       and conf.get('max_open_trades') == float('inf')
-       and conf.get('stake_amount') == constants.UNLIMITED_STAKE_AMOUNT):
+        and conf.get('max_open_trades') == float('inf')
+            and conf.get('stake_amount') == constants.UNLIMITED_STAKE_AMOUNT):
         raise OperationalException("`max_open_trades` and `stake_amount` cannot both be unlimited.")
 
 
@@ -101,13 +103,15 @@ def _validate_price_config(conf: Dict[str, Any]) -> None:
     """
     When using market orders, price sides must be using the "other" side of the price
     """
-    if (conf.get('order_types', {}).get('buy') == 'market'
-            and conf.get('bid_strategy', {}).get('price_side') != 'ask'):
-        raise OperationalException('Market buy orders require bid_strategy.price_side = "ask".')
+    # TODO: The below could be an enforced setting when using market orders
+    if (conf.get('order_types', {}).get('entry') == 'market'
+            and conf.get('entry_pricing', {}).get('price_side') not in ('ask', 'other')):
+        raise OperationalException(
+            'Market entry orders require entry_pricing.price_side = "other".')
 
-    if (conf.get('order_types', {}).get('sell') == 'market'
-            and conf.get('ask_strategy', {}).get('price_side') != 'bid'):
-        raise OperationalException('Market sell orders require ask_strategy.price_side = "bid".')
+    if (conf.get('order_types', {}).get('exit') == 'market'
+            and conf.get('exit_pricing', {}).get('price_side') not in ('bid', 'other')):
+        raise OperationalException('Market exit orders require exit_pricing.price_side = "other".')
 
 
 def _validate_trailing_stoploss(conf: Dict[str, Any]) -> None:
@@ -150,9 +154,9 @@ def _validate_edge(conf: Dict[str, Any]) -> None:
     if not conf.get('edge', {}).get('enabled'):
         return
 
-    if not conf.get('use_sell_signal', True):
+    if not conf.get('use_exit_signal', True):
         raise OperationalException(
-            "Edge requires `use_sell_signal` to be True, otherwise no sells will happen."
+            "Edge requires `use_exit_signal` to be True, otherwise no sells will happen."
         )
 
 
@@ -190,13 +194,13 @@ def _validate_protections(conf: Dict[str, Any]) -> None:
 
 
 def _validate_ask_orderbook(conf: Dict[str, Any]) -> None:
-    ask_strategy = conf.get('ask_strategy', {})
+    ask_strategy = conf.get('exit_pricing', {})
     ob_min = ask_strategy.get('order_book_min')
     ob_max = ask_strategy.get('order_book_max')
     if ob_min is not None and ob_max is not None and ask_strategy.get('use_order_book'):
         if ob_min != ob_max:
             raise OperationalException(
-                "Using order_book_max != order_book_min in ask_strategy is no longer supported."
+                "Using order_book_max != order_book_min in exit_pricing is no longer supported."
                 "Please pick one value and use `order_book_top` in the future."
             )
         else:
@@ -205,5 +209,121 @@ def _validate_ask_orderbook(conf: Dict[str, Any]) -> None:
             logger.warning(
                 "DEPRECATED: "
                 "Please use `order_book_top` instead of `order_book_min` and `order_book_max` "
-                "for your `ask_strategy` configuration."
+                "for your `exit_pricing` configuration."
             )
+
+
+def validate_migrated_strategy_settings(conf: Dict[str, Any]) -> None:
+
+    _validate_time_in_force(conf)
+    _validate_order_types(conf)
+    _validate_unfilledtimeout(conf)
+    _validate_pricing_rules(conf)
+    _strategy_settings(conf)
+
+
+def _validate_time_in_force(conf: Dict[str, Any]) -> None:
+
+    time_in_force = conf.get('order_time_in_force', {})
+    if 'buy' in time_in_force or 'sell' in time_in_force:
+        if conf.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
+            raise OperationalException(
+                "Please migrate your time_in_force settings to use 'entry' and 'exit'.")
+        else:
+            logger.warning(
+                "DEPRECATED: Using 'buy' and 'sell' for time_in_force is deprecated."
+                "Please migrate your time_in_force settings to use 'entry' and 'exit'."
+            )
+            process_deprecated_setting(
+                conf, 'order_time_in_force', 'buy', 'order_time_in_force', 'entry')
+
+            process_deprecated_setting(
+                conf, 'order_time_in_force', 'sell', 'order_time_in_force', 'exit')
+
+
+def _validate_order_types(conf: Dict[str, Any]) -> None:
+
+    order_types = conf.get('order_types', {})
+    old_order_types = ['buy', 'sell', 'emergencysell', 'forcebuy',
+                       'forcesell', 'emergencyexit', 'forceexit', 'forceentry']
+    if any(x in order_types for x in old_order_types):
+        if conf.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
+            raise OperationalException(
+                "Please migrate your order_types settings to use the new wording.")
+        else:
+            logger.warning(
+                "DEPRECATED: Using 'buy' and 'sell' for order_types is deprecated."
+                "Please migrate your order_types settings to use 'entry' and 'exit' wording."
+            )
+            for o, n in [
+                ('buy', 'entry'),
+                ('sell', 'exit'),
+                ('emergencysell', 'emergency_exit'),
+                ('forcesell', 'force_exit'),
+                ('forcebuy', 'force_entry'),
+                ('emergencyexit', 'emergency_exit'),
+                ('forceexit', 'force_exit'),
+                ('forceentry', 'force_entry'),
+            ]:
+
+                process_deprecated_setting(conf, 'order_types', o, 'order_types', n)
+
+
+def _validate_unfilledtimeout(conf: Dict[str, Any]) -> None:
+    unfilledtimeout = conf.get('unfilledtimeout', {})
+    if any(x in unfilledtimeout for x in ['buy', 'sell']):
+        if conf.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
+            raise OperationalException(
+                "Please migrate your unfilledtimeout settings to use the new wording.")
+        else:
+
+            logger.warning(
+                "DEPRECATED: Using 'buy' and 'sell' for unfilledtimeout is deprecated."
+                "Please migrate your unfilledtimeout settings to use 'entry' and 'exit' wording."
+            )
+            for o, n in [
+                ('buy', 'entry'),
+                ('sell', 'exit'),
+            ]:
+
+                process_deprecated_setting(conf, 'unfilledtimeout', o, 'unfilledtimeout', n)
+
+
+def _validate_pricing_rules(conf: Dict[str, Any]) -> None:
+
+    if conf.get('ask_strategy') or conf.get('bid_strategy'):
+        if conf.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
+            raise OperationalException(
+                "Please migrate your pricing settings to use the new wording.")
+        else:
+
+            logger.warning(
+                "DEPRECATED: Using 'ask_strategy' and 'bid_strategy' is deprecated."
+                "Please migrate your settings to use 'entry_pricing' and 'exit_pricing'."
+            )
+            conf['entry_pricing'] = {}
+            for obj in list(conf.get('bid_strategy', {}).keys()):
+                if obj == 'ask_last_balance':
+                    process_deprecated_setting(conf, 'bid_strategy', obj,
+                                               'entry_pricing', 'price_last_balance')
+                else:
+                    process_deprecated_setting(conf, 'bid_strategy', obj, 'entry_pricing', obj)
+            del conf['bid_strategy']
+
+            conf['exit_pricing'] = {}
+            for obj in list(conf.get('ask_strategy', {}).keys()):
+                if obj == 'bid_last_balance':
+                    process_deprecated_setting(conf, 'ask_strategy', obj,
+                                               'exit_pricing', 'price_last_balance')
+                else:
+                    process_deprecated_setting(conf, 'ask_strategy', obj, 'exit_pricing', obj)
+            del conf['ask_strategy']
+
+
+def _strategy_settings(conf: Dict[str, Any]) -> None:
+
+    process_deprecated_setting(conf, None, 'use_sell_signal', None, 'use_exit_signal')
+    process_deprecated_setting(conf, None, 'sell_profit_only', None, 'exit_profit_only')
+    process_deprecated_setting(conf, None, 'sell_profit_offset', None, 'exit_profit_offset')
+    process_deprecated_setting(conf, None, 'ignore_roi_if_buy_signal',
+                               None, 'ignore_roi_if_entry_signal')
diff --git a/freqtrade/configuration/configuration.py b/freqtrade/configuration/configuration.py
index 94b108f2b..331901920 100644
--- a/freqtrade/configuration/configuration.py
+++ b/freqtrade/configuration/configuration.py
@@ -12,8 +12,8 @@ from freqtrade.configuration.check_exchange import check_exchange
 from freqtrade.configuration.deprecated_settings import process_temporary_deprecated_settings
 from freqtrade.configuration.directory_operations import create_datadir, create_userdata_dir
 from freqtrade.configuration.environment_vars import enironment_vars_to_dict
-from freqtrade.configuration.load_config import load_config_file, load_file
-from freqtrade.enums import NON_UTIL_MODES, TRADING_MODES, RunMode
+from freqtrade.configuration.load_config import load_file, load_from_files
+from freqtrade.enums import NON_UTIL_MODES, TRADING_MODES, CandleType, RunMode, TradingMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.loggers import setup_logging
 from freqtrade.misc import deep_merge_dicts, parse_db_uri_for_logging
@@ -55,47 +55,28 @@ class Configuration:
         :param files: List of file paths
         :return: configuration dictionary
         """
+        # Keep this method as staticmethod, so it can be used from interactive environments
         c = Configuration({'config': files}, RunMode.OTHER)
         return c.get_config()
 
-    def load_from_files(self, files: List[str]) -> Dict[str, Any]:
-
-        # Keep this method as staticmethod, so it can be used from interactive environments
-        config: Dict[str, Any] = {}
-
-        if not files:
-            return deepcopy(constants.MINIMAL_CONFIG)
-
-        # We expect here a list of config filenames
-        for path in files:
-            logger.info(f'Using config: {path} ...')
-
-            # Merge config options, overwriting old values
-            config = deep_merge_dicts(load_config_file(path), config)
-
-        # Load environment variables
-        env_data = enironment_vars_to_dict()
-        config = deep_merge_dicts(env_data, config)
-
-        config['config_files'] = files
-        # Normalize config
-        if 'internals' not in config:
-            config['internals'] = {}
-        if 'ask_strategy' not in config:
-            config['ask_strategy'] = {}
-
-        if 'pairlists' not in config:
-            config['pairlists'] = []
-
-        return config
-
     def load_config(self) -> Dict[str, Any]:
         """
         Extract information for sys.argv and load the bot configuration
         :return: Configuration dictionary
         """
         # Load all configs
-        config: Dict[str, Any] = self.load_from_files(self.args.get("config", []))
+        config: Dict[str, Any] = load_from_files(self.args.get("config", []))
+
+        # Load environment variables
+        env_data = enironment_vars_to_dict()
+        config = deep_merge_dicts(env_data, config)
+
+        # Normalize config
+        if 'internals' not in config:
+            config['internals'] = {}
+
+        if 'pairlists' not in config:
+            config['pairlists'] = []
 
         # Keep a copy of the original configuration file
         config['original_config'] = deepcopy(config)
@@ -166,8 +147,8 @@ class Configuration:
             config.update({'db_url': self.args['db_url']})
             logger.info('Parameter --db-url detected ...')
 
-        if config.get('forcebuy_enable', False):
-            logger.warning('`forcebuy` RPC message enabled.')
+        if config.get('force_entry_enable', False):
+            logger.warning('`force_entry_enable` RPC message enabled.')
 
         # Support for sd_notify
         if 'sd_notify' in self.args and self.args['sd_notify']:
@@ -245,6 +226,10 @@ class Configuration:
         self._args_to_config(config, argname='timeframe_detail',
                              logstring='Parameter --timeframe-detail detected, '
                              'using {} for intra-candle backtesting ...')
+
+        self._args_to_config(config, argname='backtest_show_pair_list',
+                             logstring='Parameter --show-pair-list detected.')
+
         self._args_to_config(config, argname='stake_amount',
                              logstring='Parameter --stake-amount detected, '
                              'overriding stake_amount to: {} ...')
@@ -269,8 +254,15 @@ class Configuration:
         self._args_to_config(config, argname='export',
                              logstring='Parameter --export detected: {} ...')
 
+        self._args_to_config(config, argname='backtest_breakdown',
+                             logstring='Parameter --breakdown detected ...')
+
+        self._args_to_config(config, argname='backtest_cache',
+                             logstring='Parameter --cache={} detected ...')
+
         self._args_to_config(config, argname='disableparamexport',
                              logstring='Parameter --disableparamexport detected: {} ...')
+
         # Edge section:
         if 'stoploss_range' in self.args and self.args["stoploss_range"]:
             txt_range = eval(self.args["stoploss_range"])
@@ -369,6 +361,9 @@ class Configuration:
         self._args_to_config(config, argname='hyperopt_show_no_header',
                              logstring='Parameter --no-header detected: {}')
 
+        self._args_to_config(config, argname="hyperopt_ignore_missing_space",
+                             logstring="Paramter --ignore-missing-space detected: {}")
+
     def _process_plot_options(self, config: Dict[str, Any]) -> None:
 
         self._args_to_config(config, argname='pairs',
@@ -404,6 +399,9 @@ class Configuration:
         self._args_to_config(config, argname='days',
                              logstring='Detected --days: {}')
 
+        self._args_to_config(config, argname='include_inactive',
+                             logstring='Detected --include-inactive-pairs: {}')
+
         self._args_to_config(config, argname='download_trades',
                              logstring='Detected --dl-trades: {}')
 
@@ -414,9 +412,15 @@ class Configuration:
                              logstring='Using "{}" to store trades data.')
 
     def _process_data_options(self, config: Dict[str, Any]) -> None:
-
         self._args_to_config(config, argname='new_pairs_days',
                              logstring='Detected --new-pairs-days: {}')
+        self._args_to_config(config, argname='trading_mode',
+                             logstring='Detected --trading-mode: {}')
+        config['candle_type_def'] = CandleType.get_default(
+            config.get('trading_mode', 'spot') or 'spot')
+        config['trading_mode'] = TradingMode(config.get('trading_mode', 'spot') or 'spot')
+        self._args_to_config(config, argname='candle_types',
+                             logstring='Detected --candle-types: {}')
 
     def _process_runmode(self, config: Dict[str, Any]) -> None:
 
diff --git a/freqtrade/configuration/deprecated_settings.py b/freqtrade/configuration/deprecated_settings.py
index 5efe26bd2..70d29e2bd 100644
--- a/freqtrade/configuration/deprecated_settings.py
+++ b/freqtrade/configuration/deprecated_settings.py
@@ -12,14 +12,15 @@ logger = logging.getLogger(__name__)
 
 
 def check_conflicting_settings(config: Dict[str, Any],
-                               section_old: str, name_old: str,
+                               section_old: Optional[str], name_old: str,
                                section_new: Optional[str], name_new: str) -> None:
     section_new_config = config.get(section_new, {}) if section_new else config
-    section_old_config = config.get(section_old, {})
+    section_old_config = config.get(section_old, {}) if section_old else config
     if name_new in section_new_config and name_old in section_old_config:
         new_name = f"{section_new}.{name_new}" if section_new else f"{name_new}"
+        old_name = f"{section_old}.{name_old}" if section_old else f"{name_old}"
         raise OperationalException(
-            f"Conflicting settings `{new_name}` and `{section_old}.{name_old}` "
+            f"Conflicting settings `{new_name}` and `{old_name}` "
             "(DEPRECATED) detected in the configuration file. "
             "This deprecated setting will be removed in the next versions of Freqtrade. "
             f"Please delete it from your configuration and use the `{new_name}` "
@@ -47,23 +48,25 @@ def process_removed_setting(config: Dict[str, Any],
 
 
 def process_deprecated_setting(config: Dict[str, Any],
-                               section_old: str, name_old: str,
+                               section_old: Optional[str], name_old: str,
                                section_new: Optional[str], name_new: str
                                ) -> None:
     check_conflicting_settings(config, section_old, name_old, section_new, name_new)
-    section_old_config = config.get(section_old, {})
+    section_old_config = config.get(section_old, {}) if section_old else config
 
     if name_old in section_old_config:
+        section_1 = f"{section_old}.{name_old}" if section_old else f"{name_old}"
         section_2 = f"{section_new}.{name_new}" if section_new else f"{name_new}"
         logger.warning(
             "DEPRECATED: "
-            f"The `{section_old}.{name_old}` setting is deprecated and "
+            f"The `{section_1}` setting is deprecated and "
             "will be removed in the next versions of Freqtrade. "
             f"Please use the `{section_2}` setting in your configuration instead."
         )
 
         section_new_config = config.get(section_new, {}) if section_new else config
         section_new_config[name_new] = section_old_config[name_old]
+        del section_old_config[name_old]
 
 
 def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
@@ -71,25 +74,51 @@ def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
     # Kept for future deprecated / moved settings
     # check_conflicting_settings(config, 'ask_strategy', 'use_sell_signal',
     #                            'experimental', 'use_sell_signal')
-    process_deprecated_setting(config, 'ask_strategy', 'use_sell_signal',
-                               None, 'use_sell_signal')
-    process_deprecated_setting(config, 'ask_strategy', 'sell_profit_only',
-                               None, 'sell_profit_only')
-    process_deprecated_setting(config, 'ask_strategy', 'sell_profit_offset',
-                               None, 'sell_profit_offset')
-    process_deprecated_setting(config, 'ask_strategy', 'ignore_roi_if_buy_signal',
-                               None, 'ignore_roi_if_buy_signal')
+
     process_deprecated_setting(config, 'ask_strategy', 'ignore_buying_expired_candle_after',
                                None, 'ignore_buying_expired_candle_after')
 
-    # Legacy way - having them in experimental ...
-    process_removed_setting(config, 'experimental', 'use_sell_signal',
-                            None, 'use_sell_signal')
-    process_removed_setting(config, 'experimental', 'sell_profit_only',
-                            None, 'sell_profit_only')
-    process_removed_setting(config, 'experimental', 'ignore_roi_if_buy_signal',
-                            None, 'ignore_roi_if_buy_signal')
+    process_deprecated_setting(config, None, 'forcebuy_enable', None, 'force_entry_enable')
 
+    # New settings
+    if config.get('telegram'):
+        process_deprecated_setting(config['telegram'], 'notification_settings', 'sell',
+                                   'notification_settings', 'exit')
+        process_deprecated_setting(config['telegram'], 'notification_settings', 'sell_fill',
+                                   'notification_settings', 'exit_fill')
+        process_deprecated_setting(config['telegram'], 'notification_settings', 'sell_cancel',
+                                   'notification_settings', 'exit_cancel')
+        process_deprecated_setting(config['telegram'], 'notification_settings', 'buy',
+                                   'notification_settings', 'entry')
+        process_deprecated_setting(config['telegram'], 'notification_settings', 'buy_fill',
+                                   'notification_settings', 'entry_fill')
+        process_deprecated_setting(config['telegram'], 'notification_settings', 'buy_cancel',
+                                   'notification_settings', 'entry_cancel')
+    if config.get('webhook'):
+        process_deprecated_setting(config, 'webhook', 'webhookbuy', 'webhook', 'webhookentry')
+        process_deprecated_setting(config, 'webhook', 'webhookbuycancel',
+                                   'webhook', 'webhookentrycancel')
+        process_deprecated_setting(config, 'webhook', 'webhookbuyfill',
+                                   'webhook', 'webhookentryfill')
+        process_deprecated_setting(config, 'webhook', 'webhooksell', 'webhook', 'webhookexit')
+        process_deprecated_setting(config, 'webhook', 'webhooksellcancel',
+                                   'webhook', 'webhookexitcancel')
+        process_deprecated_setting(config, 'webhook', 'webhooksellfill',
+                                   'webhook', 'webhookexitfill')
+
+    # Legacy way - having them in experimental ...
+
+    process_removed_setting(config, 'experimental', 'use_sell_signal', None, 'use_exit_signal')
+    process_removed_setting(config, 'experimental', 'sell_profit_only', None, 'exit_profit_only')
+    process_removed_setting(config, 'experimental', 'ignore_roi_if_buy_signal',
+                            None, 'ignore_roi_if_entry_signal')
+
+    process_removed_setting(config, 'ask_strategy', 'use_sell_signal', None, 'exit_sell_signal')
+    process_removed_setting(config, 'ask_strategy', 'sell_profit_only', None, 'exit_profit_only')
+    process_removed_setting(config, 'ask_strategy', 'sell_profit_offset',
+                            None, 'exit_profit_offset')
+    process_removed_setting(config, 'ask_strategy', 'ignore_roi_if_buy_signal',
+                            None, 'ignore_roi_if_entry_signal')
     if (config.get('edge', {}).get('enabled', False)
        and 'capital_available_percentage' in config.get('edge', {})):
         raise OperationalException(
@@ -100,16 +129,11 @@ def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
             "from the edge configuration."
         )
     if 'ticker_interval' in config:
-        logger.warning(
-            "DEPRECATED: "
+
+        raise OperationalException(
+            "DEPRECATED: 'ticker_interval' detected. "
             "Please use 'timeframe' instead of 'ticker_interval."
         )
-        if 'timeframe' in config:
-            raise OperationalException(
-                "Both 'timeframe' and 'ticker_interval' detected."
-                "Please remove 'ticker_interval' from your configuration to continue operating."
-            )
-        config['timeframe'] = config['ticker_interval']
 
     if 'protections' in config:
         logger.warning("DEPRECATED: Setting 'protections' in the configuration is deprecated.")
diff --git a/freqtrade/configuration/environment_vars.py b/freqtrade/configuration/environment_vars.py
index 4c190ed04..473758fe1 100644
--- a/freqtrade/configuration/environment_vars.py
+++ b/freqtrade/configuration/environment_vars.py
@@ -32,6 +32,7 @@ def flat_vars_to_nested_dict(env_dict: Dict[str, Any], prefix: str) -> Dict[str,
     :param prefix: Prefix to consider (usually FREQTRADE__)
     :return: Nested dict based on available and relevant variables.
     """
+    no_convert = ['CHAT_ID']
     relevant_vars: Dict[str, Any] = {}
 
     for env_var, val in sorted(env_dict.items()):
@@ -39,9 +40,9 @@ def flat_vars_to_nested_dict(env_dict: Dict[str, Any], prefix: str) -> Dict[str,
             logger.info(f"Loading variable '{env_var}'")
             key = env_var.replace(prefix, '')
             for k in reversed(key.split('__')):
-                val = {k.lower(): get_var_typed(val) if type(val) != dict else val}
+                val = {k.lower(): get_var_typed(val)
+                       if type(val) != dict and k not in no_convert else val}
             relevant_vars = deep_merge_dicts(val, relevant_vars)
-
     return relevant_vars
 
 
diff --git a/freqtrade/configuration/load_config.py b/freqtrade/configuration/load_config.py
index 27190d259..3fcbd1f2f 100644
--- a/freqtrade/configuration/load_config.py
+++ b/freqtrade/configuration/load_config.py
@@ -4,12 +4,15 @@ This module contain functions to load the configuration file
 import logging
 import re
 import sys
+from copy import deepcopy
 from pathlib import Path
-from typing import Any, Dict
+from typing import Any, Dict, List
 
 import rapidjson
 
+from freqtrade.constants import MINIMAL_CONFIG
 from freqtrade.exceptions import OperationalException
+from freqtrade.misc import deep_merge_dicts
 
 
 logger = logging.getLogger(__name__)
@@ -28,7 +31,7 @@ def log_config_error_range(path: str, errmsg: str) -> str:
             offset = int(offsetlist[0])
             text = Path(path).read_text()
             # Fetch an offset of 80 characters around the error line
-            subtext = text[offset-min(80, offset):offset+80]
+            subtext = text[offset - min(80, offset):offset + 80]
             segments = subtext.split('\n')
             if len(segments) > 3:
                 # Remove first and last lines, to avoid odd truncations
@@ -70,3 +73,43 @@ def load_config_file(path: str) -> Dict[str, Any]:
         )
 
     return config
+
+
+def load_from_files(files: List[str], base_path: Path = None, level: int = 0) -> Dict[str, Any]:
+    """
+    Recursively load configuration files if specified.
+    Sub-files are assumed to be relative to the initial config.
+    """
+    config: Dict[str, Any] = {}
+    if level > 5:
+        raise OperationalException("Config loop detected.")
+
+    if not files:
+        return deepcopy(MINIMAL_CONFIG)
+    files_loaded = []
+    # We expect here a list of config filenames
+    for filename in files:
+        logger.info(f'Using config: {filename} ...')
+        if filename == '-':
+            # Immediately load stdin and return
+            return load_config_file(filename)
+        file = Path(filename)
+        if base_path:
+            # Prepend basepath to allow for relative assignments
+            file = base_path / file
+
+        config_tmp = load_config_file(str(file))
+        if 'add_config_files' in config_tmp:
+            config_sub = load_from_files(
+                config_tmp['add_config_files'], file.resolve().parent, level + 1)
+            files_loaded.extend(config_sub.get('config_files', []))
+            config_tmp = deep_merge_dicts(config_tmp, config_sub)
+
+        files_loaded.insert(0, str(file))
+
+        # Merge config options, overwriting prior values
+        config = deep_merge_dicts(config_tmp, config)
+
+    config['config_files'] = files_loaded
+
+    return config
diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index fca319a0f..c6a2ab5d3 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -3,7 +3,9 @@
 """
 bot constants
 """
-from typing import List, Tuple
+from typing import List, Literal, Tuple
+
+from freqtrade.enums import CandleType
 
 
 DEFAULT_CONFIG = 'config.json'
@@ -17,20 +19,25 @@ DEFAULT_DB_PROD_URL = 'sqlite:///tradesv3.sqlite'
 DEFAULT_DB_DRYRUN_URL = 'sqlite:///tradesv3.dryrun.sqlite'
 UNLIMITED_STAKE_AMOUNT = 'unlimited'
 DEFAULT_AMOUNT_RESERVE_PERCENT = 0.05
-REQUIRED_ORDERTIF = ['buy', 'sell']
-REQUIRED_ORDERTYPES = ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']
-ORDERBOOK_SIDES = ['ask', 'bid']
+REQUIRED_ORDERTIF = ['entry', 'exit']
+REQUIRED_ORDERTYPES = ['entry', 'exit', 'stoploss', 'stoploss_on_exchange']
+PRICING_SIDES = ['ask', 'bid', 'same', 'other']
 ORDERTYPE_POSSIBILITIES = ['limit', 'market']
 ORDERTIF_POSSIBILITIES = ['gtc', 'fok', 'ioc']
 HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
                          'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily',
-                         'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily']
+                         'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily',
+                         'CalmarHyperOptLoss',
+                         'MaxDrawDownHyperOptLoss', 'ProfitDrawDownHyperOptLoss']
 AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
                        'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
                        'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
                        'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter']
 AVAILABLE_PROTECTIONS = ['CooldownPeriod', 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard']
 AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5']
+BACKTEST_BREAKDOWNS = ['day', 'week', 'month']
+BACKTEST_CACHE_AGE = ['none', 'day', 'week', 'month']
+BACKTEST_CACHE_DEFAULT = 'day'
 DRY_RUN_WALLET = 1000
 DATETIME_PRINT_FORMAT = '%Y-%m-%d %H:%M:%S'
 MATH_CLOSE_PREC = 1e-14  # Precision used for float comparisons
@@ -38,6 +45,8 @@ DEFAULT_DATAFRAME_COLUMNS = ['date', 'open', 'high', 'low', 'close', 'volume']
 # Don't modify sequence of DEFAULT_TRADES_COLUMNS
 # it has wide consequences for stored trades files
 DEFAULT_TRADES_COLUMNS = ['timestamp', 'id', 'type', 'side', 'price', 'amount', 'cost']
+TRADING_MODES = ['spot', 'margin', 'futures']
+MARGIN_MODES = ['cross', 'isolated', '']
 
 LAST_BT_RESULT_FN = '.last_result.json'
 FTHYPT_FILEVERSION = 'fthypt_fileversion'
@@ -47,11 +56,12 @@ USERPATH_STRATEGIES = 'strategies'
 USERPATH_NOTEBOOKS = 'notebooks'
 
 TELEGRAM_SETTING_OPTIONS = ['on', 'off', 'silent']
+WEBHOOK_FORMAT_OPTIONS = ['form', 'json', 'raw']
+
 ENV_VAR_PREFIX = 'FREQTRADE__'
 
 NON_OPEN_EXCHANGE_STATES = ('cancelled', 'canceled', 'closed', 'expired')
 
-
 # Define decimals per coin for outputs
 # Only used for outputs.
 DECIMAL_PER_COIN_FALLBACK = 3  # Should be low to avoid listing all possible FIAT's
@@ -65,7 +75,6 @@ DUST_PER_COIN = {
     'ETH': 0.01
 }
 
-
 # Source files with destination directories within user-directory
 USER_DATA_FILES = {
     'sample_strategy.py': USERPATH_STRATEGIES,
@@ -77,20 +86,19 @@ SUPPORTED_FIAT = [
     "AUD", "BRL", "CAD", "CHF", "CLP", "CNY", "CZK", "DKK",
     "EUR", "GBP", "HKD", "HUF", "IDR", "ILS", "INR", "JPY",
     "KRW", "MXN", "MYR", "NOK", "NZD", "PHP", "PKR", "PLN",
-    "RUB", "SEK", "SGD", "THB", "TRY", "TWD", "ZAR", "USD",
-    "BTC", "ETH", "XRP", "LTC", "BCH"
+    "RUB", "UAH", "SEK", "SGD", "THB", "TRY", "TWD", "ZAR",
+    "USD", "BTC", "ETH", "XRP", "LTC", "BCH"
 ]
 
 MINIMAL_CONFIG = {
-    'stake_currency': '',
-    'dry_run': True,
-    'exchange': {
-        'name': '',
-        'key': '',
-        'secret': '',
-        'pair_whitelist': [],
-        'ccxt_async_config': {
-            'enableRateLimit': True,
+    "stake_currency": "",
+    "dry_run": True,
+    "exchange": {
+        "name": "",
+        "key": "",
+        "secret": "",
+        "pair_whitelist": [],
+        "ccxt_async_config": {
         }
     }
 }
@@ -135,35 +143,43 @@ CONF_SCHEMA = {
             'minProperties': 1
         },
         'amount_reserve_percent': {'type': 'number', 'minimum': 0.0, 'maximum': 0.5},
-        'stoploss': {'type': 'number', 'maximum': 0, 'exclusiveMaximum': True},
+        'stoploss': {'type': 'number', 'maximum': 0, 'exclusiveMaximum': True, 'minimum': -1},
         'trailing_stop': {'type': 'boolean'},
         'trailing_stop_positive': {'type': 'number', 'minimum': 0, 'maximum': 1},
         'trailing_stop_positive_offset': {'type': 'number', 'minimum': 0, 'maximum': 1},
         'trailing_only_offset_is_reached': {'type': 'boolean'},
-        'use_sell_signal': {'type': 'boolean'},
-        'sell_profit_only': {'type': 'boolean'},
-        'sell_profit_offset': {'type': 'number'},
-        'ignore_roi_if_buy_signal': {'type': 'boolean'},
+        'use_exit_signal': {'type': 'boolean'},
+        'exit_profit_only': {'type': 'boolean'},
+        'exit_profit_offset': {'type': 'number'},
+        'ignore_roi_if_entry_signal': {'type': 'boolean'},
         'ignore_buying_expired_candle_after': {'type': 'number'},
+        'trading_mode': {'type': 'string', 'enum': TRADING_MODES},
+        'margin_mode': {'type': 'string', 'enum': MARGIN_MODES},
+        'liquidation_buffer': {'type': 'number', 'minimum': 0.0, 'maximum': 0.99},
+        'backtest_breakdown': {
+            'type': 'array',
+            'items': {'type': 'string', 'enum': BACKTEST_BREAKDOWNS}
+        },
         'bot_name': {'type': 'string'},
         'unfilledtimeout': {
             'type': 'object',
             'properties': {
-                'buy': {'type': 'number', 'minimum': 1},
-                'sell': {'type': 'number', 'minimum': 1},
+                'entry': {'type': 'number', 'minimum': 1},
+                'exit': {'type': 'number', 'minimum': 1},
+                'exit_timeout_count': {'type': 'number', 'minimum': 0, 'default': 0},
                 'unit': {'type': 'string', 'enum': TIMEOUT_UNITS, 'default': 'minutes'}
             }
         },
-        'bid_strategy': {
+        'entry_pricing': {
             'type': 'object',
             'properties': {
-                'ask_last_balance': {
+                'price_last_balance': {
                     'type': 'number',
                     'minimum': 0,
                     'maximum': 1,
                     'exclusiveMaximum': False,
                 },
-                'price_side': {'type': 'string', 'enum': ORDERBOOK_SIDES, 'default': 'bid'},
+                'price_side': {'type': 'string', 'enum': PRICING_SIDES, 'default': 'same'},
                 'use_order_book': {'type': 'boolean'},
                 'order_book_top': {'type': 'integer', 'minimum': 1, 'maximum': 50, },
                 'check_depth_of_market': {
@@ -176,11 +192,11 @@ CONF_SCHEMA = {
             },
             'required': ['price_side']
         },
-        'ask_strategy': {
+        'exit_pricing': {
             'type': 'object',
             'properties': {
-                'price_side': {'type': 'string', 'enum': ORDERBOOK_SIDES, 'default': 'ask'},
-                'bid_last_balance': {
+                'price_side': {'type': 'string', 'enum': PRICING_SIDES, 'default': 'same'},
+                'price_last_balance': {
                     'type': 'number',
                     'minimum': 0,
                     'maximum': 1,
@@ -192,31 +208,34 @@ CONF_SCHEMA = {
             'required': ['price_side']
         },
         'custom_price_max_distance_ratio': {
-           'type': 'number', 'minimum': 0.0
+            'type': 'number', 'minimum': 0.0
         },
         'order_types': {
             'type': 'object',
             'properties': {
-                'buy': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
-                'sell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
-                'forcesell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
-                'forcebuy': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
-                'emergencysell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
+                'entry': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
+                'exit': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
+                'force_exit': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
+                'force_entry': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
+                'emergency_exit': {
+                    'type': 'string',
+                    'enum': ORDERTYPE_POSSIBILITIES,
+                    'default': 'market'},
                 'stoploss': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
                 'stoploss_on_exchange': {'type': 'boolean'},
                 'stoploss_on_exchange_interval': {'type': 'number'},
                 'stoploss_on_exchange_limit_ratio': {'type': 'number', 'minimum': 0.0,
                                                      'maximum': 1.0}
             },
-            'required': ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']
+            'required': ['entry', 'exit', 'stoploss', 'stoploss_on_exchange']
         },
         'order_time_in_force': {
             'type': 'object',
             'properties': {
-                'buy': {'type': 'string', 'enum': ORDERTIF_POSSIBILITIES},
-                'sell': {'type': 'string', 'enum': ORDERTIF_POSSIBILITIES}
+                'entry': {'type': 'string', 'enum': ORDERTIF_POSSIBILITIES},
+                'exit': {'type': 'string', 'enum': ORDERTIF_POSSIBILITIES}
             },
-            'required': ['buy', 'sell']
+            'required': REQUIRED_ORDERTIF
         },
         'exchange': {'$ref': '#/definitions/exchange'},
         'edge': {'$ref': '#/definitions/edge'},
@@ -265,21 +284,21 @@ CONF_SCHEMA = {
                         'status': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
                         'warning': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
                         'startup': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
-                        'buy': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
-                        'buy_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
-                        'buy_fill': {'type': 'string',
-                                     'enum': TELEGRAM_SETTING_OPTIONS,
-                                     'default': 'off'
-                                     },
-                        'sell': {
+                        'entry': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
+                        'entry_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
+                        'entry_fill': {'type': 'string',
+                                       'enum': TELEGRAM_SETTING_OPTIONS,
+                                       'default': 'off'
+                                       },
+                        'exit': {
                             'type': ['string', 'object'],
                             'additionalProperties': {
                                 'type': 'string',
                                 'enum': TELEGRAM_SETTING_OPTIONS
                             }
                         },
-                        'sell_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
-                        'sell_fill': {
+                        'exit_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
+                        'exit_fill': {
                             'type': 'string',
                             'enum': TELEGRAM_SETTING_OPTIONS,
                             'default': 'off'
@@ -303,10 +322,16 @@ CONF_SCHEMA = {
             'type': 'object',
             'properties': {
                 'enabled': {'type': 'boolean'},
-                'webhookbuy': {'type': 'object'},
-                'webhookbuycancel': {'type': 'object'},
-                'webhooksell': {'type': 'object'},
-                'webhooksellcancel': {'type': 'object'},
+                'url': {'type': 'string'},
+                'format': {'type': 'string', 'enum': WEBHOOK_FORMAT_OPTIONS, 'default': 'form'},
+                'retries': {'type': 'integer', 'minimum': 0},
+                'retry_delay': {'type': 'number', 'minimum': 0},
+                'webhookentry': {'type': 'object'},
+                'webhookentrycancel': {'type': 'object'},
+                'webhookentryfill': {'type': 'object'},
+                'webhookexit': {'type': 'object'},
+                'webhookexitcancel': {'type': 'object'},
+                'webhookexitfill': {'type': 'object'},
                 'webhookstatus': {'type': 'object'},
             },
         },
@@ -332,7 +357,7 @@ CONF_SCHEMA = {
         'export': {'type': 'string', 'enum': EXPORT_OPTIONS, 'default': 'trades'},
         'disableparamexport': {'type': 'boolean'},
         'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
-        'forcebuy_enable': {'type': 'boolean'},
+        'force_entry_enable': {'type': 'boolean'},
         'disable_dataframe_checks': {'type': 'boolean'},
         'internals': {
             'type': 'object',
@@ -345,14 +370,16 @@ CONF_SCHEMA = {
         },
         'dataformat_ohlcv': {
             'type': 'string',
-                    'enum': AVAILABLE_DATAHANDLERS,
-                    'default': 'json'
+            'enum': AVAILABLE_DATAHANDLERS,
+            'default': 'json'
         },
         'dataformat_trades': {
             'type': 'string',
-                    'enum': AVAILABLE_DATAHANDLERS,
-                    'default': 'jsongz'
-        }
+            'enum': AVAILABLE_DATAHANDLERS,
+            'default': 'jsongz'
+        },
+        'position_adjustment_enable': {'type': 'boolean'},
+        'max_entry_position_adjustment': {'type': ['integer', 'number'], 'minimum': -1},
     },
     'definitions': {
         'exchange': {
@@ -378,6 +405,7 @@ CONF_SCHEMA = {
                     },
                     'uniqueItems': True
                 },
+                'unknown_fee_rate': {'type': 'number'},
                 'outdated_offset': {'type': 'integer', 'minimum': 1},
                 'markets_refresh_interval': {'type': 'integer'},
                 'ccxt_config': {'type': 'object'},
@@ -416,9 +444,8 @@ SCHEMA_TRADE_REQUIRED = [
     'last_stake_amount_min_ratio',
     'dry_run',
     'dry_run_wallet',
-    'ask_strategy',
-    'bid_strategy',
-    'unfilledtimeout',
+    'exit_pricing',
+    'entry_pricing',
     'stoploss',
     'minimal_roi',
     'internals',
@@ -450,12 +477,15 @@ CANCEL_REASON = {
     "FULLY_CANCELLED": "fully cancelled",
     "ALL_CANCELLED": "cancelled (all unfilled and partially filled open orders cancelled)",
     "CANCELLED_ON_EXCHANGE": "cancelled on exchange",
-    "FORCE_SELL": "forcesold",
+    "FORCE_EXIT": "forcesold",
 }
 
 # List of pairs with their timeframes
-PairWithTimeframe = Tuple[str, str]
+PairWithTimeframe = Tuple[str, str, CandleType]
 ListPairsWithTimeframes = List[PairWithTimeframe]
 
 # Type for trades list
 TradeList = List[List]
+
+LongShort = Literal['long', 'short']
+EntryExit = Literal['entry', 'exit']
diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py
index 7d97661c4..8abcc6747 100644
--- a/freqtrade/data/btanalysis.py
+++ b/freqtrade/data/btanalysis.py
@@ -2,6 +2,8 @@
 Helpers when analyzing backtest data
 """
 import logging
+from copy import copy
+from datetime import datetime, timezone
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Tuple, Union
 
@@ -9,28 +11,22 @@ import numpy as np
 import pandas as pd
 
 from freqtrade.constants import LAST_BT_RESULT_FN
-from freqtrade.misc import json_load
+from freqtrade.exceptions import OperationalException
+from freqtrade.misc import get_backtest_metadata_filename, json_load
 from freqtrade.persistence import LocalTrade, Trade, init_db
 
 
 logger = logging.getLogger(__name__)
 
-# Old format - maybe remove?
-BT_DATA_COLUMNS_OLD = ["pair", "profit_percent", "open_date", "close_date", "index",
-                       "trade_duration", "open_rate", "close_rate", "open_at_end", "sell_reason"]
-
-# Mid-term format, created by BacktestResult Named Tuple
-BT_DATA_COLUMNS_MID = ['pair', 'profit_percent', 'open_date', 'close_date', 'trade_duration',
-                       'open_rate', 'close_rate', 'open_at_end', 'sell_reason', 'fee_open',
-                       'fee_close', 'amount', 'profit_abs', 'profit_ratio']
-
 # Newest format
 BT_DATA_COLUMNS = ['pair', 'stake_amount', 'amount', 'open_date', 'close_date',
                    'open_rate', 'close_rate',
                    'fee_open', 'fee_close', 'trade_duration',
-                   'profit_ratio', 'profit_abs', 'sell_reason',
+                   'profit_ratio', 'profit_abs', 'exit_reason',
                    'initial_stop_loss_abs', 'initial_stop_loss_ratio', 'stop_loss_abs',
-                   'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', 'buy_tag']
+                   'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', 'enter_tag',
+                   'is_short'
+                   ]
 
 
 def get_latest_optimize_filename(directory: Union[Path, str], variant: str) -> str:
@@ -106,10 +102,30 @@ def get_latest_hyperopt_file(directory: Union[Path, str], predef_filename: str =
     if isinstance(directory, str):
         directory = Path(directory)
     if predef_filename:
+        if Path(predef_filename).is_absolute():
+            raise OperationalException(
+                "--hyperopt-filename expects only the filename, not an absolute path.")
         return directory / predef_filename
     return directory / get_latest_hyperopt_filename(directory)
 
 
+def load_backtest_metadata(filename: Union[Path, str]) -> Dict[str, Any]:
+    """
+    Read metadata dictionary from backtest results file without reading and deserializing entire
+    file.
+    :param filename: path to backtest results file.
+    :return: metadata dict or None if metadata is not present.
+    """
+    filename = get_backtest_metadata_filename(filename)
+    try:
+        with filename.open() as fp:
+            return json_load(fp)
+    except FileNotFoundError:
+        return {}
+    except Exception as e:
+        raise OperationalException('Unexpected error while loading backtest metadata.') from e
+
+
 def load_backtest_stats(filename: Union[Path, str]) -> Dict[str, Any]:
     """
     Load backtest statistics file.
@@ -126,9 +142,104 @@ def load_backtest_stats(filename: Union[Path, str]) -> Dict[str, Any]:
     with filename.open() as file:
         data = json_load(file)
 
+    # Legacy list format does not contain metadata.
+    if isinstance(data, dict):
+        data['metadata'] = load_backtest_metadata(filename)
+
     return data
 
 
+def load_and_merge_backtest_result(strategy_name: str, filename: Path, results: Dict[str, Any]):
+    """
+    Load one strategy from multi-strategy result
+    and merge it with results
+    :param strategy_name: Name of the strategy contained in the result
+    :param filename: Backtest-result-filename to load
+    :param results: dict to merge the result to.
+    """
+    bt_data = load_backtest_stats(filename)
+    for k in ('metadata', 'strategy'):
+        results[k][strategy_name] = bt_data[k][strategy_name]
+    comparison = bt_data['strategy_comparison']
+    for i in range(len(comparison)):
+        if comparison[i]['key'] == strategy_name:
+            results['strategy_comparison'].append(comparison[i])
+            break
+
+
+def _get_backtest_files(dirname: Path) -> List[Path]:
+    return list(reversed(sorted(dirname.glob('backtest-result-*-[0-9][0-9].json'))))
+
+
+def get_backtest_resultlist(dirname: Path):
+    """
+    Get list of backtest results read from metadata files
+    """
+    results = []
+    for filename in _get_backtest_files(dirname):
+        metadata = load_backtest_metadata(filename)
+        if not metadata:
+            continue
+        for s, v in metadata.items():
+            results.append({
+                'filename': filename.name,
+                'strategy': s,
+                'run_id': v['run_id'],
+                'backtest_start_time': v['backtest_start_time'],
+
+            })
+    return results
+
+
+def find_existing_backtest_stats(dirname: Union[Path, str], run_ids: Dict[str, str],
+                                 min_backtest_date: datetime = None) -> Dict[str, Any]:
+    """
+    Find existing backtest stats that match specified run IDs and load them.
+    :param dirname: pathlib.Path object, or string pointing to the file.
+    :param run_ids: {strategy_name: id_string} dictionary.
+    :param min_backtest_date: do not load a backtest older than specified date.
+    :return: results dict.
+    """
+    # Copy so we can modify this dict without affecting parent scope.
+    run_ids = copy(run_ids)
+    dirname = Path(dirname)
+    results: Dict[str, Any] = {
+        'metadata': {},
+        'strategy': {},
+        'strategy_comparison': [],
+    }
+
+    # Weird glob expression here avoids including .meta.json files.
+    for filename in _get_backtest_files(dirname):
+        metadata = load_backtest_metadata(filename)
+        if not metadata:
+            # Files are sorted from newest to oldest. When file without metadata is encountered it
+            # is safe to assume older files will also not have any metadata.
+            break
+
+        for strategy_name, run_id in list(run_ids.items()):
+            strategy_metadata = metadata.get(strategy_name, None)
+            if not strategy_metadata:
+                # This strategy is not present in analyzed backtest.
+                continue
+
+            if min_backtest_date is not None:
+                backtest_date = strategy_metadata['backtest_start_time']
+                backtest_date = datetime.fromtimestamp(backtest_date, tz=timezone.utc)
+                if backtest_date < min_backtest_date:
+                    # Do not use a cached result for this strategy as first result is too old.
+                    del run_ids[strategy_name]
+                    continue
+
+            if strategy_metadata['run_id'] == run_id:
+                del run_ids[strategy_name]
+                load_and_merge_backtest_result(strategy_name, filename, results)
+
+        if len(run_ids) == 0:
+            break
+    return results
+
+
 def load_backtest_data(filename: Union[Path, str], strategy: Optional[str] = None) -> pd.DataFrame:
     """
     Load backtest data file.
@@ -165,25 +276,18 @@ def load_backtest_data(filename: Union[Path, str], strategy: Optional[str] = Non
                                               utc=True,
                                               infer_datetime_format=True
                                               )
+            # Compatibility support for pre short Columns
+            if 'is_short' not in df.columns:
+                df['is_short'] = 0
+            if 'enter_tag' not in df.columns:
+                df['enter_tag'] = df['buy_tag']
+                df = df.drop(['buy_tag'], axis=1)
+
     else:
         # old format - only with lists.
-        df = pd.DataFrame(data, columns=BT_DATA_COLUMNS_OLD)
-        if not df.empty:
-            df['open_date'] = pd.to_datetime(df['open_date'],
-                                             unit='s',
-                                             utc=True,
-                                             infer_datetime_format=True
-                                             )
-            df['close_date'] = pd.to_datetime(df['close_date'],
-                                              unit='s',
-                                              utc=True,
-                                              infer_datetime_format=True
-                                              )
-            # Create compatibility with new format
-            df['profit_abs'] = df['close_rate'] - df['open_rate']
+        raise OperationalException(
+            "Backtest-results with only trades data are no longer supported.")
     if not df.empty:
-        if 'profit_ratio' not in df.columns:
-            df['profit_ratio'] = df['profit_percent']
         df = df.sort_values("open_date").reset_index(drop=True)
     return df
 
@@ -325,6 +429,7 @@ def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],
     :param column: Column in the original dataframes to use
     :return: DataFrame with the column renamed to the dict key, and a column
         named mean, containing the mean of all pairs.
+    :raise: ValueError if no data is provided.
     """
     df_comb = pd.concat([data[pair].set_index('date').rename(
         {column: pair}, axis=1)[pair] for pair in data], axis=1)
@@ -360,9 +465,19 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
     return df
 
 
-def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date',
-                           value_col: str = 'profit_ratio'
-                           ) -> Tuple[float, pd.Timestamp, pd.Timestamp, float, float]:
+def _calc_drawdown_series(profit_results: pd.DataFrame, *, date_col: str, value_col: str
+                          ) -> pd.DataFrame:
+    max_drawdown_df = pd.DataFrame()
+    max_drawdown_df['cumulative'] = profit_results[value_col].cumsum()
+    max_drawdown_df['high_value'] = max_drawdown_df['cumulative'].cummax()
+    max_drawdown_df['drawdown'] = max_drawdown_df['cumulative'] - max_drawdown_df['high_value']
+    max_drawdown_df['date'] = profit_results.loc[:, date_col]
+    return max_drawdown_df
+
+
+def calculate_underwater(trades: pd.DataFrame, *, date_col: str = 'close_date',
+                         value_col: str = 'profit_ratio'
+                         ):
     """
     Calculate max drawdown and the corresponding close dates
     :param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
@@ -375,10 +490,29 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date'
     if len(trades) == 0:
         raise ValueError("Trade dataframe empty.")
     profit_results = trades.sort_values(date_col).reset_index(drop=True)
-    max_drawdown_df = pd.DataFrame()
-    max_drawdown_df['cumulative'] = profit_results[value_col].cumsum()
-    max_drawdown_df['high_value'] = max_drawdown_df['cumulative'].cummax()
-    max_drawdown_df['drawdown'] = max_drawdown_df['cumulative'] - max_drawdown_df['high_value']
+    max_drawdown_df = _calc_drawdown_series(profit_results, date_col=date_col, value_col=value_col)
+
+    return max_drawdown_df
+
+
+def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date',
+                           value_col: str = 'profit_abs', starting_balance: float = 0
+                           ) -> Tuple[float, pd.Timestamp, pd.Timestamp, float, float, float]:
+    """
+    Calculate max drawdown and the corresponding close dates
+    :param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
+    :param date_col: Column in DataFrame to use for dates (defaults to 'close_date')
+    :param value_col: Column in DataFrame to use for values (defaults to 'profit_abs')
+    :param starting_balance: Portfolio starting balance - properly calculate relative drawdown.
+    :return: Tuple (float, highdate, lowdate, highvalue, lowvalue, relative_drawdown)
+             with absolute max drawdown, high and low time and high and low value,
+             and the relative account drawdown
+    :raise: ValueError if trade-dataframe was found empty.
+    """
+    if len(trades) == 0:
+        raise ValueError("Trade dataframe empty.")
+    profit_results = trades.sort_values(date_col).reset_index(drop=True)
+    max_drawdown_df = _calc_drawdown_series(profit_results, date_col=date_col, value_col=value_col)
 
     idxmin = max_drawdown_df['drawdown'].idxmin()
     if idxmin == 0:
@@ -388,7 +522,18 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date'
     high_val = max_drawdown_df.loc[max_drawdown_df.iloc[:idxmin]
                                    ['high_value'].idxmax(), 'cumulative']
     low_val = max_drawdown_df.loc[idxmin, 'cumulative']
-    return abs(min(max_drawdown_df['drawdown'])), high_date, low_date, high_val, low_val
+    max_drawdown_rel = 0.0
+    if high_val + starting_balance != 0:
+        max_drawdown_rel = (high_val - low_val) / (high_val + starting_balance)
+
+    return (
+        abs(min(max_drawdown_df['drawdown'])),
+        high_date,
+        low_date,
+        high_val,
+        low_val,
+        max_drawdown_rel
+    )
 
 
 def calculate_csum(trades: pd.DataFrame, starting_balance: float = 0) -> Tuple[float, float]:
diff --git a/freqtrade/data/converter.py b/freqtrade/data/converter.py
index ca6464965..84c57be41 100644
--- a/freqtrade/data/converter.py
+++ b/freqtrade/data/converter.py
@@ -11,6 +11,7 @@ import pandas as pd
 from pandas import DataFrame, to_datetime
 
 from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS, TradeList
+from freqtrade.enums import CandleType
 
 
 logger = logging.getLogger(__name__)
@@ -113,7 +114,7 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
     pct_missing = (len_after - len_before) / len_before if len_before > 0 else 0
     if len_before != len_after:
         message = (f"Missing data fillup for {pair}: before: {len_before} - after: {len_after}"
-                   f" - {round(pct_missing * 100, 2)}%")
+                   f" - {pct_missing:.2%}")
         if pct_missing > 0.01:
             logger.info(message)
         else:
@@ -261,13 +262,20 @@ def convert_trades_format(config: Dict[str, Any], convert_from: str, convert_to:
             src.trades_purge(pair=pair)
 
 
-def convert_ohlcv_format(config: Dict[str, Any], convert_from: str, convert_to: str, erase: bool):
+def convert_ohlcv_format(
+    config: Dict[str, Any],
+    convert_from: str,
+    convert_to: str,
+    erase: bool,
+    candle_type: CandleType
+):
     """
     Convert OHLCV from one format to another
     :param config: Config dictionary
     :param convert_from: Source format
     :param convert_to: Target format
     :param erase: Erase source data (does not apply if source and target format are identical)
+    :param candle_type: Any of the enum CandleType (must match trading mode!)
     """
     from freqtrade.data.history.idatahandler import get_datahandler
     src = get_datahandler(config['datadir'], convert_from)
@@ -279,8 +287,11 @@ def convert_ohlcv_format(config: Dict[str, Any], convert_from: str, convert_to:
         config['pairs'] = []
         # Check timeframes or fall back to timeframe.
         for timeframe in timeframes:
-            config['pairs'].extend(src.ohlcv_get_pairs(config['datadir'],
-                                                       timeframe))
+            config['pairs'].extend(src.ohlcv_get_pairs(
+                config['datadir'],
+                timeframe,
+                candle_type=candle_type
+            ))
     logger.info(f"Converting candle (OHLCV) data for {config['pairs']}")
 
     for timeframe in timeframes:
@@ -289,10 +300,16 @@ def convert_ohlcv_format(config: Dict[str, Any], convert_from: str, convert_to:
                                   timerange=None,
                                   fill_missing=False,
                                   drop_incomplete=False,
-                                  startup_candles=0)
-            logger.info(f"Converting {len(data)} candles for {pair}")
+                                  startup_candles=0,
+                                  candle_type=candle_type)
+            logger.info(f"Converting {len(data)} {candle_type} candles for {pair}")
             if len(data) > 0:
-                trg.ohlcv_store(pair=pair, timeframe=timeframe, data=data)
+                trg.ohlcv_store(
+                    pair=pair,
+                    timeframe=timeframe,
+                    data=data,
+                    candle_type=candle_type
+                )
                 if erase and convert_from != convert_to:
                     logger.info(f"Deleting source data for {pair} / {timeframe}")
-                    src.ohlcv_purge(pair=pair, timeframe=timeframe)
+                    src.ohlcv_purge(pair=pair, timeframe=timeframe, candle_type=candle_type)
diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py
index cdee0f078..b9b118c00 100644
--- a/freqtrade/data/dataprovider.py
+++ b/freqtrade/data/dataprovider.py
@@ -13,7 +13,7 @@ from pandas import DataFrame
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
 from freqtrade.data.history import load_pair_history
-from freqtrade.enums import RunMode
+from freqtrade.enums import CandleType, RunMode
 from freqtrade.exceptions import ExchangeError, OperationalException
 from freqtrade.exchange import Exchange, timeframe_to_seconds
 
@@ -41,7 +41,13 @@ class DataProvider:
         """
         self.__slice_index = limit_index
 
-    def _set_cached_df(self, pair: str, timeframe: str, dataframe: DataFrame) -> None:
+    def _set_cached_df(
+        self,
+        pair: str,
+        timeframe: str,
+        dataframe: DataFrame,
+        candle_type: CandleType
+    ) -> None:
         """
         Store cached Dataframe.
         Using private method as this should never be used by a user
@@ -49,8 +55,10 @@ class DataProvider:
         :param pair: pair to get the data for
         :param timeframe: Timeframe to get data for
         :param dataframe: analyzed dataframe
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         """
-        self.__cached_pairs[(pair, timeframe)] = (dataframe, datetime.now(timezone.utc))
+        self.__cached_pairs[(pair, timeframe, candle_type)] = (
+            dataframe, datetime.now(timezone.utc))
 
     def add_pairlisthandler(self, pairlists) -> None:
         """
@@ -58,13 +66,21 @@ class DataProvider:
         """
         self._pairlists = pairlists
 
-    def historic_ohlcv(self, pair: str, timeframe: str = None) -> DataFrame:
+    def historic_ohlcv(
+        self,
+        pair: str,
+        timeframe: str = None,
+        candle_type: str = ''
+    ) -> DataFrame:
         """
         Get stored historical candle (OHLCV) data
         :param pair: pair to get the data for
         :param timeframe: timeframe to get data for
+        :param candle_type: '', mark, index, premiumIndex, or funding_rate
         """
-        saved_pair = (pair, str(timeframe))
+        _candle_type = CandleType.from_string(
+            candle_type) if candle_type != '' else self._config['candle_type_def']
+        saved_pair = (pair, str(timeframe), _candle_type)
         if saved_pair not in self.__cached_pairs_backtesting:
             timerange = TimeRange.parse_timerange(None if self._config.get(
                 'timerange') is None else str(self._config.get('timerange')))
@@ -77,26 +93,36 @@ class DataProvider:
                 timeframe=timeframe or self._config['timeframe'],
                 datadir=self._config['datadir'],
                 timerange=timerange,
-                data_format=self._config.get('dataformat_ohlcv', 'json')
+                data_format=self._config.get('dataformat_ohlcv', 'json'),
+                candle_type=_candle_type,
+
             )
         return self.__cached_pairs_backtesting[saved_pair].copy()
 
-    def get_pair_dataframe(self, pair: str, timeframe: str = None) -> DataFrame:
+    def get_pair_dataframe(
+        self,
+        pair: str,
+        timeframe: str = None,
+        candle_type: str = ''
+    ) -> DataFrame:
         """
         Return pair candle (OHLCV) data, either live or cached historical -- depending
         on the runmode.
+        Only combinations in the pairlist or which have been specified as informative pairs
+        will be available.
         :param pair: pair to get the data for
         :param timeframe: timeframe to get data for
         :return: Dataframe for this pair
+        :param candle_type: '', mark, index, premiumIndex, or funding_rate
         """
         if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
             # Get live OHLCV data.
-            data = self.ohlcv(pair=pair, timeframe=timeframe)
+            data = self.ohlcv(pair=pair, timeframe=timeframe, candle_type=candle_type)
         else:
             # Get historical OHLCV data (cached on disk).
-            data = self.historic_ohlcv(pair=pair, timeframe=timeframe)
+            data = self.historic_ohlcv(pair=pair, timeframe=timeframe, candle_type=candle_type)
         if len(data) == 0:
-            logger.warning(f"No data found for ({pair}, {timeframe}).")
+            logger.warning(f"No data found for ({pair}, {timeframe}, {candle_type}).")
         return data
 
     def get_analyzed_dataframe(self, pair: str, timeframe: str) -> Tuple[DataFrame, datetime]:
@@ -109,7 +135,7 @@ class DataProvider:
             combination.
             Returns empty dataframe and Epoch 0 (1970-01-01) if no dataframe was cached.
         """
-        pair_key = (pair, timeframe)
+        pair_key = (pair, timeframe, self._config.get('candle_type_def', CandleType.SPOT))
         if pair_key in self.__cached_pairs:
             if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
                 df, date = self.__cached_pairs[pair_key]
@@ -149,6 +175,8 @@ class DataProvider:
         Clear pair dataframe cache.
         """
         self.__cached_pairs = {}
+        self.__cached_pairs_backtesting = {}
+        self.__slice_index = 0
 
     # Exchange functions
 
@@ -175,20 +203,31 @@ class DataProvider:
             raise OperationalException(NO_EXCHANGE_EXCEPTION)
         return list(self._exchange._klines.keys())
 
-    def ohlcv(self, pair: str, timeframe: str = None, copy: bool = True) -> DataFrame:
+    def ohlcv(
+        self,
+        pair: str,
+        timeframe: str = None,
+        copy: bool = True,
+        candle_type: str = ''
+    ) -> DataFrame:
         """
         Get candle (OHLCV) data for the given pair as DataFrame
         Please use the `available_pairs` method to verify which pairs are currently cached.
         :param pair: pair to get the data for
         :param timeframe: Timeframe to get data for
+        :param candle_type: '', mark, index, premiumIndex, or funding_rate
         :param copy: copy dataframe before returning if True.
                      Use False only for read-only operations (where the dataframe is not modified)
         """
         if self._exchange is None:
             raise OperationalException(NO_EXCHANGE_EXCEPTION)
         if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
-            return self._exchange.klines((pair, timeframe or self._config['timeframe']),
-                                         copy=copy)
+            _candle_type = CandleType.from_string(
+                candle_type) if candle_type != '' else self._config['candle_type_def']
+            return self._exchange.klines(
+                (pair, timeframe or self._config['timeframe'], _candle_type),
+                copy=copy
+            )
         else:
             return DataFrame()
 
diff --git a/freqtrade/data/history/hdf5datahandler.py b/freqtrade/data/history/hdf5datahandler.py
index dd60530aa..23120a4ba 100644
--- a/freqtrade/data/history/hdf5datahandler.py
+++ b/freqtrade/data/history/hdf5datahandler.py
@@ -6,10 +6,10 @@ from typing import List, Optional
 import numpy as np
 import pandas as pd
 
-from freqtrade import misc
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import (DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS,
                                  ListPairsWithTimeframes, TradeList)
+from freqtrade.enums import CandleType, TradingMode
 
 from .idatahandler import IDataHandler
 
@@ -22,52 +22,72 @@ class HDF5DataHandler(IDataHandler):
     _columns = DEFAULT_DATAFRAME_COLUMNS
 
     @classmethod
-    def ohlcv_get_available_data(cls, datadir: Path) -> ListPairsWithTimeframes:
+    def ohlcv_get_available_data(
+            cls, datadir: Path, trading_mode: TradingMode) -> ListPairsWithTimeframes:
         """
         Returns a list of all pairs with ohlcv data available in this datadir
         :param datadir: Directory to search for ohlcv files
+        :param trading_mode: trading-mode to be used
         :return: List of Tuples of (pair, timeframe)
         """
-        _tmp = [re.search(r'^([a-zA-Z_]+)\-(\d+\S+)(?=.h5)', p.name)
-                for p in datadir.glob("*.h5")]
-        return [(match[1].replace('_', '/'), match[2]) for match in _tmp
-                if match and len(match.groups()) > 1]
+        if trading_mode == TradingMode.FUTURES:
+            datadir = datadir.joinpath('futures')
+        _tmp = [
+            re.search(
+                cls._OHLCV_REGEX, p.name
+            ) for p in datadir.glob("*.h5")
+        ]
+        return [
+            (
+                cls.rebuild_pair_from_filename(match[1]),
+                match[2],
+                CandleType.from_string(match[3])
+            ) for match in _tmp if match and len(match.groups()) > 1]
 
     @classmethod
-    def ohlcv_get_pairs(cls, datadir: Path, timeframe: str) -> List[str]:
+    def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
         """
         Returns a list of all pairs with ohlcv data available in this datadir
         for the specified timeframe
         :param datadir: Directory to search for ohlcv files
         :param timeframe: Timeframe to search pairs for
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: List of Pairs
         """
+        candle = ""
+        if candle_type != CandleType.SPOT:
+            datadir = datadir.joinpath('futures')
+            candle = f"-{candle_type}"
 
-        _tmp = [re.search(r'^(\S+)(?=\-' + timeframe + '.h5)', p.name)
-                for p in datadir.glob(f"*{timeframe}.h5")]
+        _tmp = [re.search(r'^(\S+)(?=\-' + timeframe + candle + '.h5)', p.name)
+                for p in datadir.glob(f"*{timeframe}{candle}.h5")]
         # Check if regex found something and only return these results
-        return [match[0].replace('_', '/') for match in _tmp if match]
+        return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
 
-    def ohlcv_store(self, pair: str, timeframe: str, data: pd.DataFrame) -> None:
+    def ohlcv_store(
+            self, pair: str, timeframe: str, data: pd.DataFrame, candle_type: CandleType) -> None:
         """
         Store data in hdf5 file.
         :param pair: Pair - used to generate filename
         :param timeframe: Timeframe - used to generate filename
         :param data: Dataframe containing OHLCV data
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: None
         """
         key = self._pair_ohlcv_key(pair, timeframe)
         _data = data.copy()
 
-        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+        filename = self._pair_data_filename(self._datadir, pair, timeframe, candle_type)
+        self.create_dir_if_needed(filename)
 
-        ds = pd.HDFStore(filename, mode='a', complevel=9, complib='blosc')
-        ds.put(key, _data.loc[:, self._columns], format='table', data_columns=['date'])
-
-        ds.close()
+        _data.loc[:, self._columns].to_hdf(
+            filename, key, mode='a', complevel=9, complib='blosc',
+            format='table', data_columns=['date']
+        )
 
     def _ohlcv_load(self, pair: str, timeframe: str,
-                    timerange: Optional[TimeRange] = None) -> pd.DataFrame:
+                    timerange: Optional[TimeRange], candle_type: CandleType
+                    ) -> pd.DataFrame:
         """
         Internal method used to load data for one pair from disk.
         Implements the loading and conversion to a Pandas dataframe.
@@ -77,10 +97,16 @@ class HDF5DataHandler(IDataHandler):
         :param timerange: Limit data to be loaded to this timerange.
                         Optionally implemented by subclasses to avoid loading
                         all data where possible.
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: DataFrame with ohlcv data, or empty DataFrame
         """
         key = self._pair_ohlcv_key(pair, timeframe)
-        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+        filename = self._pair_data_filename(
+            self._datadir,
+            pair,
+            timeframe,
+            candle_type=candle_type
+        )
 
         if not filename.exists():
             return pd.DataFrame(columns=self._columns)
@@ -99,25 +125,19 @@ class HDF5DataHandler(IDataHandler):
                                           'low': 'float', 'close': 'float', 'volume': 'float'})
         return pairdata
 
-    def ohlcv_purge(self, pair: str, timeframe: str) -> bool:
-        """
-        Remove data for this pair
-        :param pair: Delete data for this pair.
-        :param timeframe: Timeframe (e.g. "5m")
-        :return: True when deleted, false if file did not exist.
-        """
-        filename = self._pair_data_filename(self._datadir, pair, timeframe)
-        if filename.exists():
-            filename.unlink()
-            return True
-        return False
-
-    def ohlcv_append(self, pair: str, timeframe: str, data: pd.DataFrame) -> None:
+    def ohlcv_append(
+        self,
+        pair: str,
+        timeframe: str,
+        data: pd.DataFrame,
+        candle_type: CandleType
+    ) -> None:
         """
         Append data to existing data structures
         :param pair: Pair
         :param timeframe: Timeframe this ohlcv data is for
         :param data: Data to append.
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         """
         raise NotImplementedError()
 
@@ -131,7 +151,7 @@ class HDF5DataHandler(IDataHandler):
         _tmp = [re.search(r'^(\S+)(?=\-trades.h5)', p.name)
                 for p in datadir.glob("*trades.h5")]
         # Check if regex found something and only return these results to avoid exceptions.
-        return [match[0].replace('_', '/') for match in _tmp if match]
+        return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
 
     def trades_store(self, pair: str, data: TradeList) -> None:
         """
@@ -142,11 +162,11 @@ class HDF5DataHandler(IDataHandler):
         """
         key = self._pair_trades_key(pair)
 
-        ds = pd.HDFStore(self._pair_trades_filename(self._datadir, pair),
-                         mode='a', complevel=9, complib='blosc')
-        ds.put(key, pd.DataFrame(data, columns=DEFAULT_TRADES_COLUMNS),
-               format='table', data_columns=['timestamp'])
-        ds.close()
+        pd.DataFrame(data, columns=DEFAULT_TRADES_COLUMNS).to_hdf(
+            self._pair_trades_filename(self._datadir, pair), key,
+            mode='a', complevel=9, complib='blosc',
+            format='table', data_columns=['timestamp']
+        )
 
     def trades_append(self, pair: str, data: TradeList):
         """
@@ -180,34 +200,16 @@ class HDF5DataHandler(IDataHandler):
         trades[['id', 'type']] = trades[['id', 'type']].replace({np.nan: None})
         return trades.values.tolist()
 
-    def trades_purge(self, pair: str) -> bool:
-        """
-        Remove data for this pair
-        :param pair: Delete data for this pair.
-        :return: True when deleted, false if file did not exist.
-        """
-        filename = self._pair_trades_filename(self._datadir, pair)
-        if filename.exists():
-            filename.unlink()
-            return True
-        return False
+    @classmethod
+    def _get_file_extension(cls):
+        return "h5"
 
     @classmethod
     def _pair_ohlcv_key(cls, pair: str, timeframe: str) -> str:
-        return f"{pair}/ohlcv/tf_{timeframe}"
+        # Escape futures pairs to avoid warnings
+        pair_esc = pair.replace(':', '_')
+        return f"{pair_esc}/ohlcv/tf_{timeframe}"
 
     @classmethod
     def _pair_trades_key(cls, pair: str) -> str:
         return f"{pair}/trades"
-
-    @classmethod
-    def _pair_data_filename(cls, datadir: Path, pair: str, timeframe: str) -> Path:
-        pair_s = misc.pair_to_filename(pair)
-        filename = datadir.joinpath(f'{pair_s}-{timeframe}.h5')
-        return filename
-
-    @classmethod
-    def _pair_trades_filename(cls, datadir: Path, pair: str) -> Path:
-        pair_s = misc.pair_to_filename(pair)
-        filename = datadir.joinpath(f'{pair_s}-trades.h5')
-        return filename
diff --git a/freqtrade/data/history/history_utils.py b/freqtrade/data/history/history_utils.py
index e6b8db322..8560fd29e 100644
--- a/freqtrade/data/history/history_utils.py
+++ b/freqtrade/data/history/history_utils.py
@@ -5,13 +5,14 @@ from pathlib import Path
 from typing import Dict, List, Optional, Tuple
 
 import arrow
-from pandas import DataFrame
+from pandas import DataFrame, concat
 
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS
 from freqtrade.data.converter import (clean_ohlcv_dataframe, ohlcv_to_dataframe,
                                       trades_remove_duplicates, trades_to_ohlcv)
 from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler
+from freqtrade.enums import CandleType
 from freqtrade.exceptions import OperationalException
 from freqtrade.exchange import Exchange
 from freqtrade.misc import format_ms_time
@@ -29,6 +30,7 @@ def load_pair_history(pair: str,
                       startup_candles: int = 0,
                       data_format: str = None,
                       data_handler: IDataHandler = None,
+                      candle_type: CandleType = CandleType.SPOT
                       ) -> DataFrame:
     """
     Load cached ohlcv history for the given pair.
@@ -43,6 +45,7 @@ def load_pair_history(pair: str,
     :param startup_candles: Additional candles to load at the start of the period
     :param data_handler: Initialized data-handler to use.
                          Will be initialized from data_format if not set
+    :param candle_type: Any of the enum CandleType (must match trading mode!)
     :return: DataFrame with ohlcv data, or empty DataFrame
     """
     data_handler = get_datahandler(datadir, data_format, data_handler)
@@ -53,6 +56,7 @@ def load_pair_history(pair: str,
                                    fill_missing=fill_up_missing,
                                    drop_incomplete=drop_incomplete,
                                    startup_candles=startup_candles,
+                                   candle_type=candle_type
                                    )
 
 
@@ -64,6 +68,7 @@ def load_data(datadir: Path,
               startup_candles: int = 0,
               fail_without_data: bool = False,
               data_format: str = 'json',
+              candle_type: CandleType = CandleType.SPOT
               ) -> Dict[str, DataFrame]:
     """
     Load ohlcv history data for a list of pairs.
@@ -76,6 +81,7 @@ def load_data(datadir: Path,
     :param startup_candles: Additional candles to load at the start of the period
     :param fail_without_data: Raise OperationalException if no data is found.
     :param data_format: Data format which should be used. Defaults to json
+    :param candle_type: Any of the enum CandleType (must match trading mode!)
     :return: dict(<pair>:<Dataframe>)
     """
     result: Dict[str, DataFrame] = {}
@@ -89,7 +95,8 @@ def load_data(datadir: Path,
                                  datadir=datadir, timerange=timerange,
                                  fill_up_missing=fill_up_missing,
                                  startup_candles=startup_candles,
-                                 data_handler=data_handler
+                                 data_handler=data_handler,
+                                 candle_type=candle_type
                                  )
         if not hist.empty:
             result[pair] = hist
@@ -99,12 +106,13 @@ def load_data(datadir: Path,
     return result
 
 
-def refresh_data(datadir: Path,
+def refresh_data(*, datadir: Path,
                  timeframe: str,
                  pairs: List[str],
                  exchange: Exchange,
                  data_format: str = None,
                  timerange: Optional[TimeRange] = None,
+                 candle_type: CandleType,
                  ) -> None:
     """
     Refresh ohlcv history data for a list of pairs.
@@ -115,17 +123,24 @@ def refresh_data(datadir: Path,
     :param exchange: Exchange object
     :param data_format: dataformat to use
     :param timerange: Limit data to be loaded to this timerange
+    :param candle_type: Any of the enum CandleType (must match trading mode!)
     """
     data_handler = get_datahandler(datadir, data_format)
     for idx, pair in enumerate(pairs):
         process = f'{idx}/{len(pairs)}'
         _download_pair_history(pair=pair, process=process,
                                timeframe=timeframe, datadir=datadir,
-                               timerange=timerange, exchange=exchange, data_handler=data_handler)
+                               timerange=timerange, exchange=exchange, data_handler=data_handler,
+                               candle_type=candle_type)
 
 
-def _load_cached_data_for_updating(pair: str, timeframe: str, timerange: Optional[TimeRange],
-                                   data_handler: IDataHandler) -> Tuple[DataFrame, Optional[int]]:
+def _load_cached_data_for_updating(
+    pair: str,
+    timeframe: str,
+    timerange: Optional[TimeRange],
+    data_handler: IDataHandler,
+    candle_type: CandleType
+) -> Tuple[DataFrame, Optional[int]]:
     """
     Load cached data to download more data.
     If timerange is passed in, checks whether data from an before the stored data will be
@@ -142,7 +157,8 @@ def _load_cached_data_for_updating(pair: str, timeframe: str, timerange: Optiona
     # Intentionally don't pass timerange in - since we need to load the full dataset.
     data = data_handler.ohlcv_load(pair, timeframe=timeframe,
                                    timerange=None, fill_missing=False,
-                                   drop_incomplete=True, warn_no_data=False)
+                                   drop_incomplete=True, warn_no_data=False,
+                                   candle_type=candle_type)
     if not data.empty:
         if start and start < data.iloc[0]['date']:
             # Earlier data than existing data requested, redownload all
@@ -161,7 +177,10 @@ def _download_pair_history(pair: str, *,
                            process: str = '',
                            new_pairs_days: int = 30,
                            data_handler: IDataHandler = None,
-                           timerange: Optional[TimeRange] = None) -> bool:
+                           timerange: Optional[TimeRange] = None,
+                           candle_type: CandleType,
+                           erase: bool = False,
+                           ) -> bool:
     """
     Download latest candles from the exchange for the pair and timeframe passed in parameters
     The data is downloaded starting from the last correct data that
@@ -173,19 +192,25 @@ def _download_pair_history(pair: str, *,
     :param pair: pair to download
     :param timeframe: Timeframe (e.g "5m")
     :param timerange: range of time to download
+    :param candle_type: Any of the enum CandleType (must match trading mode!)
+    :param erase: Erase existing data
     :return: bool with success state
     """
     data_handler = get_datahandler(datadir, data_handler=data_handler)
 
     try:
+        if erase:
+            if data_handler.ohlcv_purge(pair, timeframe, candle_type=candle_type):
+                logger.info(f'Deleting existing data for pair {pair}, {timeframe}, {candle_type}.')
+
         logger.info(
-            f'Download history data for pair: "{pair}" ({process}), timeframe: {timeframe} '
-            f'and store in {datadir}.'
+            f'Download history data for pair: "{pair}" ({process}), timeframe: {timeframe}, '
+            f'candle type: {candle_type} and store in {datadir}.'
         )
 
-        # data, since_ms = _load_cached_data_for_updating_old(datadir, pair, timeframe, timerange)
         data, since_ms = _load_cached_data_for_updating(pair, timeframe, timerange,
-                                                        data_handler=data_handler)
+                                                        data_handler=data_handler,
+                                                        candle_type=candle_type)
 
         logger.debug("Current Start: %s",
                      f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
@@ -198,7 +223,8 @@ def _download_pair_history(pair: str, *,
                                                since_ms=since_ms if since_ms else
                                                arrow.utcnow().shift(
                                                    days=-new_pairs_days).int_timestamp * 1000,
-                                               is_new_pair=data.empty
+                                               is_new_pair=data.empty,
+                                               candle_type=candle_type,
                                                )
         # TODO: Maybe move parsing to exchange class (?)
         new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair,
@@ -208,7 +234,7 @@ def _download_pair_history(pair: str, *,
         else:
             # Run cleaning again to ensure there were no duplicate candles
             # Especially between existing and new data.
-            data = clean_ohlcv_dataframe(data.append(new_dataframe), timeframe, pair,
+            data = clean_ohlcv_dataframe(concat([data, new_dataframe], axis=0), timeframe, pair,
                                          fill_missing=False, drop_incomplete=False)
 
         logger.debug("New  Start: %s",
@@ -216,7 +242,7 @@ def _download_pair_history(pair: str, *,
         logger.debug("New End: %s",
                      f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
 
-        data_handler.ohlcv_store(pair, timeframe, data=data)
+        data_handler.ohlcv_store(pair, timeframe, data=data, candle_type=candle_type)
         return True
 
     except Exception:
@@ -227,9 +253,11 @@ def _download_pair_history(pair: str, *,
 
 
 def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes: List[str],
-                                datadir: Path, timerange: Optional[TimeRange] = None,
+                                datadir: Path, trading_mode: str,
+                                timerange: Optional[TimeRange] = None,
                                 new_pairs_days: int = 30, erase: bool = False,
-                                data_format: str = None) -> List[str]:
+                                data_format: str = None,
+                                ) -> List[str]:
     """
     Refresh stored ohlcv data for backtesting and hyperopt operations.
     Used by freqtrade download-data subcommand.
@@ -237,6 +265,7 @@ def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes
     """
     pairs_not_available = []
     data_handler = get_datahandler(datadir, data_format)
+    candle_type = CandleType.get_default(trading_mode)
     for idx, pair in enumerate(pairs, start=1):
         if pair not in exchange.markets:
             pairs_not_available.append(pair)
@@ -244,17 +273,29 @@ def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes
             continue
         for timeframe in timeframes:
 
-            if erase:
-                if data_handler.ohlcv_purge(pair, timeframe):
-                    logger.info(
-                        f'Deleting existing data for pair {pair}, interval {timeframe}.')
-
             logger.info(f'Downloading pair {pair}, interval {timeframe}.')
             process = f'{idx}/{len(pairs)}'
             _download_pair_history(pair=pair, process=process,
                                    datadir=datadir, exchange=exchange,
                                    timerange=timerange, data_handler=data_handler,
-                                   timeframe=str(timeframe), new_pairs_days=new_pairs_days)
+                                   timeframe=str(timeframe), new_pairs_days=new_pairs_days,
+                                   candle_type=candle_type,
+                                   erase=erase)
+        if trading_mode == 'futures':
+            # Predefined candletype (and timeframe) depending on exchange
+            # Downloads what is necessary to backtest based on futures data.
+            tf_mark = exchange._ft_has['mark_ohlcv_timeframe']
+            fr_candle_type = CandleType.from_string(exchange._ft_has['mark_ohlcv_price'])
+            # All exchanges need FundingRate for futures trading.
+            # The timeframe is aligned to the mark-price timeframe.
+            for funding_candle_type in (CandleType.FUNDING_RATE, fr_candle_type):
+                _download_pair_history(pair=pair, process=process,
+                                       datadir=datadir, exchange=exchange,
+                                       timerange=timerange, data_handler=data_handler,
+                                       timeframe=str(tf_mark), new_pairs_days=new_pairs_days,
+                                       candle_type=funding_candle_type,
+                                       erase=erase)
+
     return pairs_not_available
 
 
@@ -353,10 +394,16 @@ def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir:
     return pairs_not_available
 
 
-def convert_trades_to_ohlcv(pairs: List[str], timeframes: List[str],
-                            datadir: Path, timerange: TimeRange, erase: bool = False,
-                            data_format_ohlcv: str = 'json',
-                            data_format_trades: str = 'jsongz') -> None:
+def convert_trades_to_ohlcv(
+    pairs: List[str],
+    timeframes: List[str],
+    datadir: Path,
+    timerange: TimeRange,
+    erase: bool = False,
+    data_format_ohlcv: str = 'json',
+    data_format_trades: str = 'jsongz',
+    candle_type: CandleType = CandleType.SPOT
+) -> None:
     """
     Convert stored trades data to ohlcv data
     """
@@ -367,12 +414,12 @@ def convert_trades_to_ohlcv(pairs: List[str], timeframes: List[str],
         trades = data_handler_trades.trades_load(pair)
         for timeframe in timeframes:
             if erase:
-                if data_handler_ohlcv.ohlcv_purge(pair, timeframe):
+                if data_handler_ohlcv.ohlcv_purge(pair, timeframe, candle_type=candle_type):
                     logger.info(f'Deleting existing data for pair {pair}, interval {timeframe}.')
             try:
                 ohlcv = trades_to_ohlcv(trades, timeframe)
                 # Store ohlcv
-                data_handler_ohlcv.ohlcv_store(pair, timeframe, data=ohlcv)
+                data_handler_ohlcv.ohlcv_store(pair, timeframe, data=ohlcv, candle_type=candle_type)
             except ValueError:
                 logger.exception(f'Could not convert {pair} to OHLCV.')
 
diff --git a/freqtrade/data/history/idatahandler.py b/freqtrade/data/history/idatahandler.py
index 05052b2d7..4a5eb6bc2 100644
--- a/freqtrade/data/history/idatahandler.py
+++ b/freqtrade/data/history/idatahandler.py
@@ -4,6 +4,7 @@ It's subclasses handle and storing data from disk.
 
 """
 import logging
+import re
 from abc import ABC, abstractclassmethod, abstractmethod
 from copy import deepcopy
 from datetime import datetime, timezone
@@ -12,9 +13,11 @@ from typing import List, Optional, Type
 
 from pandas import DataFrame
 
+from freqtrade import misc
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import ListPairsWithTimeframes, TradeList
 from freqtrade.data.converter import clean_ohlcv_dataframe, trades_remove_duplicates, trim_dataframe
+from freqtrade.enums import CandleType, TradingMode
 from freqtrade.exchange import timeframe_to_seconds
 
 
@@ -23,40 +26,54 @@ logger = logging.getLogger(__name__)
 
 class IDataHandler(ABC):
 
+    _OHLCV_REGEX = r'^([a-zA-Z_-]+)\-(\d+\S)\-?([a-zA-Z_]*)?(?=\.)'
+
     def __init__(self, datadir: Path) -> None:
         self._datadir = datadir
 
+    @classmethod
+    def _get_file_extension(cls) -> str:
+        """
+        Get file extension for this particular datahandler
+        """
+        raise NotImplementedError()
+
     @abstractclassmethod
-    def ohlcv_get_available_data(cls, datadir: Path) -> ListPairsWithTimeframes:
+    def ohlcv_get_available_data(
+            cls, datadir: Path, trading_mode: TradingMode) -> ListPairsWithTimeframes:
         """
         Returns a list of all pairs with ohlcv data available in this datadir
         :param datadir: Directory to search for ohlcv files
+        :param trading_mode: trading-mode to be used
         :return: List of Tuples of (pair, timeframe)
         """
 
     @abstractclassmethod
-    def ohlcv_get_pairs(cls, datadir: Path, timeframe: str) -> List[str]:
+    def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
         """
         Returns a list of all pairs with ohlcv data available in this datadir
         for the specified timeframe
         :param datadir: Directory to search for ohlcv files
         :param timeframe: Timeframe to search pairs for
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: List of Pairs
         """
 
     @abstractmethod
-    def ohlcv_store(self, pair: str, timeframe: str, data: DataFrame) -> None:
+    def ohlcv_store(
+            self, pair: str, timeframe: str, data: DataFrame, candle_type: CandleType) -> None:
         """
         Store ohlcv data.
         :param pair: Pair - used to generate filename
         :param timeframe: Timeframe - used to generate filename
         :param data: Dataframe containing OHLCV data
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: None
         """
 
     @abstractmethod
-    def _ohlcv_load(self, pair: str, timeframe: str,
-                    timerange: Optional[TimeRange] = None,
+    def _ohlcv_load(self, pair: str, timeframe: str, timerange: Optional[TimeRange],
+                    candle_type: CandleType
                     ) -> DataFrame:
         """
         Internal method used to load data for one pair from disk.
@@ -67,25 +84,38 @@ class IDataHandler(ABC):
         :param timerange: Limit data to be loaded to this timerange.
                         Optionally implemented by subclasses to avoid loading
                         all data where possible.
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: DataFrame with ohlcv data, or empty DataFrame
         """
 
-    @abstractmethod
-    def ohlcv_purge(self, pair: str, timeframe: str) -> bool:
+    def ohlcv_purge(self, pair: str, timeframe: str, candle_type: CandleType) -> bool:
         """
         Remove data for this pair
         :param pair: Delete data for this pair.
         :param timeframe: Timeframe (e.g. "5m")
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: True when deleted, false if file did not exist.
         """
+        filename = self._pair_data_filename(self._datadir, pair, timeframe, candle_type)
+        if filename.exists():
+            filename.unlink()
+            return True
+        return False
 
     @abstractmethod
-    def ohlcv_append(self, pair: str, timeframe: str, data: DataFrame) -> None:
+    def ohlcv_append(
+        self,
+        pair: str,
+        timeframe: str,
+        data: DataFrame,
+        candle_type: CandleType
+    ) -> None:
         """
         Append data to existing data structures
         :param pair: Pair
         :param timeframe: Timeframe this ohlcv data is for
         :param data: Data to append.
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         """
 
     @abstractclassmethod
@@ -123,13 +153,17 @@ class IDataHandler(ABC):
         :return: List of trades
         """
 
-    @abstractmethod
     def trades_purge(self, pair: str) -> bool:
         """
         Remove data for this pair
         :param pair: Delete data for this pair.
         :return: True when deleted, false if file did not exist.
         """
+        filename = self._pair_trades_filename(self._datadir, pair)
+        if filename.exists():
+            filename.unlink()
+            return True
+        return False
 
     def trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> TradeList:
         """
@@ -141,12 +175,55 @@ class IDataHandler(ABC):
         """
         return trades_remove_duplicates(self._trades_load(pair, timerange=timerange))
 
+    @classmethod
+    def create_dir_if_needed(cls, datadir: Path):
+        """
+        Creates datadir if necessary
+        should only create directories for "futures" mode at the moment.
+        """
+        if not datadir.parent.is_dir():
+            datadir.parent.mkdir()
+
+    @classmethod
+    def _pair_data_filename(
+        cls,
+        datadir: Path,
+        pair: str,
+        timeframe: str,
+        candle_type: CandleType
+    ) -> Path:
+        pair_s = misc.pair_to_filename(pair)
+        candle = ""
+        if candle_type != CandleType.SPOT:
+            datadir = datadir.joinpath('futures')
+            candle = f"-{candle_type}"
+        filename = datadir.joinpath(
+            f'{pair_s}-{timeframe}{candle}.{cls._get_file_extension()}')
+        return filename
+
+    @classmethod
+    def _pair_trades_filename(cls, datadir: Path, pair: str) -> Path:
+        pair_s = misc.pair_to_filename(pair)
+        filename = datadir.joinpath(f'{pair_s}-trades.{cls._get_file_extension()}')
+        return filename
+
+    @staticmethod
+    def rebuild_pair_from_filename(pair: str) -> str:
+        """
+        Rebuild pair name from filename
+        Assumes a asset name of max. 7 length to also support BTC-PERP and BTC-PERP:USD names.
+        """
+        res = re.sub(r'^(([A-Za-z]{1,10})|^([A-Za-z\-]{1,6}))(_)', r'\g<1>/', pair, 1)
+        res = re.sub('_', ':', res, 1)
+        return res
+
     def ohlcv_load(self, pair, timeframe: str,
+                   candle_type: CandleType,
                    timerange: Optional[TimeRange] = None,
                    fill_missing: bool = True,
                    drop_incomplete: bool = True,
                    startup_candles: int = 0,
-                   warn_no_data: bool = True
+                   warn_no_data: bool = True,
                    ) -> DataFrame:
         """
         Load cached candle (OHLCV) data for the given pair.
@@ -158,6 +235,7 @@ class IDataHandler(ABC):
         :param drop_incomplete: Drop last candle assuming it may be incomplete.
         :param startup_candles: Additional candles to load at the start of the period
         :param warn_no_data: Log a warning message when no data is found
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: DataFrame with ohlcv data, or empty DataFrame
         """
         # Fix startup period
@@ -165,17 +243,21 @@ class IDataHandler(ABC):
         if startup_candles > 0 and timerange_startup:
             timerange_startup.subtract_start(timeframe_to_seconds(timeframe) * startup_candles)
 
-        pairdf = self._ohlcv_load(pair, timeframe,
-                                  timerange=timerange_startup)
-        if self._check_empty_df(pairdf, pair, timeframe, warn_no_data):
+        pairdf = self._ohlcv_load(
+            pair,
+            timeframe,
+            timerange=timerange_startup,
+            candle_type=candle_type
+        )
+        if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
             return pairdf
         else:
             enddate = pairdf.iloc[-1]['date']
 
             if timerange_startup:
-                self._validate_pairdata(pair, pairdf, timerange_startup)
+                self._validate_pairdata(pair, pairdf, timeframe, candle_type, timerange_startup)
                 pairdf = trim_dataframe(pairdf, timerange_startup)
-                if self._check_empty_df(pairdf, pair, timeframe, warn_no_data):
+                if self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data):
                     return pairdf
 
             # incomplete candles should only be dropped if we didn't trim the end beforehand.
@@ -184,23 +266,25 @@ class IDataHandler(ABC):
                                            fill_missing=fill_missing,
                                            drop_incomplete=(drop_incomplete and
                                                             enddate == pairdf.iloc[-1]['date']))
-            self._check_empty_df(pairdf, pair, timeframe, warn_no_data)
+            self._check_empty_df(pairdf, pair, timeframe, candle_type, warn_no_data)
             return pairdf
 
-    def _check_empty_df(self, pairdf: DataFrame, pair: str, timeframe: str, warn_no_data: bool):
+    def _check_empty_df(self, pairdf: DataFrame, pair: str, timeframe: str,
+                        candle_type: CandleType, warn_no_data: bool):
         """
         Warn on empty dataframe
         """
         if pairdf.empty:
             if warn_no_data:
                 logger.warning(
-                    f'No history data for pair: "{pair}", timeframe: {timeframe}. '
-                    'Use `freqtrade download-data` to download the data'
+                    f"No history for {pair}, {candle_type}, {timeframe} found. "
+                    "Use `freqtrade download-data` to download the data"
                 )
             return True
         return False
 
-    def _validate_pairdata(self, pair, pairdata: DataFrame, timerange: TimeRange):
+    def _validate_pairdata(self, pair, pairdata: DataFrame, timeframe: str,
+                           candle_type: CandleType, timerange: TimeRange):
         """
         Validates pairdata for missing data at start end end and logs warnings.
         :param pairdata: Dataframe to validate
@@ -210,12 +294,12 @@ class IDataHandler(ABC):
         if timerange.starttype == 'date':
             start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
             if pairdata.iloc[0]['date'] > start:
-                logger.warning(f"Missing data at start for pair {pair}, "
+                logger.warning(f"{pair}, {candle_type}, {timeframe}, "
                                f"data starts at {pairdata.iloc[0]['date']:%Y-%m-%d %H:%M:%S}")
         if timerange.stoptype == 'date':
             stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
             if pairdata.iloc[-1]['date'] < stop:
-                logger.warning(f"Missing data at end for pair {pair}, "
+                logger.warning(f"{pair}, {candle_type}, {timeframe}, "
                                f"data ends at {pairdata.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}")
 
 
diff --git a/freqtrade/data/history/jsondatahandler.py b/freqtrade/data/history/jsondatahandler.py
index 24d6e814b..23054ac51 100644
--- a/freqtrade/data/history/jsondatahandler.py
+++ b/freqtrade/data/history/jsondatahandler.py
@@ -10,6 +10,7 @@ from freqtrade import misc
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, ListPairsWithTimeframes, TradeList
 from freqtrade.data.converter import trades_dict_to_list
+from freqtrade.enums import CandleType, TradingMode
 
 from .idatahandler import IDataHandler
 
@@ -23,33 +24,49 @@ class JsonDataHandler(IDataHandler):
     _columns = DEFAULT_DATAFRAME_COLUMNS
 
     @classmethod
-    def ohlcv_get_available_data(cls, datadir: Path) -> ListPairsWithTimeframes:
+    def ohlcv_get_available_data(
+            cls, datadir: Path, trading_mode: TradingMode) -> ListPairsWithTimeframes:
         """
         Returns a list of all pairs with ohlcv data available in this datadir
         :param datadir: Directory to search for ohlcv files
+        :param trading_mode: trading-mode to be used
         :return: List of Tuples of (pair, timeframe)
         """
-        _tmp = [re.search(r'^([a-zA-Z_]+)\-(\d+\S+)(?=.json)', p.name)
-                for p in datadir.glob(f"*.{cls._get_file_extension()}")]
-        return [(match[1].replace('_', '/'), match[2]) for match in _tmp
-                if match and len(match.groups()) > 1]
+        if trading_mode == 'futures':
+            datadir = datadir.joinpath('futures')
+        _tmp = [
+            re.search(
+                cls._OHLCV_REGEX, p.name
+            ) for p in datadir.glob(f"*.{cls._get_file_extension()}")]
+        return [
+            (
+                cls.rebuild_pair_from_filename(match[1]),
+                match[2],
+                CandleType.from_string(match[3])
+            ) for match in _tmp if match and len(match.groups()) > 1]
 
     @classmethod
-    def ohlcv_get_pairs(cls, datadir: Path, timeframe: str) -> List[str]:
+    def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
         """
         Returns a list of all pairs with ohlcv data available in this datadir
         for the specified timeframe
         :param datadir: Directory to search for ohlcv files
         :param timeframe: Timeframe to search pairs for
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: List of Pairs
         """
+        candle = ""
+        if candle_type != CandleType.SPOT:
+            datadir = datadir.joinpath('futures')
+            candle = f"-{candle_type}"
 
-        _tmp = [re.search(r'^(\S+)(?=\-' + timeframe + '.json)', p.name)
-                for p in datadir.glob(f"*{timeframe}.{cls._get_file_extension()}")]
+        _tmp = [re.search(r'^(\S+)(?=\-' + timeframe + candle + '.json)', p.name)
+                for p in datadir.glob(f"*{timeframe}{candle}.{cls._get_file_extension()}")]
         # Check if regex found something and only return these results
-        return [match[0].replace('_', '/') for match in _tmp if match]
+        return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
 
-    def ohlcv_store(self, pair: str, timeframe: str, data: DataFrame) -> None:
+    def ohlcv_store(
+            self, pair: str, timeframe: str, data: DataFrame, candle_type: CandleType) -> None:
         """
         Store data in json format "values".
             format looks as follows:
@@ -57,9 +74,11 @@ class JsonDataHandler(IDataHandler):
         :param pair: Pair - used to generate filename
         :param timeframe: Timeframe - used to generate filename
         :param data: Dataframe containing OHLCV data
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: None
         """
-        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+        filename = self._pair_data_filename(self._datadir, pair, timeframe, candle_type)
+        self.create_dir_if_needed(filename)
         _data = data.copy()
         # Convert date to int
         _data['date'] = _data['date'].view(np.int64) // 1000 // 1000
@@ -70,7 +89,7 @@ class JsonDataHandler(IDataHandler):
             compression='gzip' if self._use_zip else None)
 
     def _ohlcv_load(self, pair: str, timeframe: str,
-                    timerange: Optional[TimeRange] = None,
+                    timerange: Optional[TimeRange], candle_type: CandleType
                     ) -> DataFrame:
         """
         Internal method used to load data for one pair from disk.
@@ -81,9 +100,10 @@ class JsonDataHandler(IDataHandler):
         :param timerange: Limit data to be loaded to this timerange.
                         Optionally implemented by subclasses to avoid loading
                         all data where possible.
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: DataFrame with ohlcv data, or empty DataFrame
         """
-        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+        filename = self._pair_data_filename(self._datadir, pair, timeframe, candle_type=candle_type)
         if not filename.exists():
             return DataFrame(columns=self._columns)
         try:
@@ -100,25 +120,19 @@ class JsonDataHandler(IDataHandler):
                                        infer_datetime_format=True)
         return pairdata
 
-    def ohlcv_purge(self, pair: str, timeframe: str) -> bool:
-        """
-        Remove data for this pair
-        :param pair: Delete data for this pair.
-        :param timeframe: Timeframe (e.g. "5m")
-        :return: True when deleted, false if file did not exist.
-        """
-        filename = self._pair_data_filename(self._datadir, pair, timeframe)
-        if filename.exists():
-            filename.unlink()
-            return True
-        return False
-
-    def ohlcv_append(self, pair: str, timeframe: str, data: DataFrame) -> None:
+    def ohlcv_append(
+        self,
+        pair: str,
+        timeframe: str,
+        data: DataFrame,
+        candle_type: CandleType
+    ) -> None:
         """
         Append data to existing data structures
         :param pair: Pair
         :param timeframe: Timeframe this ohlcv data is for
         :param data: Data to append.
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         """
         raise NotImplementedError()
 
@@ -132,7 +146,7 @@ class JsonDataHandler(IDataHandler):
         _tmp = [re.search(r'^(\S+)(?=\-trades.json)', p.name)
                 for p in datadir.glob(f"*trades.{cls._get_file_extension()}")]
         # Check if regex found something and only return these results to avoid exceptions.
-        return [match[0].replace('_', '/') for match in _tmp if match]
+        return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
 
     def trades_store(self, pair: str, data: TradeList) -> None:
         """
@@ -174,34 +188,10 @@ class JsonDataHandler(IDataHandler):
             pass
         return tradesdata
 
-    def trades_purge(self, pair: str) -> bool:
-        """
-        Remove data for this pair
-        :param pair: Delete data for this pair.
-        :return: True when deleted, false if file did not exist.
-        """
-        filename = self._pair_trades_filename(self._datadir, pair)
-        if filename.exists():
-            filename.unlink()
-            return True
-        return False
-
-    @classmethod
-    def _pair_data_filename(cls, datadir: Path, pair: str, timeframe: str) -> Path:
-        pair_s = misc.pair_to_filename(pair)
-        filename = datadir.joinpath(f'{pair_s}-{timeframe}.{cls._get_file_extension()}')
-        return filename
-
     @classmethod
     def _get_file_extension(cls):
         return "json.gz" if cls._use_zip else "json"
 
-    @classmethod
-    def _pair_trades_filename(cls, datadir: Path, pair: str) -> Path:
-        pair_s = misc.pair_to_filename(pair)
-        filename = datadir.joinpath(f'{pair_s}-trades.{cls._get_file_extension()}')
-        return filename
-
 
 class JsonGzDataHandler(JsonDataHandler):
 
diff --git a/freqtrade/edge/edge_positioning.py b/freqtrade/edge/edge_positioning.py
index 1950f0d08..2fe41a17b 100644
--- a/freqtrade/edge/edge_positioning.py
+++ b/freqtrade/edge/edge_positioning.py
@@ -13,7 +13,7 @@ from pandas import DataFrame
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import DATETIME_PRINT_FORMAT, UNLIMITED_STAKE_AMOUNT
 from freqtrade.data.history import get_timerange, load_data, refresh_data
-from freqtrade.enums import RunMode, SellType
+from freqtrade.enums import CandleType, ExitType, RunMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.exchange.exchange import timeframe_to_seconds
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
@@ -116,11 +116,12 @@ class Edge:
                 timeframe=self.strategy.timeframe,
                 timerange=timerange_startup,
                 data_format=self.config.get('dataformat_ohlcv', 'json'),
+                candle_type=self.config.get('candle_type_def', CandleType.SPOT),
             )
             # Download informative pairs too
             res = defaultdict(list)
-            for p, t in self.strategy.gather_informative_pairs():
-                res[t].append(p)
+            for pair, timeframe, _ in self.strategy.gather_informative_pairs():
+                res[timeframe].append(pair)
             for timeframe, inf_pairs in res.items():
                 timerange_startup = deepcopy(self._timerange)
                 timerange_startup.subtract_start(timeframe_to_seconds(
@@ -132,6 +133,7 @@ class Edge:
                     timeframe=timeframe,
                     timerange=timerange_startup,
                     data_format=self.config.get('dataformat_ohlcv', 'json'),
+                    candle_type=self.config.get('candle_type_def', CandleType.SPOT),
                 )
 
         data = load_data(
@@ -141,6 +143,7 @@ class Edge:
             timerange=self._timerange,
             startup_candles=self.strategy.startup_candle_count,
             data_format=self.config.get('dataformat_ohlcv', 'json'),
+            candle_type=self.config.get('candle_type_def', CandleType.SPOT),
         )
 
         if not data:
@@ -159,7 +162,9 @@ class Edge:
         logger.info(f'Measuring data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
                     f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
                     f'({(max_date - min_date).days} days)..')
-        headers = ['date', 'buy', 'open', 'close', 'sell', 'high', 'low']
+        # TODO: Should edge support shorts? needs to be investigated further
+        # * (add enter_short exit_short)
+        headers = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long']
 
         trades: list = []
         for pair, pair_data in preprocessed.items():
@@ -167,8 +172,13 @@ class Edge:
             pair_data = pair_data.sort_values(by=['date'])
             pair_data = pair_data.reset_index(drop=True)
 
-            df_analyzed = self.strategy.advise_sell(
-                self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
+            df_analyzed = self.strategy.advise_exit(
+                dataframe=self.strategy.advise_entry(
+                    dataframe=pair_data,
+                    metadata={'pair': pair}
+                ),
+                metadata={'pair': pair}
+            )[headers].copy()
 
             trades += self._find_trades_for_stoploss_range(df_analyzed, pair, self._stoploss_range)
 
@@ -219,9 +229,11 @@ class Edge:
         """
         final = []
         for pair, info in self._cached_pairs.items():
-            if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
-                info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)) and \
-                    pair in pairs:
+            if (
+                info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2))
+                and info.winrate > float(self.edge_config.get('minimum_winrate', 0.60))
+                and pair in pairs
+            ):
                 final.append(pair)
 
         if self._final_pairs != final:
@@ -246,8 +258,8 @@ class Edge:
         """
         final = []
         for pair, info in self._cached_pairs.items():
-            if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
-                    info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)):
+            if (info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and
+                    info.winrate > float(self.edge_config.get('minimum_winrate', 0.60))):
                 final.append({
                     'Pair': pair,
                     'Winrate': info.winrate,
@@ -382,8 +394,8 @@ class Edge:
         return final
 
     def _find_trades_for_stoploss_range(self, df, pair, stoploss_range):
-        buy_column = df['buy'].values
-        sell_column = df['sell'].values
+        buy_column = df['enter_long'].values
+        sell_column = df['exit_long'].values
         date_column = df['date'].values
         ohlc_columns = df[['open', 'high', 'low', 'close']].values
 
@@ -448,7 +460,7 @@ class Edge:
 
             if stop_index <= sell_index:
                 exit_index = open_trade_index + stop_index
-                exit_type = SellType.STOP_LOSS
+                exit_type = ExitType.STOP_LOSS
                 exit_price = stop_price
             elif stop_index > sell_index:
                 # If exit is SELL then we exit at the next candle
@@ -458,7 +470,7 @@ class Edge:
                 if len(ohlc_columns) - 1 < exit_index:
                     break
 
-                exit_type = SellType.SELL_SIGNAL
+                exit_type = ExitType.EXIT_SIGNAL
                 exit_price = ohlc_columns[exit_index, 0]
 
             trade = {'pair': pair,
diff --git a/freqtrade/enums/__init__.py b/freqtrade/enums/__init__.py
index d803baf31..e50ebc4a4 100644
--- a/freqtrade/enums/__init__.py
+++ b/freqtrade/enums/__init__.py
@@ -1,7 +1,12 @@
 # flake8: noqa: F401
 from freqtrade.enums.backteststate import BacktestState
+from freqtrade.enums.candletype import CandleType
+from freqtrade.enums.exitchecktuple import ExitCheckTuple
+from freqtrade.enums.exittype import ExitType
+from freqtrade.enums.marginmode import MarginMode
+from freqtrade.enums.ordertypevalue import OrderTypeValues
 from freqtrade.enums.rpcmessagetype import RPCMessageType
 from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode
-from freqtrade.enums.selltype import SellType
-from freqtrade.enums.signaltype import SignalTagType, SignalType
+from freqtrade.enums.signaltype import SignalDirection, SignalTagType, SignalType
 from freqtrade.enums.state import State
+from freqtrade.enums.tradingmode import TradingMode
diff --git a/freqtrade/enums/candletype.py b/freqtrade/enums/candletype.py
new file mode 100644
index 000000000..9d05ff6d7
--- /dev/null
+++ b/freqtrade/enums/candletype.py
@@ -0,0 +1,27 @@
+from enum import Enum
+
+
+class CandleType(str, Enum):
+    """Enum to distinguish candle types"""
+    SPOT = "spot"
+    FUTURES = "futures"
+    MARK = "mark"
+    INDEX = "index"
+    PREMIUMINDEX = "premiumIndex"
+
+    # TODO: Could take up less memory if these weren't a CandleType
+    FUNDING_RATE = "funding_rate"
+    # BORROW_RATE = "borrow_rate"  # * unimplemented
+
+    @staticmethod
+    def from_string(value: str) -> 'CandleType':
+        if not value:
+            # Default to spot
+            return CandleType.SPOT
+        return CandleType(value)
+
+    @staticmethod
+    def get_default(trading_mode: str) -> 'CandleType':
+        if trading_mode == 'futures':
+            return CandleType.FUTURES
+        return CandleType.SPOT
diff --git a/freqtrade/enums/exitchecktuple.py b/freqtrade/enums/exitchecktuple.py
new file mode 100644
index 000000000..c245a05da
--- /dev/null
+++ b/freqtrade/enums/exitchecktuple.py
@@ -0,0 +1,17 @@
+from freqtrade.enums.exittype import ExitType
+
+
+class ExitCheckTuple:
+    """
+    NamedTuple for Exit type + reason
+    """
+    exit_type: ExitType
+    exit_reason: str = ''
+
+    def __init__(self, exit_type: ExitType, exit_reason: str = ''):
+        self.exit_type = exit_type
+        self.exit_reason = exit_reason or exit_type.value
+
+    @property
+    def exit_flag(self):
+        return self.exit_type != ExitType.NONE
diff --git a/freqtrade/enums/selltype.py b/freqtrade/enums/exittype.py
similarity index 61%
rename from freqtrade/enums/selltype.py
rename to freqtrade/enums/exittype.py
index 015c30186..b2c5b62ea 100644
--- a/freqtrade/enums/selltype.py
+++ b/freqtrade/enums/exittype.py
@@ -1,18 +1,18 @@
 from enum import Enum
 
 
-class SellType(Enum):
+class ExitType(Enum):
     """
-    Enum to distinguish between sell reasons
+    Enum to distinguish between exit reasons
     """
     ROI = "roi"
     STOP_LOSS = "stop_loss"
     STOPLOSS_ON_EXCHANGE = "stoploss_on_exchange"
     TRAILING_STOP_LOSS = "trailing_stop_loss"
-    SELL_SIGNAL = "sell_signal"
-    FORCE_SELL = "force_sell"
-    EMERGENCY_SELL = "emergency_sell"
-    CUSTOM_SELL = "custom_sell"
+    EXIT_SIGNAL = "exit_signal"
+    FORCE_EXIT = "force_exit"
+    EMERGENCY_EXIT = "emergency_exit"
+    CUSTOM_EXIT = "custom_exit"
     NONE = ""
 
     def __str__(self):
diff --git a/freqtrade/enums/marginmode.py b/freqtrade/enums/marginmode.py
new file mode 100644
index 000000000..1e42809ea
--- /dev/null
+++ b/freqtrade/enums/marginmode.py
@@ -0,0 +1,12 @@
+from enum import Enum
+
+
+class MarginMode(Enum):
+    """
+    Enum to distinguish between
+    cross margin/futures margin_mode and
+    isolated margin/futures margin_mode
+    """
+    CROSS = "cross"
+    ISOLATED = "isolated"
+    NONE = ''
diff --git a/freqtrade/enums/ordertypevalue.py b/freqtrade/enums/ordertypevalue.py
new file mode 100644
index 000000000..9bb716171
--- /dev/null
+++ b/freqtrade/enums/ordertypevalue.py
@@ -0,0 +1,6 @@
+from enum import Enum
+
+
+class OrderTypeValues(str, Enum):
+    limit = 'limit'
+    market = 'market'
diff --git a/freqtrade/enums/rpcmessagetype.py b/freqtrade/enums/rpcmessagetype.py
index 4e3f693e5..584a011c2 100644
--- a/freqtrade/enums/rpcmessagetype.py
+++ b/freqtrade/enums/rpcmessagetype.py
@@ -5,12 +5,15 @@ class RPCMessageType(Enum):
     STATUS = 'status'
     WARNING = 'warning'
     STARTUP = 'startup'
-    BUY = 'buy'
-    BUY_FILL = 'buy_fill'
-    BUY_CANCEL = 'buy_cancel'
-    SELL = 'sell'
-    SELL_FILL = 'sell_fill'
-    SELL_CANCEL = 'sell_cancel'
+
+    ENTRY = 'entry'
+    ENTRY_FILL = 'entry_fill'
+    ENTRY_CANCEL = 'entry_cancel'
+
+    EXIT = 'exit'
+    EXIT_FILL = 'exit_fill'
+    EXIT_CANCEL = 'exit_cancel'
+
     PROTECTION_TRIGGER = 'protection_trigger'
     PROTECTION_TRIGGER_GLOBAL = 'protection_trigger_global'
 
diff --git a/freqtrade/enums/signaltype.py b/freqtrade/enums/signaltype.py
index d2995d57a..f706fd4dc 100644
--- a/freqtrade/enums/signaltype.py
+++ b/freqtrade/enums/signaltype.py
@@ -3,14 +3,22 @@ from enum import Enum
 
 class SignalType(Enum):
     """
-    Enum to distinguish between buy and sell signals
+    Enum to distinguish between enter and exit signals
     """
-    BUY = "buy"
-    SELL = "sell"
+    ENTER_LONG = "enter_long"
+    EXIT_LONG = "exit_long"
+    ENTER_SHORT = "enter_short"
+    EXIT_SHORT = "exit_short"
 
 
 class SignalTagType(Enum):
     """
     Enum for signal columns
     """
-    BUY_TAG = "buy_tag"
+    ENTER_TAG = "enter_tag"
+    EXIT_TAG = "exit_tag"
+
+
+class SignalDirection(str, Enum):
+    LONG = 'long'
+    SHORT = 'short'
diff --git a/freqtrade/enums/tradingmode.py b/freqtrade/enums/tradingmode.py
new file mode 100644
index 000000000..2f838b7c6
--- /dev/null
+++ b/freqtrade/enums/tradingmode.py
@@ -0,0 +1,11 @@
+from enum import Enum
+
+
+class TradingMode(str, Enum):
+    """
+    Enum to distinguish between
+    spot, margin, futures or any other trading method
+    """
+    SPOT = "spot"
+    MARGIN = "margin"
+    FUTURES = "futures"
diff --git a/freqtrade/exceptions.py b/freqtrade/exceptions.py
index 056be8720..6b0039a3f 100644
--- a/freqtrade/exceptions.py
+++ b/freqtrade/exceptions.py
@@ -1,5 +1,3 @@
-
-
 class FreqtradeException(Exception):
     """
     Freqtrade base exception. Handled at the outermost level.
diff --git a/freqtrade/exchange/__init__.py b/freqtrade/exchange/__init__.py
index b08213d28..2b9ed47ea 100644
--- a/freqtrade/exchange/__init__.py
+++ b/freqtrade/exchange/__init__.py
@@ -5,6 +5,7 @@ from freqtrade.exchange.exchange import Exchange
 # isort: on
 from freqtrade.exchange.bibox import Bibox
 from freqtrade.exchange.binance import Binance
+from freqtrade.exchange.bitpanda import Bitpanda
 from freqtrade.exchange.bittrex import Bittrex
 from freqtrade.exchange.bybit import Bybit
 from freqtrade.exchange.coinbasepro import Coinbasepro
@@ -17,5 +18,7 @@ from freqtrade.exchange.exchange import (available_exchanges, ccxt_exchanges,
 from freqtrade.exchange.ftx import Ftx
 from freqtrade.exchange.gateio import Gateio
 from freqtrade.exchange.hitbtc import Hitbtc
+from freqtrade.exchange.huobi import Huobi
 from freqtrade.exchange.kraken import Kraken
 from freqtrade.exchange.kucoin import Kucoin
+from freqtrade.exchange.okx import Okx
diff --git a/freqtrade/exchange/bibox.py b/freqtrade/exchange/bibox.py
index f0c2dd00b..da1effbfe 100644
--- a/freqtrade/exchange/bibox.py
+++ b/freqtrade/exchange/bibox.py
@@ -20,4 +20,9 @@ class Bibox(Exchange):
 
     # fetchCurrencies API point requires authentication for Bibox,
     # so switch it off for Freqtrade load_markets()
-    _ccxt_config: Dict = {"has": {"fetchCurrencies": False}}
+    @property
+    def _ccxt_config(self) -> Dict:
+        # Parameters to add directly to ccxt sync/async initialization.
+        config = {"has": {"fetchCurrencies": False}}
+        config.update(super()._ccxt_config)
+        return config
diff --git a/freqtrade/exchange/binance.py b/freqtrade/exchange/binance.py
index 8dced3894..8c442cd26 100644
--- a/freqtrade/exchange/binance.py
+++ b/freqtrade/exchange/binance.py
@@ -1,14 +1,18 @@
 """ Binance exchange subclass """
+import json
 import logging
-from typing import Dict, List
+from datetime import datetime
+from pathlib import Path
+from typing import Dict, List, Optional, Tuple
 
 import arrow
 import ccxt
 
-from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
-                                  OperationalException, TemporaryError)
+from freqtrade.enums import CandleType, MarginMode, TradingMode
+from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError
 from freqtrade.exchange import Exchange
 from freqtrade.exchange.common import retrier
+from freqtrade.misc import deep_merge_dicts
 
 
 logger = logging.getLogger(__name__)
@@ -18,93 +22,186 @@ class Binance(Exchange):
 
     _ft_has: Dict = {
         "stoploss_on_exchange": True,
+        "stoploss_order_types": {"limit": "stop_loss_limit"},
         "order_time_in_force": ['gtc', 'fok', 'ioc'],
         "time_in_force_parameter": "timeInForce",
         "ohlcv_candle_limit": 1000,
         "trades_pagination": "id",
         "trades_pagination_arg": "fromId",
         "l2_limit_range": [5, 10, 20, 50, 100, 500, 1000],
+        "ccxt_futures_name": "future"
+    }
+    _ft_has_futures: Dict = {
+        "stoploss_order_types": {"limit": "stop"},
+        "tickers_have_price": False,
     }
 
-    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+    _supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
+        # TradingMode.SPOT always supported and not required in this list
+        # (TradingMode.MARGIN, MarginMode.CROSS),
+        # (TradingMode.FUTURES, MarginMode.CROSS),
+        (TradingMode.FUTURES, MarginMode.ISOLATED)
+    ]
+
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
         """
         Verify stop_loss against stoploss-order value (limit or price)
         Returns True if adjustment is necessary.
+        :param side: "buy" or "sell"
         """
-        return order['type'] == 'stop_loss_limit' and stop_loss > float(order['info']['stopPrice'])
 
-    @retrier(retries=0)
-    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+        ordertype = 'stop' if self.trading_mode == TradingMode.FUTURES else 'stop_loss_limit'
+
+        return order['type'] == ordertype and (
+            (side == "sell" and stop_loss > float(order['info']['stopPrice'])) or
+            (side == "buy" and stop_loss < float(order['info']['stopPrice']))
+        )
+
+    def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
+        tickers = super().get_tickers(symbols=symbols, cached=cached)
+        if self.trading_mode == TradingMode.FUTURES:
+            # Binance's future result has no bid/ask values.
+            # Therefore we must fetch that from fetch_bids_asks and combine the two results.
+            bidsasks = self.fetch_bids_asks(symbols, cached)
+            tickers = deep_merge_dicts(bidsasks, tickers, allow_null_overrides=False)
+        return tickers
+
+    @retrier
+    def _set_leverage(
+        self,
+        leverage: float,
+        pair: Optional[str] = None,
+        trading_mode: Optional[TradingMode] = None
+    ):
         """
-        creates a stoploss limit order.
-        this stoploss-limit is binance-specific.
-        It may work with a limited number of other exchanges, but this has not been tested yet.
+        Set's the leverage before making a trade, in order to not
+        have the same leverage on every trade
         """
-        # Limit price threshold: As limit price should always be below stop-price
-        limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
-        rate = stop_price * limit_price_pct
+        trading_mode = trading_mode or self.trading_mode
 
-        ordertype = "stop_loss_limit"
-
-        stop_price = self.price_to_precision(pair, stop_price)
-
-        # Ensure rate is less than stop price
-        if stop_price <= rate:
-            raise OperationalException(
-                'In stoploss limit order, stop price should be more than limit price')
-
-        if self._config['dry_run']:
-            dry_order = self.create_dry_run_order(
-                pair, ordertype, "sell", amount, stop_price)
-            return dry_order
+        if self._config['dry_run'] or trading_mode != TradingMode.FUTURES:
+            return
 
         try:
-            params = self._params.copy()
-            params.update({'stopPrice': stop_price})
-
-            amount = self.amount_to_precision(pair, amount)
-
-            rate = self.price_to_precision(pair, rate)
-
-            order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
-                                           amount=amount, price=rate, params=params)
-            logger.info('stoploss limit order added for %s. '
-                        'stop price: %s. limit: %s', pair, stop_price, rate)
-            self._log_exchange_response('create_stoploss_order', order)
-            return order
-        except ccxt.InsufficientFunds as e:
-            raise InsufficientFundsError(
-                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
-                f'Tried to sell amount {amount} at rate {rate}. '
-                f'Message: {e}') from e
-        except ccxt.InvalidOrder as e:
-            # Errors:
-            # `binance Order would trigger immediately.`
-            raise InvalidOrderException(
-                f'Could not create {ordertype} sell order on market {pair}. '
-                f'Tried to sell amount {amount} at rate {rate}. '
-                f'Message: {e}') from e
+            self._api.set_leverage(symbol=pair, leverage=round(leverage))
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
+                f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
 
     async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
-                                        since_ms: int, is_new_pair: bool
-                                        ) -> List:
+                                        since_ms: int, candle_type: CandleType,
+                                        is_new_pair: bool = False, raise_: bool = False,
+                                        ) -> Tuple[str, str, str, List]:
         """
         Overwrite to introduce "fast new pair" functionality by detecting the pair's listing date
         Does not work for other exchanges, which don't return the earliest data when called with "0"
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         """
         if is_new_pair:
-            x = await self._async_get_candle_history(pair, timeframe, 0)
-            if x and x[2] and x[2][0] and x[2][0][0] > since_ms:
+            x = await self._async_get_candle_history(pair, timeframe, candle_type, 0)
+            if x and x[3] and x[3][0] and x[3][0][0] > since_ms:
                 # Set starting date to first available candle.
-                since_ms = x[2][0][0]
+                since_ms = x[3][0][0]
                 logger.info(f"Candle-data for {pair} available starting with "
                             f"{arrow.get(since_ms // 1000).isoformat()}.")
+
         return await super()._async_get_historic_ohlcv(
-            pair=pair, timeframe=timeframe, since_ms=since_ms, is_new_pair=is_new_pair)
+            pair=pair,
+            timeframe=timeframe,
+            since_ms=since_ms,
+            is_new_pair=is_new_pair,
+            raise_=raise_,
+            candle_type=candle_type
+        )
+
+    def funding_fee_cutoff(self, open_date: datetime):
+        """
+        :param open_date: The open date for a trade
+        :return: The cutoff open time for when a funding fee is charged
+        """
+        return open_date.minute > 0 or (open_date.minute == 0 and open_date.second > 15)
+
+    def dry_run_liquidation_price(
+        self,
+        pair: str,
+        open_rate: float,   # Entry price of position
+        is_short: bool,
+        position: float,  # Absolute value of position size
+        wallet_balance: float,  # Or margin balance
+        mm_ex_1: float = 0.0,  # (Binance) Cross only
+        upnl_ex_1: float = 0.0,  # (Binance) Cross only
+    ) -> Optional[float]:
+        """
+        MARGIN: https://www.binance.com/en/support/faq/f6b010588e55413aa58b7d63ee0125ed
+        PERPETUAL: https://www.binance.com/en/support/faq/b3c689c1f50a44cabb3a84e663b81d93
+
+        :param exchange_name:
+        :param open_rate: (EP1) Entry price of position
+        :param is_short: True if the trade is a short, false otherwise
+        :param position: Absolute value of position size (in base currency)
+        :param wallet_balance: (WB)
+            Cross-Margin Mode: crossWalletBalance
+            Isolated-Margin Mode: isolatedWalletBalance
+        :param maintenance_amt:
+
+        # * Only required for Cross
+        :param mm_ex_1: (TMM)
+            Cross-Margin Mode: Maintenance Margin of all other contracts, excluding Contract 1
+            Isolated-Margin Mode: 0
+        :param upnl_ex_1: (UPNL)
+            Cross-Margin Mode: Unrealized PNL of all other contracts, excluding Contract 1.
+            Isolated-Margin Mode: 0
+        """
+
+        side_1 = -1 if is_short else 1
+        position = abs(position)
+        cross_vars = upnl_ex_1 - mm_ex_1 if self.margin_mode == MarginMode.CROSS else 0.0
+
+        # mm_ratio: Binance's formula specifies maintenance margin rate which is mm_ratio * 100%
+        # maintenance_amt: (CUM) Maintenance Amount of position
+        mm_ratio, maintenance_amt = self.get_maintenance_ratio_and_amt(pair, position)
+
+        if (maintenance_amt is None):
+            raise OperationalException(
+                "Parameter maintenance_amt is required by Binance.liquidation_price"
+                f"for {self.trading_mode.value}"
+            )
+
+        if self.trading_mode == TradingMode.FUTURES:
+            return (
+                (
+                    (wallet_balance + cross_vars + maintenance_amt) -
+                    (side_1 * position * open_rate)
+                ) / (
+                    (position * mm_ratio) - (side_1 * position)
+                )
+            )
+        else:
+            raise OperationalException(
+                "Freqtrade only supports isolated futures for leverage trading")
+
+    @retrier
+    def load_leverage_tiers(self) -> Dict[str, List[Dict]]:
+        if self.trading_mode == TradingMode.FUTURES:
+            if self._config['dry_run']:
+                leverage_tiers_path = (
+                    Path(__file__).parent / 'binance_leverage_tiers.json'
+                )
+                with open(leverage_tiers_path) as json_file:
+                    return json.load(json_file)
+            else:
+                try:
+                    return self._api.fetch_leverage_tiers()
+                except ccxt.DDoSProtection as e:
+                    raise DDosProtection(e) from e
+                except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+                    raise TemporaryError(f'Could not fetch leverage amounts due to'
+                                         f'{e.__class__.__name__}. Message: {e}') from e
+                except ccxt.BaseError as e:
+                    raise OperationalException(e) from e
+        else:
+            return {}
diff --git a/freqtrade/exchange/binance_leverage_tiers.json b/freqtrade/exchange/binance_leverage_tiers.json
new file mode 100644
index 000000000..c0bb965d0
--- /dev/null
+++ b/freqtrade/exchange/binance_leverage_tiers.json
@@ -0,0 +1,16481 @@
+{
+  "RAY/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 25,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "25",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5700.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11950.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ],
+  "SUSHI/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 50000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "50000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 50000,
+      "notionalCap": 150000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "150000",
+        "notionalFloor": "50000",
+        "maintMarginRatio": "0.025",
+        "cum": "750.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 150000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "250000",
+        "notionalFloor": "150000",
+        "maintMarginRatio": "0.05",
+        "cum": "4500.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 250000,
+      "notionalCap": 500000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "500000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.1",
+        "cum": "17000.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 500000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 4,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "4",
+        "notionalCap": "1000000",
+        "notionalFloor": "500000",
+        "maintMarginRatio": "0.125",
+        "cum": "29500.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 2000000,
+      "maintenanceMarginRate": 0.25,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "2",
+        "notionalCap": "2000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.25",
+        "cum": "154500.0"
+      }
+    },
+    {
+      "tier": 7,
+      "notionalFloor": 2000000,
+      "notionalCap": 50000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "7",
+        "initialLeverage": "1",
+        "notionalCap": "50000000",
+        "notionalFloor": "2000000",
+        "maintMarginRatio": "0.5",
+        "cum": "654500.0"
+      }
+    }
+  ],
+  "CVC/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5700.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11950.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ],
+  "BTS/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5700.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11950.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ],
+  "HOT/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5700.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11950.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ],
+  "ZRX/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5700.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11950.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ],
+  "QTUM/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5700.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11950.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ],
+  "IOTA/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
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+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ],
+  "CHZ/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.012,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.012",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "65.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "690.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5690.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11940.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386940.0"
+      }
+    }
+  ],
+  "LENDUSDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5700.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11950.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 9223372036854776000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "9223372036854775807",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ],
+  "ANKR/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.012,
+      "maxLeverage": 50,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "50",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.012",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "65.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "690.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5690.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11940.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386940.0"
+      }
+    }
+  ],
+  "DUSK/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 25,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "25",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5700.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11950.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ],
+  "CTSI/USDT": [
+    {
+      "tier": 1,
+      "notionalFloor": 0,
+      "notionalCap": 5000,
+      "maintenanceMarginRate": 0.01,
+      "maxLeverage": 25,
+      "info": {
+        "bracket": "1",
+        "initialLeverage": "25",
+        "notionalCap": "5000",
+        "notionalFloor": "0",
+        "maintMarginRatio": "0.01",
+        "cum": "0.0"
+      }
+    },
+    {
+      "tier": 2,
+      "notionalFloor": 5000,
+      "notionalCap": 25000,
+      "maintenanceMarginRate": 0.025,
+      "maxLeverage": 20,
+      "info": {
+        "bracket": "2",
+        "initialLeverage": "20",
+        "notionalCap": "25000",
+        "notionalFloor": "5000",
+        "maintMarginRatio": "0.025",
+        "cum": "75.0"
+      }
+    },
+    {
+      "tier": 3,
+      "notionalFloor": 25000,
+      "notionalCap": 100000,
+      "maintenanceMarginRate": 0.05,
+      "maxLeverage": 10,
+      "info": {
+        "bracket": "3",
+        "initialLeverage": "10",
+        "notionalCap": "100000",
+        "notionalFloor": "25000",
+        "maintMarginRatio": "0.05",
+        "cum": "700.0"
+      }
+    },
+    {
+      "tier": 4,
+      "notionalFloor": 100000,
+      "notionalCap": 250000,
+      "maintenanceMarginRate": 0.1,
+      "maxLeverage": 5,
+      "info": {
+        "bracket": "4",
+        "initialLeverage": "5",
+        "notionalCap": "250000",
+        "notionalFloor": "100000",
+        "maintMarginRatio": "0.1",
+        "cum": "5700.0"
+      }
+    },
+    {
+      "tier": 5,
+      "notionalFloor": 250000,
+      "notionalCap": 1000000,
+      "maintenanceMarginRate": 0.125,
+      "maxLeverage": 2,
+      "info": {
+        "bracket": "5",
+        "initialLeverage": "2",
+        "notionalCap": "1000000",
+        "notionalFloor": "250000",
+        "maintMarginRatio": "0.125",
+        "cum": "11950.0"
+      }
+    },
+    {
+      "tier": 6,
+      "notionalFloor": 1000000,
+      "notionalCap": 30000000,
+      "maintenanceMarginRate": 0.5,
+      "maxLeverage": 1,
+      "info": {
+        "bracket": "6",
+        "initialLeverage": "1",
+        "notionalCap": "30000000",
+        "notionalFloor": "1000000",
+        "maintMarginRatio": "0.5",
+        "cum": "386950.0"
+      }
+    }
+  ]
+}
diff --git a/freqtrade/exchange/bitpanda.py b/freqtrade/exchange/bitpanda.py
new file mode 100644
index 000000000..4cac35ce8
--- /dev/null
+++ b/freqtrade/exchange/bitpanda.py
@@ -0,0 +1,37 @@
+""" Bitpanda exchange subclass """
+import logging
+from datetime import datetime, timezone
+from typing import Dict, List, Optional
+
+from freqtrade.exchange import Exchange
+
+
+logger = logging.getLogger(__name__)
+
+
+class Bitpanda(Exchange):
+    """
+    Bitpanda exchange class. Contains adjustments needed for Freqtrade to work
+    with this exchange.
+    """
+
+    def get_trades_for_order(self, order_id: str, pair: str, since: datetime,
+                             params: Optional[Dict] = None) -> List:
+        """
+        Fetch Orders using the "fetch_my_trades" endpoint and filter them by order-id.
+        The "since" argument passed in is coming from the database and is in UTC,
+        as timezone-native datetime object.
+        From the python documentation:
+            > Naive datetime instances are assumed to represent local time
+        Therefore, calling "since.timestamp()" will get the UTC timestamp, after applying the
+        transformation from local timezone to UTC.
+        This works for timezones UTC+ since then the result will contain trades from a few hours
+        instead of from the last 5 seconds, however fails for UTC- timezones,
+        since we're then asking for trades with a "since" argument in the future.
+
+        :param order_id order_id: Order-id as given when creating the order
+        :param pair: Pair the order is for
+        :param since: datetime object of the order creation time. Assumes object is in UTC.
+        """
+        params = {'to': int(datetime.now(timezone.utc).timestamp() * 1000)}
+        return super().get_trades_for_order(order_id, pair, since, params)
diff --git a/freqtrade/exchange/bybit.py b/freqtrade/exchange/bybit.py
index 163f8c44e..484b8b9d3 100644
--- a/freqtrade/exchange/bybit.py
+++ b/freqtrade/exchange/bybit.py
@@ -1,7 +1,8 @@
 """ Bybit exchange subclass """
 import logging
-from typing import Dict
+from typing import Dict, List, Tuple
 
+from freqtrade.enums import MarginMode, TradingMode
 from freqtrade.exchange import Exchange
 
 
@@ -20,4 +21,11 @@ class Bybit(Exchange):
 
     _ft_has: Dict = {
         "ohlcv_candle_limit": 200,
+        "ccxt_futures_name": "linear"
     }
+
+    _supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
+        # TradingMode.SPOT always supported and not required in this list
+        # (TradingMode.FUTURES, MarginMode.CROSS),
+        # (TradingMode.FUTURES, MarginMode.ISOLATED)
+    ]
diff --git a/freqtrade/exchange/common.py b/freqtrade/exchange/common.py
index 7b89adf06..4355662a8 100644
--- a/freqtrade/exchange/common.py
+++ b/freqtrade/exchange/common.py
@@ -4,9 +4,20 @@ import time
 from functools import wraps
 
 from freqtrade.exceptions import DDosProtection, RetryableOrderError, TemporaryError
+from freqtrade.mixins import LoggingMixin
 
 
 logger = logging.getLogger(__name__)
+__logging_mixin = None
+
+
+def _get_logging_mixin():
+    # Logging-mixin to cache kucoin responses
+    # Only to be used in retrier
+    global __logging_mixin
+    if not __logging_mixin:
+        __logging_mixin = LoggingMixin(logger)
+    return __logging_mixin
 
 
 # Maximum default retry count.
@@ -16,17 +27,27 @@ API_FETCH_ORDER_RETRY_COUNT = 5
 
 BAD_EXCHANGES = {
     "bitmex": "Various reasons.",
-    "bitstamp": "Does not provide history. "
-                "Details in https://github.com/freqtrade/freqtrade/issues/1983",
-    "phemex": "Does not provide history. ",
+    "phemex": "Does not provide history.",
+    "probit": "Requires additional, regular calls to `signIn()`.",
     "poloniex": "Does not provide fetch_order endpoint to fetch both open and closed orders.",
 }
 
 MAP_EXCHANGE_CHILDCLASS = {
     'binanceus': 'binance',
     'binanceje': 'binance',
+    'binanceusdm': 'binance',
+    'okex': 'okx',
 }
 
+SUPPORTED_EXCHANGES = [
+    'binance',
+    'bittrex',
+    'ftx',
+    'gateio',
+    'huobi',
+    'kraken',
+    'okx',
+]
 
 EXCHANGE_HAS_REQUIRED = [
     # Required / private
@@ -44,10 +65,17 @@ EXCHANGE_HAS_REQUIRED = [
 EXCHANGE_HAS_OPTIONAL = [
     # Private
     'fetchMyTrades',  # Trades for order - fee detection
+    # 'setLeverage',  # Margin/Futures trading
+    # 'setMarginMode',  # Margin/Futures trading
+    # 'fetchFundingHistory', # Futures trading
     # Public
     'fetchOrderBook', 'fetchL2OrderBook', 'fetchTicker',  # OR for pricing
     'fetchTickers',  # For volumepairlist?
     'fetchTrades',  # Downloading trades data
+    # 'fetchFundingRateHistory',  # Futures trading
+    # 'fetchPositions',  # Futures trading
+    # 'fetchLeverageTiers',  # Futures initialization
+    # 'fetchMarketLeverageTiers',  # Futures initialization
 ]
 
 
@@ -74,21 +102,33 @@ def calculate_backoff(retrycount, max_retries):
 def retrier_async(f):
     async def wrapper(*args, **kwargs):
         count = kwargs.pop('count', API_RETRY_COUNT)
+        kucoin = args[0].name == "KuCoin"  # Check if the exchange is KuCoin.
         try:
             return await f(*args, **kwargs)
         except TemporaryError as ex:
-            logger.warning('%s() returned exception: "%s"', f.__name__, ex)
+            msg = f'{f.__name__}() returned exception: "{ex}". '
             if count > 0:
-                logger.warning('retrying %s() still for %s times', f.__name__, count)
+                msg += f'Retrying still for {count} times.'
                 count -= 1
-                kwargs.update({'count': count})
+                kwargs['count'] = count
                 if isinstance(ex, DDosProtection):
-                    backoff_delay = calculate_backoff(count + 1, API_RETRY_COUNT)
-                    logger.info(f"Applying DDosProtection backoff delay: {backoff_delay}")
-                    await asyncio.sleep(backoff_delay)
+                    if kucoin and "429000" in str(ex):
+                        # Temporary fix for 429000 error on kucoin
+                        # see https://github.com/freqtrade/freqtrade/issues/5700 for details.
+                        _get_logging_mixin().log_once(
+                            f"Kucoin 429 error, avoid triggering DDosProtection backoff delay. "
+                            f"{count} tries left before giving up", logmethod=logger.warning)
+                        # Reset msg to avoid logging too many times.
+                        msg = ''
+                    else:
+                        backoff_delay = calculate_backoff(count + 1, API_RETRY_COUNT)
+                        logger.info(f"Applying DDosProtection backoff delay: {backoff_delay}")
+                        await asyncio.sleep(backoff_delay)
+                if msg:
+                    logger.warning(msg)
                 return await wrapper(*args, **kwargs)
             else:
-                logger.warning('Giving up retrying: %s()', f.__name__)
+                logger.warning(msg + 'Giving up.')
                 raise ex
     return wrapper
 
@@ -101,9 +141,9 @@ def retrier(_func=None, retries=API_RETRY_COUNT):
             try:
                 return f(*args, **kwargs)
             except (TemporaryError, RetryableOrderError) as ex:
-                logger.warning('%s() returned exception: "%s"', f.__name__, ex)
+                msg = f'{f.__name__}() returned exception: "{ex}". '
                 if count > 0:
-                    logger.warning('retrying %s() still for %s times', f.__name__, count)
+                    logger.warning(msg + f'Retrying still for {count} times.')
                     count -= 1
                     kwargs.update({'count': count})
                     if isinstance(ex, (DDosProtection, RetryableOrderError)):
@@ -113,7 +153,7 @@ def retrier(_func=None, retries=API_RETRY_COUNT):
                         time.sleep(backoff_delay)
                     return wrapper(*args, **kwargs)
                 else:
-                    logger.warning('Giving up retrying: %s()', f.__name__)
+                    logger.warning(msg + 'Giving up.')
                     raise ex
         return wrapper
     # Support both @retrier and @retrier(retries=2) syntax
diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index 2b9b08d70..e0da0878d 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -7,9 +7,9 @@ import http
 import inspect
 import logging
 from copy import deepcopy
-from datetime import datetime, timezone
+from datetime import datetime, timedelta, timezone
 from math import ceil
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any, Coroutine, Dict, List, Literal, Optional, Tuple, Union
 
 import arrow
 import ccxt
@@ -20,14 +20,16 @@ from ccxt.base.decimal_to_precision import (ROUND_DOWN, ROUND_UP, TICK_SIZE, TRU
 from pandas import DataFrame
 
 from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES,
-                                 ListPairsWithTimeframes)
+                                 EntryExit, ListPairsWithTimeframes, PairWithTimeframe)
 from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list
+from freqtrade.enums import OPTIMIZE_MODES, CandleType, MarginMode, TradingMode
 from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError,
                                   InvalidOrderException, OperationalException, PricingError,
                                   RetryableOrderError, TemporaryError)
 from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES,
                                        EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED,
-                                       remove_credentials, retrier, retrier_async)
+                                       SUPPORTED_EXCHANGES, remove_credentials, retrier,
+                                       retrier_async)
 from freqtrade.misc import chunks, deep_merge_dicts, safe_value_fallback2
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 
@@ -46,11 +48,6 @@ http.cookies.Morsel._reserved["samesite"] = "SameSite"  # type: ignore
 
 class Exchange:
 
-    _config: Dict = {}
-
-    # Parameters to add directly to ccxt sync/async initialization.
-    _ccxt_config: Dict = {}
-
     # Parameters to add directly to buy/sell calls (like agreeing to trading agreement)
     _params: Dict = {}
 
@@ -67,12 +64,25 @@ class Exchange:
         "ohlcv_params": {},
         "ohlcv_candle_limit": 500,
         "ohlcv_partial_candle": True,
+        # Check https://github.com/ccxt/ccxt/issues/10767 for removal of ohlcv_volume_currency
+        "ohlcv_volume_currency": "base",  # "base" or "quote"
+        "tickers_have_quoteVolume": True,
+        "tickers_have_price": True,
         "trades_pagination": "time",  # Possible are "time" or "id"
         "trades_pagination_arg": "since",
         "l2_limit_range": None,
         "l2_limit_range_required": True,  # Allow Empty L2 limit (kucoin)
+        "mark_ohlcv_price": "mark",
+        "mark_ohlcv_timeframe": "8h",
+        "ccxt_futures_name": "swap",
+        "needs_trading_fees": False,  # use fetch_trading_fees to cache fees
     }
     _ft_has: Dict = {}
+    _ft_has_futures: Dict = {}
+
+    _supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
+        # TradingMode.SPOT always supported and not required in this list
+    ]
 
     def __init__(self, config: Dict[str, Any], validate: bool = True) -> None:
         """
@@ -83,24 +93,29 @@ class Exchange:
         self._api: ccxt.Exchange = None
         self._api_async: ccxt_async.Exchange = None
         self._markets: Dict = {}
+        self._trading_fees: Dict[str, Any] = {}
+        self._leverage_tiers: Dict[str, List[Dict]] = {}
+        self.loop = asyncio.new_event_loop()
+        asyncio.set_event_loop(self.loop)
+        self._config: Dict = {}
 
         self._config.update(config)
 
         # Holds last candle refreshed time of each pair
-        self._pairs_last_refresh_time: Dict[Tuple[str, str], int] = {}
+        self._pairs_last_refresh_time: Dict[PairWithTimeframe, int] = {}
         # Timestamp of last markets refresh
         self._last_markets_refresh: int = 0
 
         # Cache for 10 minutes ...
-        self._fetch_tickers_cache: TTLCache = TTLCache(maxsize=1, ttl=60 * 10)
+        self._fetch_tickers_cache: TTLCache = TTLCache(maxsize=2, ttl=60 * 10)
         # Cache values for 1800 to avoid frequent polling of the exchange for prices
         # Caching only applies to RPC methods, so prices for open trades are still
         # refreshed once every iteration.
-        self._sell_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
-        self._buy_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
+        self._exit_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
+        self._entry_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
 
         # Holds candles
-        self._klines: Dict[Tuple[str, str], DataFrame] = {}
+        self._klines: Dict[PairWithTimeframe, DataFrame] = {}
 
         # Holds all open sell orders for dry_run
         self._dry_run_open_orders: Dict[str, Any] = {}
@@ -112,8 +127,19 @@ class Exchange:
         exchange_config = config['exchange']
         self.log_responses = exchange_config.get('log_responses', False)
 
+        # Leverage properties
+        self.trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT)
+        self.margin_mode: MarginMode = (
+            MarginMode(config.get('margin_mode'))
+            if config.get('margin_mode')
+            else MarginMode.NONE
+        )
+        self.liquidation_buffer = config.get('liquidation_buffer', 0.05)
+
         # Deep merge ft_has with default ft_has options
         self._ft_has = deep_merge_dicts(self._ft_has, deepcopy(self._ft_has_default))
+        if self.trading_mode == TradingMode.FUTURES:
+            self._ft_has = deep_merge_dicts(self._ft_has_futures, self._ft_has)
         if exchange_config.get('_ft_has_params'):
             self._ft_has = deep_merge_dicts(exchange_config.get('_ft_has_params'),
                                             self._ft_has)
@@ -126,13 +152,13 @@ class Exchange:
         self._trades_pagination_arg = self._ft_has['trades_pagination_arg']
 
         # Initialize ccxt objects
-        ccxt_config = self._ccxt_config.copy()
+        ccxt_config = self._ccxt_config
         ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}), ccxt_config)
         ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_sync_config', {}), ccxt_config)
 
         self._api = self._init_ccxt(exchange_config, ccxt_kwargs=ccxt_config)
 
-        ccxt_async_config = self._ccxt_config.copy()
+        ccxt_async_config = self._ccxt_config
         ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}),
                                              ccxt_async_config)
         ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_async_config', {}),
@@ -155,13 +181,19 @@ class Exchange:
                 self.validate_pairs(config['exchange']['pair_whitelist'])
             self.validate_ordertypes(config.get('order_types', {}))
             self.validate_order_time_in_force(config.get('order_time_in_force', {}))
-            self.validate_required_startup_candles(config.get('startup_candle_count', 0),
-                                                   config.get('timeframe', ''))
+            self.required_candle_call_count = self.validate_required_startup_candles(
+                config.get('startup_candle_count', 0), config.get('timeframe', ''))
+            self.validate_trading_mode_and_margin_mode(self.trading_mode, self.margin_mode)
+            self.validate_pricing(config['exit_pricing'])
+            self.validate_pricing(config['entry_pricing'])
 
         # Converts the interval provided in minutes in config to seconds
         self.markets_refresh_interval: int = exchange_config.get(
             "markets_refresh_interval", 60) * 60
 
+        if self.trading_mode != TradingMode.SPOT:
+            self.fill_leverage_tiers()
+
     def __del__(self):
         """
         Destructor - clean up async stuff
@@ -170,8 +202,10 @@ class Exchange:
 
     def close(self):
         logger.debug("Exchange object destroyed, closing async loop")
-        if self._api_async and inspect.iscoroutinefunction(self._api_async.close):
-            asyncio.get_event_loop().run_until_complete(self._api_async.close())
+        if (self._api_async and inspect.iscoroutinefunction(self._api_async.close)
+                and self._api_async.session):
+            logger.info("Closing async ccxt session.")
+            self.loop.run_until_complete(self._api_async.close())
 
     def _init_ccxt(self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt,
                    ccxt_kwargs: Dict = {}) -> ccxt.Exchange:
@@ -210,6 +244,24 @@ class Exchange:
 
         return api
 
+    @property
+    def _ccxt_config(self) -> Dict:
+        # Parameters to add directly to ccxt sync/async initialization.
+        if self.trading_mode == TradingMode.MARGIN:
+            return {
+                "options": {
+                    "defaultType": "margin"
+                }
+            }
+        elif self.trading_mode == TradingMode.FUTURES:
+            return {
+                "options": {
+                    "defaultType": self._ft_has["ccxt_futures_name"]
+                }
+            }
+        else:
+            return {}
+
     @property
     def name(self) -> str:
         """exchange Name (from ccxt)"""
@@ -254,12 +306,12 @@ class Exchange:
             timeframe, self._ft_has.get('ohlcv_candle_limit')))
 
     def get_markets(self, base_currencies: List[str] = None, quote_currencies: List[str] = None,
-                    pairs_only: bool = False, active_only: bool = False) -> Dict[str, Any]:
+                    spot_only: bool = False, margin_only: bool = False, futures_only: bool = False,
+                    tradable_only: bool = True,
+                    active_only: bool = False) -> Dict[str, Any]:
         """
         Return exchange ccxt markets, filtered out by base currency and quote currency
         if this was requested in parameters.
-
-        TODO: consider moving it to the Dataprovider
         """
         markets = self.markets
         if not markets:
@@ -269,8 +321,14 @@ class Exchange:
             markets = {k: v for k, v in markets.items() if v['base'] in base_currencies}
         if quote_currencies:
             markets = {k: v for k, v in markets.items() if v['quote'] in quote_currencies}
-        if pairs_only:
+        if tradable_only:
             markets = {k: v for k, v in markets.items() if self.market_is_tradable(v)}
+        if spot_only:
+            markets = {k: v for k, v in markets.items() if self.market_is_spot(v)}
+        if margin_only:
+            markets = {k: v for k, v in markets.items() if self.market_is_margin(v)}
+        if futures_only:
+            markets = {k: v for k, v in markets.items() if self.market_is_future(v)}
         if active_only:
             markets = {k: v for k, v in markets.items() if market_is_active(v)}
         return markets
@@ -283,36 +341,88 @@ class Exchange:
         return sorted(set([x['quote'] for _, x in markets.items()]))
 
     def get_pair_quote_currency(self, pair: str) -> str:
-        """
-        Return a pair's quote currency
-        """
+        """ Return a pair's quote currency (base/quote:settlement) """
         return self.markets.get(pair, {}).get('quote', '')
 
     def get_pair_base_currency(self, pair: str) -> str:
-        """
-        Return a pair's quote currency
-        """
+        """ Return a pair's base currency (base/quote:settlement) """
         return self.markets.get(pair, {}).get('base', '')
 
+    def market_is_future(self, market: Dict[str, Any]) -> bool:
+        return (
+            market.get(self._ft_has["ccxt_futures_name"], False) is True and
+            market.get('linear', False) is True
+        )
+
+    def market_is_spot(self, market: Dict[str, Any]) -> bool:
+        return market.get('spot', False) is True
+
+    def market_is_margin(self, market: Dict[str, Any]) -> bool:
+        return market.get('margin', False) is True
+
     def market_is_tradable(self, market: Dict[str, Any]) -> bool:
         """
         Check if the market symbol is tradable by Freqtrade.
-        By default, checks if it's splittable by `/` and both sides correspond to base / quote
+        Ensures that Configured mode aligns to
         """
-        symbol_parts = market['symbol'].split('/')
-        return (len(symbol_parts) == 2 and
-                len(symbol_parts[0]) > 0 and
-                len(symbol_parts[1]) > 0 and
-                symbol_parts[0] == market.get('base') and
-                symbol_parts[1] == market.get('quote')
-                )
+        return (
+            market.get('quote', None) is not None
+            and market.get('base', None) is not None
+            and ((self.trading_mode == TradingMode.SPOT and self.market_is_spot(market))
+                 or (self.trading_mode == TradingMode.MARGIN and self.market_is_margin(market))
+                 or (self.trading_mode == TradingMode.FUTURES and self.market_is_future(market)))
+        )
 
-    def klines(self, pair_interval: Tuple[str, str], copy: bool = True) -> DataFrame:
+    def klines(self, pair_interval: PairWithTimeframe, copy: bool = True) -> DataFrame:
         if pair_interval in self._klines:
             return self._klines[pair_interval].copy() if copy else self._klines[pair_interval]
         else:
             return DataFrame()
 
+    def _get_contract_size(self, pair: str) -> float:
+        if self.trading_mode == TradingMode.FUTURES:
+            market = self.markets[pair]
+            contract_size: float = 1.0
+            if market['contractSize'] is not None:
+                # ccxt has contractSize in markets as string
+                contract_size = float(market['contractSize'])
+            return contract_size
+        else:
+            return 1
+
+    def _trades_contracts_to_amount(self, trades: List) -> List:
+        if len(trades) > 0 and 'symbol' in trades[0]:
+            contract_size = self._get_contract_size(trades[0]['symbol'])
+            if contract_size != 1:
+                for trade in trades:
+                    trade['amount'] = trade['amount'] * contract_size
+        return trades
+
+    def _order_contracts_to_amount(self, order: Dict) -> Dict:
+        if 'symbol' in order and order['symbol'] is not None:
+            contract_size = self._get_contract_size(order['symbol'])
+            if contract_size != 1:
+                for prop in ['amount', 'cost', 'filled', 'remaining']:
+                    if prop in order and order[prop] is not None:
+                        order[prop] = order[prop] * contract_size
+        return order
+
+    def _amount_to_contracts(self, pair: str, amount: float) -> float:
+
+        contract_size = self._get_contract_size(pair)
+        if contract_size and contract_size != 1:
+            return amount / contract_size
+        else:
+            return amount
+
+    def _contracts_to_amount(self, pair: str, num_contracts: float) -> float:
+
+        contract_size = self._get_contract_size(pair)
+        if contract_size and contract_size != 1:
+            return num_contracts * contract_size
+        else:
+            return num_contracts
+
     def set_sandbox(self, api: ccxt.Exchange, exchange_config: dict, name: str) -> None:
         if exchange_config.get('sandbox'):
             if api.urls.get('test'):
@@ -326,7 +436,7 @@ class Exchange:
     def _load_async_markets(self, reload: bool = False) -> None:
         try:
             if self._api_async:
-                asyncio.get_event_loop().run_until_complete(
+                self.loop.run_until_complete(
                     self._api_async.load_markets(reload=reload))
 
         except (asyncio.TimeoutError, ccxt.BaseError) as e:
@@ -339,6 +449,9 @@ class Exchange:
             self._markets = self._api.load_markets()
             self._load_async_markets()
             self._last_markets_refresh = arrow.utcnow().int_timestamp
+            if self._ft_has['needs_trading_fees']:
+                self._trading_fees = self.fetch_trading_fees()
+
         except ccxt.BaseError:
             logger.exception('Unable to initialize markets.')
 
@@ -355,6 +468,7 @@ class Exchange:
             # Also reload async markets to avoid issues with newly listed pairs
             self._load_async_markets(reload=True)
             self._last_markets_refresh = arrow.utcnow().int_timestamp
+            self.fill_leverage_tiers()
         except ccxt.BaseError:
             logger.exception("Could not reload markets.")
 
@@ -370,7 +484,7 @@ class Exchange:
             raise OperationalException(
                 'Could not load markets, therefore cannot start. '
                 'Please investigate the above error for more details.'
-                )
+            )
         quote_currencies = self.get_quote_currencies()
         if stake_currency not in quote_currencies:
             raise OperationalException(
@@ -394,7 +508,7 @@ class Exchange:
             # Note: ccxt has BaseCurrency/QuoteCurrency format for pairs
             if self.markets and pair not in self.markets:
                 raise OperationalException(
-                    f'Pair {pair} is not available on {self.name}. '
+                    f'Pair {pair} is not available on {self.name} {self.trading_mode.value}. '
                     f'Please remove {pair} from your whitelist.')
 
                 # From ccxt Documentation:
@@ -462,6 +576,14 @@ class Exchange:
                 f'On exchange stoploss is not supported for {self.name}.'
             )
 
+    def validate_pricing(self, pricing: Dict) -> None:
+        if pricing.get('use_order_book', False) and not self.exchange_has('fetchL2OrderBook'):
+            raise OperationalException(f'Orderbook not available for {self.name}.')
+        if (not pricing.get('use_order_book', False) and (
+                not self.exchange_has('fetchTicker')
+                or not self._ft_has['tickers_have_price'])):
+            raise OperationalException(f'Ticker pricing not available for {self.name}.')
+
     def validate_order_time_in_force(self, order_time_in_force: Dict) -> None:
         """
         Checks if order time in force configured in strategy/config are supported
@@ -471,16 +593,48 @@ class Exchange:
             raise OperationalException(
                 f'Time in force policies are not supported for {self.name} yet.')
 
-    def validate_required_startup_candles(self, startup_candles: int, timeframe: str) -> None:
+    def validate_required_startup_candles(self, startup_candles: int, timeframe: str) -> int:
         """
         Checks if required startup_candles is more than ohlcv_candle_limit().
         Requires a grace-period of 5 candles - so a startup-period up to 494 is allowed by default.
         """
         candle_limit = self.ohlcv_candle_limit(timeframe)
-        if startup_candles + 5 > candle_limit:
+        # Require one more candle - to account for the still open candle.
+        candle_count = startup_candles + 1
+        # Allow 5 calls to the exchange per pair
+        required_candle_call_count = int(
+            (candle_count / candle_limit) + (0 if candle_count % candle_limit == 0 else 1))
+
+        if required_candle_call_count > 5:
+            # Only allow 5 calls per pair to somewhat limit the impact
             raise OperationalException(
-                f"This strategy requires {startup_candles} candles to start. "
-                f"{self.name} only provides {candle_limit} for {timeframe}.")
+                f"This strategy requires {startup_candles} candles to start, which is more than 5x "
+                f"the amount of candles {self.name} provides for {timeframe}.")
+
+        if required_candle_call_count > 1:
+            logger.warning(f"Using {required_candle_call_count} calls to get OHLCV. "
+                           f"This can result in slower operations for the bot. Please check "
+                           f"if you really need {startup_candles} candles for your strategy")
+        return required_candle_call_count
+
+    def validate_trading_mode_and_margin_mode(
+        self,
+        trading_mode: TradingMode,
+        margin_mode: Optional[MarginMode]  # Only None when trading_mode = TradingMode.SPOT
+    ):
+        """
+        Checks if freqtrade can perform trades using the configured
+        trading mode(Margin, Futures) and MarginMode(Cross, Isolated)
+        Throws OperationalException:
+            If the trading_mode/margin_mode type are not supported by freqtrade on this exchange
+        """
+        if trading_mode != TradingMode.SPOT and (
+            (trading_mode, margin_mode) not in self._supported_trading_mode_margin_pairs
+        ):
+            mm_value = margin_mode and margin_mode.value
+            raise OperationalException(
+                f"Freqtrade does not support {mm_value} {trading_mode.value} on {self.name}"
+            )
 
     def exchange_has(self, endpoint: str) -> bool:
         """
@@ -497,7 +651,7 @@ class Exchange:
         Re-implementation of ccxt internal methods - ensuring we can test the result is correct
         based on our definitions.
         """
-        if self.markets[pair]['precision']['amount']:
+        if self.markets[pair]['precision']['amount'] is not None:
             amount = float(decimal_to_precision(amount, rounding_mode=TRUNCATE,
                                                 precision=self.markets[pair]['precision']['amount'],
                                                 counting_mode=self.precisionMode,
@@ -523,7 +677,7 @@ class Exchange:
                 precision = self.markets[pair]['precision']['price']
                 missing = price % precision
                 if missing != 0:
-                    price = price - missing + precision
+                    price = round(price - missing + precision, 10)
             else:
                 symbol_prec = self.markets[pair]['precision']['price']
                 big_price = price * pow(10, symbol_prec)
@@ -541,28 +695,59 @@ class Exchange:
         else:
             return 1 / pow(10, precision)
 
-    def get_min_pair_stake_amount(self, pair: str, price: float,
-                                  stoploss: float) -> Optional[float]:
+    def get_min_pair_stake_amount(
+        self,
+        pair: str,
+        price: float,
+        stoploss: float,
+        leverage: Optional[float] = 1.0
+    ) -> Optional[float]:
+        return self._get_stake_amount_limit(pair, price, stoploss, 'min', leverage)
+
+    def get_max_pair_stake_amount(self, pair: str, price: float, leverage: float = 1.0) -> float:
+        max_stake_amount = self._get_stake_amount_limit(pair, price, 0.0, 'max')
+        if max_stake_amount is None:
+            # * Should never be executed
+            raise OperationalException(f'{self.name}.get_max_pair_stake_amount should'
+                                       'never set max_stake_amount to None')
+        return max_stake_amount / leverage
+
+    def _get_stake_amount_limit(
+        self,
+        pair: str,
+        price: float,
+        stoploss: float,
+        limit: Literal['min', 'max'],
+        leverage: Optional[float] = 1.0
+    ) -> Optional[float]:
+
+        isMin = limit == 'min'
+
         try:
             market = self.markets[pair]
         except KeyError:
             raise ValueError(f"Can't get market information for symbol {pair}")
 
-        if 'limits' not in market:
-            return None
-
-        min_stake_amounts = []
+        stake_limits = []
         limits = market['limits']
-        if ('cost' in limits and 'min' in limits['cost']
-                and limits['cost']['min'] is not None):
-            min_stake_amounts.append(limits['cost']['min'])
+        if (limits['cost'][limit] is not None):
+            stake_limits.append(
+                self._contracts_to_amount(
+                    pair,
+                    limits['cost'][limit]
+                )
+            )
 
-        if ('amount' in limits and 'min' in limits['amount']
-                and limits['amount']['min'] is not None):
-            min_stake_amounts.append(limits['amount']['min'] * price)
+        if (limits['amount'][limit] is not None):
+            stake_limits.append(
+                self._contracts_to_amount(
+                    pair,
+                    limits['amount'][limit] * price
+                )
+            )
 
-        if not min_stake_amounts:
-            return None
+        if not stake_limits:
+            return None if isMin else float('inf')
 
         # reserve some percent defined in config (5% default) + stoploss
         amount_reserve_percent = 1.0 + self._config.get('amount_reserve_percent',
@@ -576,12 +761,25 @@ class Exchange:
         # The value returned should satisfy both limits: for amount (base currency) and
         # for cost (quote, stake currency), so max() is used here.
         # See also #2575 at github.
-        return max(min_stake_amounts) * amount_reserve_percent
+        return self._get_stake_amount_considering_leverage(
+            max(stake_limits) * amount_reserve_percent,
+            leverage or 1.0
+        ) if isMin else min(stake_limits)
+
+    def _get_stake_amount_considering_leverage(self, stake_amount: float, leverage: float) -> float:
+        """
+        Takes the minimum stake amount for a pair with no leverage and returns the minimum
+        stake amount when leverage is considered
+        :param stake_amount: The stake amount for a pair before leverage is considered
+        :param leverage: The amount of leverage being used on the current trade
+        """
+        return stake_amount / leverage
 
     # Dry-run methods
 
     def create_dry_run_order(self, pair: str, ordertype: str, side: str, amount: float,
-                             rate: float, params: Dict = {}) -> Dict[str, Any]:
+                             rate: float, leverage: float, params: Dict = {},
+                             stop_loss: bool = False) -> Dict[str, Any]:
         order_id = f'dry_run_{side}_{datetime.now().timestamp()}'
         _amount = self.amount_to_precision(pair, amount)
         dry_order: Dict[str, Any] = {
@@ -590,25 +788,31 @@ class Exchange:
             'price': rate,
             'average': rate,
             'amount': _amount,
-            'cost': _amount * rate,
+            'cost': _amount * rate / leverage,
             'type': ordertype,
             'side': side,
+            'filled': 0,
             'remaining': _amount,
-            'datetime': arrow.utcnow().isoformat(),
+            'datetime': arrow.utcnow().strftime('%Y-%m-%dT%H:%M:%S.%fZ'),
             'timestamp': arrow.utcnow().int_timestamp * 1000,
-            'status': "closed" if ordertype == "market" else "open",
+            'status': "closed" if ordertype == "market" and not stop_loss else "open",
             'fee': None,
-            'info': {}
+            'info': {},
+            'leverage': leverage
         }
-        if dry_order["type"] in ["stop_loss_limit", "stop-loss-limit"]:
+        if stop_loss:
             dry_order["info"] = {"stopPrice": dry_order["price"]}
+            dry_order["stopPrice"] = dry_order["price"]
+            # Workaround to avoid filling stoploss orders immediately
+            dry_order["ft_order_type"] = "stoploss"
 
-        if dry_order["type"] == "market":
+        if dry_order["type"] == "market" and not dry_order.get("ft_order_type"):
             # Update market order pricing
             average = self.get_dry_market_fill_price(pair, side, amount, rate)
             dry_order.update({
                 'average': average,
-                'cost': dry_order['amount'] * average,
+                'filled': _amount,
+                'cost': (dry_order['amount'] * average) / leverage
             })
             dry_order = self.add_dry_order_fee(pair, dry_order)
 
@@ -639,7 +843,8 @@ class Exchange:
             max_slippage_val = rate * ((1 + slippage) if side == 'buy' else (1 - slippage))
 
             remaining_amount = amount
-            filled_amount = 0
+            filled_amount = 0.0
+            book_entry_price = 0.0
             for book_entry in ob[ob_type]:
                 book_entry_price = book_entry[0]
                 book_entry_coin_volume = book_entry[1]
@@ -672,23 +877,29 @@ class Exchange:
         if not self.exchange_has('fetchL2OrderBook'):
             return True
         ob = self.fetch_l2_order_book(pair, 1)
-        if side == 'buy':
-            price = ob['asks'][0][0]
-            logger.debug(f"{pair} checking dry buy-order: price={price}, limit={limit}")
-            if limit >= price:
-                return True
-        else:
-            price = ob['bids'][0][0]
-            logger.debug(f"{pair} checking dry sell-order: price={price}, limit={limit}")
-            if limit <= price:
-                return True
+        try:
+            if side == 'buy':
+                price = ob['asks'][0][0]
+                logger.debug(f"{pair} checking dry buy-order: price={price}, limit={limit}")
+                if limit >= price:
+                    return True
+            else:
+                price = ob['bids'][0][0]
+                logger.debug(f"{pair} checking dry sell-order: price={price}, limit={limit}")
+                if limit <= price:
+                    return True
+        except IndexError:
+            # Ignore empty orderbooks when filling - can be filled with the next iteration.
+            pass
         return False
 
     def check_dry_limit_order_filled(self, order: Dict[str, Any]) -> Dict[str, Any]:
         """
         Check dry-run limit order fill and update fee (if it filled).
         """
-        if order['status'] != "closed" and order['type'] in ["limit"]:
+        if (order['status'] != "closed"
+                and order['type'] in ["limit"]
+                and not order.get('ft_order_type')):
             pair = order['symbol']
             if self._is_dry_limit_order_filled(pair, order['side'], order['price']):
                 order.update({
@@ -716,28 +927,64 @@ class Exchange:
 
     # Order handling
 
-    def create_order(self, pair: str, ordertype: str, side: str, amount: float,
-                     rate: float, time_in_force: str = 'gtc') -> Dict:
-
-        if self._config['dry_run']:
-            dry_order = self.create_dry_run_order(pair, ordertype, side, amount, rate)
-            return dry_order
+    def _lev_prep(self, pair: str, leverage: float, side: str):
+        if self.trading_mode != TradingMode.SPOT:
+            self.set_margin_mode(pair, self.margin_mode)
+            self._set_leverage(leverage, pair)
 
+    def _get_params(
+        self,
+        ordertype: str,
+        leverage: float,
+        reduceOnly: bool,
+        time_in_force: str = 'gtc',
+    ) -> Dict:
         params = self._params.copy()
         if time_in_force != 'gtc' and ordertype != 'market':
             param = self._ft_has.get('time_in_force_parameter', '')
             params.update({param: time_in_force})
+        if reduceOnly:
+            params.update({'reduceOnly': True})
+        return params
+
+    def create_order(
+        self,
+        *,
+        pair: str,
+        ordertype: str,
+        side: str,
+        amount: float,
+        rate: float,
+        leverage: float,
+        reduceOnly: bool = False,
+        time_in_force: str = 'gtc',
+    ) -> Dict:
+        if self._config['dry_run']:
+            dry_order = self.create_dry_run_order(pair, ordertype, side, amount, rate, leverage)
+            return dry_order
+
+        params = self._get_params(ordertype, leverage, reduceOnly, time_in_force)
 
         try:
             # Set the precision for amount and price(rate) as accepted by the exchange
-            amount = self.amount_to_precision(pair, amount)
+            amount = self.amount_to_precision(pair, self._amount_to_contracts(pair, amount))
             needs_price = (ordertype != 'market'
                            or self._api.options.get("createMarketBuyOrderRequiresPrice", False))
             rate_for_order = self.price_to_precision(pair, rate) if needs_price else None
 
-            order = self._api.create_order(pair, ordertype, side,
-                                           amount, rate_for_order, params)
+            if not reduceOnly:
+                self._lev_prep(pair, leverage, side)
+
+            order = self._api.create_order(
+                pair,
+                ordertype,
+                side,
+                amount,
+                rate_for_order,
+                params,
+            )
             self._log_exchange_response('create_order', order)
+            order = self._order_contracts_to_amount(order)
             return order
 
         except ccxt.InsufficientFunds as e:
@@ -758,33 +1005,133 @@ class Exchange:
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
 
-    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
         """
         Verify stop_loss against stoploss-order value (limit or price)
         Returns True if adjustment is necessary.
         """
         raise OperationalException(f"stoploss is not implemented for {self.name}.")
 
-    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+    def _get_stop_order_type(self, user_order_type) -> Tuple[str, str]:
+
+        available_order_Types: Dict[str, str] = self._ft_has["stoploss_order_types"]
+
+        if user_order_type in available_order_Types.keys():
+            ordertype = available_order_Types[user_order_type]
+        else:
+            # Otherwise pick only one available
+            ordertype = list(available_order_Types.values())[0]
+            user_order_type = list(available_order_Types.keys())[0]
+        return ordertype, user_order_type
+
+    def _get_stop_limit_rate(self, stop_price: float, order_types: Dict, side: str) -> float:
+        # Limit price threshold: As limit price should always be below stop-price
+        limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
+        if side == "sell":
+            limit_rate = stop_price * limit_price_pct
+        else:
+            limit_rate = stop_price * (2 - limit_price_pct)
+
+        bad_stop_price = ((stop_price <= limit_rate) if side ==
+                          "sell" else (stop_price >= limit_rate))
+        # Ensure rate is less than stop price
+        if bad_stop_price:
+            raise OperationalException(
+                'In stoploss limit order, stop price should be more than limit price')
+        return limit_rate
+
+    def _get_stop_params(self, ordertype: str, stop_price: float) -> Dict:
+        params = self._params.copy()
+        # Verify if stopPrice works for your exchange!
+        params.update({'stopPrice': stop_price})
+        return params
+
+    @retrier(retries=0)
+    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict,
+                 side: str, leverage: float) -> Dict:
         """
         creates a stoploss order.
+        requires `_ft_has['stoploss_order_types']` to be set as a dict mapping limit and market
+            to the corresponding exchange type.
+
         The precise ordertype is determined by the order_types dict or exchange default.
-        Since ccxt does not unify stoploss-limit orders yet, this needs to be implemented in each
-        exchange's subclass.
+
         The exception below should never raise, since we disallow
         starting the bot in validate_ordertypes()
-        Note: Changes to this interface need to be applied to all sub-classes too.
-        """
 
-        raise OperationalException(f"stoploss is not implemented for {self.name}.")
+        This may work with a limited number of other exchanges, but correct working
+            needs to be tested individually.
+        WARNING: setting `stoploss_on_exchange` to True will NOT auto-enable stoploss on exchange.
+            `stoploss_adjust` must still be implemented for this to work.
+        """
+        if not self._ft_has['stoploss_on_exchange']:
+            raise OperationalException(f"stoploss is not implemented for {self.name}.")
+
+        user_order_type = order_types.get('stoploss', 'market')
+        ordertype, user_order_type = self._get_stop_order_type(user_order_type)
+
+        stop_price_norm = self.price_to_precision(pair, stop_price)
+        limit_rate = None
+        if user_order_type == 'limit':
+            limit_rate = self._get_stop_limit_rate(stop_price, order_types, side)
+            limit_rate = self.price_to_precision(pair, limit_rate)
+
+        if self._config['dry_run']:
+            dry_order = self.create_dry_run_order(
+                pair,
+                ordertype,
+                side,
+                amount,
+                stop_price_norm,
+                stop_loss=True,
+                leverage=leverage,
+            )
+            return dry_order
+
+        try:
+            params = self._get_stop_params(ordertype=ordertype, stop_price=stop_price_norm)
+            if self.trading_mode == TradingMode.FUTURES:
+                params['reduceOnly'] = True
+
+            amount = self.amount_to_precision(pair, self._amount_to_contracts(pair, amount))
+
+            self._lev_prep(pair, leverage, side)
+            order = self._api.create_order(symbol=pair, type=ordertype, side=side,
+                                           amount=amount, price=limit_rate, params=params)
+            self._log_exchange_response('create_stoploss_order', order)
+            order = self._order_contracts_to_amount(order)
+            logger.info(f"stoploss {user_order_type} order added for {pair}. "
+                        f"stop price: {stop_price}. limit: {limit_rate}")
+            return order
+        except ccxt.InsufficientFunds as e:
+            raise InsufficientFundsError(
+                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
+                f'Tried to sell amount {amount} at rate {limit_rate}. '
+                f'Message: {e}') from e
+        except ccxt.InvalidOrder as e:
+            # Errors:
+            # `Order would trigger immediately.`
+            raise InvalidOrderException(
+                f'Could not create {ordertype} sell order on market {pair}. '
+                f'Tried to sell amount {amount} at rate {limit_rate}. '
+                f'Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f"Could not place stoploss order due to {e.__class__.__name__}. "
+                f"Message: {e}") from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
 
     @retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
-    def fetch_order(self, order_id: str, pair: str) -> Dict:
+    def fetch_order(self, order_id: str, pair: str, params={}) -> Dict:
         if self._config['dry_run']:
             return self.fetch_dry_run_order(order_id)
         try:
-            order = self._api.fetch_order(order_id, pair)
+            order = self._api.fetch_order(order_id, pair, params=params)
             self._log_exchange_response('fetch_order', order)
+            order = self._order_contracts_to_amount(order)
             return order
         except ccxt.OrderNotFound as e:
             raise RetryableOrderError(
@@ -826,7 +1173,7 @@ class Exchange:
                 and order.get('filled') == 0.0)
 
     @retrier
-    def cancel_order(self, order_id: str, pair: str) -> Dict:
+    def cancel_order(self, order_id: str, pair: str, params={}) -> Dict:
         if self._config['dry_run']:
             try:
                 order = self.fetch_dry_run_order(order_id)
@@ -837,8 +1184,9 @@ class Exchange:
                 return {}
 
         try:
-            order = self._api.cancel_order(order_id, pair)
+            order = self._api.cancel_order(order_id, pair, params=params)
             self._log_exchange_response('cancel_order', order)
+            order = self._order_contracts_to_amount(order)
             return order
         except ccxt.InvalidOrder as e:
             raise InvalidOrderException(
@@ -927,7 +1275,72 @@ class Exchange:
             raise OperationalException(e) from e
 
     @retrier
-    def get_tickers(self, cached: bool = False) -> Dict:
+    def fetch_positions(self) -> List[Dict]:
+        if self._config['dry_run'] or self.trading_mode != TradingMode.FUTURES:
+            return []
+        try:
+            positions: List[Dict] = self._api.fetch_positions()
+            self._log_exchange_response('fetch_positions', positions)
+            return positions
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not get positions due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    @retrier
+    def fetch_trading_fees(self) -> Dict[str, Any]:
+        """
+        Fetch user account trading fees
+        Can be cached, should not update often.
+        """
+        if (self._config['dry_run'] or self.trading_mode != TradingMode.FUTURES
+                or not self.exchange_has('fetchTradingFees')):
+            return {}
+        try:
+            trading_fees: Dict[str, Any] = self._api.fetch_trading_fees()
+            self._log_exchange_response('fetch_trading_fees', trading_fees)
+            return trading_fees
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not fetch trading fees due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    @retrier
+    def fetch_bids_asks(self, symbols: List[str] = None, cached: bool = False) -> Dict:
+        """
+        :param cached: Allow cached result
+        :return: fetch_tickers result
+        """
+        if not self.exchange_has('fetchBidsAsks'):
+            return {}
+        if cached:
+            tickers = self._fetch_tickers_cache.get('fetch_bids_asks')
+            if tickers:
+                return tickers
+        try:
+            tickers = self._api.fetch_bids_asks(symbols)
+            self._fetch_tickers_cache['fetch_bids_asks'] = tickers
+            return tickers
+        except ccxt.NotSupported as e:
+            raise OperationalException(
+                f'Exchange {self._api.name} does not support fetching bids/asks in batch. '
+                f'Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not load bids/asks due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    @retrier
+    def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
         """
         :param cached: Allow cached result
         :return: fetch_tickers result
@@ -937,7 +1350,7 @@ class Exchange:
             if tickers:
                 return tickers
         try:
-            tickers = self._api.fetch_tickers()
+            tickers = self._api.fetch_tickers(symbols)
             self._fetch_tickers_cache['fetch_tickers'] = tickers
             return tickers
         except ccxt.NotSupported as e:
@@ -1011,7 +1424,8 @@ class Exchange:
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
 
-    def get_rate(self, pair: str, refresh: bool, side: str) -> float:
+    def get_rate(self, pair: str, refresh: bool,
+                 side: EntryExit, is_short: bool) -> float:
         """
         Calculates bid/ask target
         bid rate - between current ask price and last price
@@ -1023,9 +1437,10 @@ class Exchange:
         :return: float: Price
         :raises PricingError if orderbook price could not be determined.
         """
-        cache_rate: TTLCache = self._buy_rate_cache if side == "buy" else self._sell_rate_cache
-        [strat_name, name] = ['bid_strategy', 'Buy'] if side == "buy" else ['ask_strategy', 'Sell']
+        name = side.capitalize()
+        strat_name = 'entry_pricing' if side == "entry" else 'exit_pricing'
 
+        cache_rate: TTLCache = self._entry_rate_cache if side == "entry" else self._exit_rate_cache
         if not refresh:
             rate = cache_rate.get(pair)
             # Check if cache has been invalidated
@@ -1035,33 +1450,49 @@ class Exchange:
 
         conf_strategy = self._config.get(strat_name, {})
 
-        if conf_strategy.get('use_order_book', False) and ('use_order_book' in conf_strategy):
+        price_side = conf_strategy['price_side']
+
+        if price_side in ('same', 'other'):
+            price_map = {
+                ('entry', 'long', 'same'): 'bid',
+                ('entry', 'long', 'other'): 'ask',
+                ('entry', 'short', 'same'): 'ask',
+                ('entry', 'short', 'other'): 'bid',
+                ('exit', 'long', 'same'): 'ask',
+                ('exit', 'long', 'other'): 'bid',
+                ('exit', 'short', 'same'): 'bid',
+                ('exit', 'short', 'other'): 'ask',
+            }
+            price_side = price_map[(side, 'short' if is_short else 'long', price_side)]
+
+        price_side_word = price_side.capitalize()
+
+        if conf_strategy.get('use_order_book', False):
 
             order_book_top = conf_strategy.get('order_book_top', 1)
             order_book = self.fetch_l2_order_book(pair, order_book_top)
             logger.debug('order_book %s', order_book)
             # top 1 = index 0
             try:
-                rate = order_book[f"{conf_strategy['price_side']}s"][order_book_top - 1][0]
+                rate = order_book[f"{price_side}s"][order_book_top - 1][0]
             except (IndexError, KeyError) as e:
                 logger.warning(
                     f"{name} Price at location {order_book_top} from orderbook could not be "
                     f"determined. Orderbook: {order_book}"
                 )
                 raise PricingError from e
-            price_side = {conf_strategy['price_side'].capitalize()}
-            logger.debug(f"{name} price from orderbook {price_side}"
+            logger.debug(f"{name} price from orderbook {price_side_word}"
                          f"side - top {order_book_top} order book {side} rate {rate:.8f}")
         else:
-            logger.debug(f"Using Last {conf_strategy['price_side'].capitalize()} / Last Price")
+            logger.debug(f"Using Last {price_side_word} / Last Price")
             ticker = self.fetch_ticker(pair)
-            ticker_rate = ticker[conf_strategy['price_side']]
+            ticker_rate = ticker[price_side]
             if ticker['last'] and ticker_rate:
-                if side == 'buy' and ticker_rate > ticker['last']:
-                    balance = conf_strategy['ask_last_balance']
+                if side == 'entry' and ticker_rate > ticker['last']:
+                    balance = conf_strategy.get('price_last_balance', 0.0)
                     ticker_rate = ticker_rate + balance * (ticker['last'] - ticker_rate)
-                elif side == 'sell' and ticker_rate < ticker['last']:
-                    balance = conf_strategy.get('bid_last_balance', 0.0)
+                elif side == 'exit' and ticker_rate < ticker['last']:
+                    balance = conf_strategy.get('price_last_balance', 0.0)
                     ticker_rate = ticker_rate - balance * (ticker_rate - ticker['last'])
             rate = ticker_rate
 
@@ -1074,7 +1505,8 @@ class Exchange:
     # Fee handling
 
     @retrier
-    def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
+    def get_trades_for_order(self, order_id: str, pair: str, since: datetime,
+                             params: Optional[Dict] = None) -> List:
         """
         Fetch Orders using the "fetch_my_trades" endpoint and filter them by order-id.
         The "since" argument passed in is coming from the database and is in UTC,
@@ -1098,11 +1530,16 @@ class Exchange:
         try:
             # Allow 5s offset to catch slight time offsets (discovered in #1185)
             # since needs to be int in milliseconds
+            _params = params if params else {}
             my_trades = self._api.fetch_my_trades(
-                pair, int((since.replace(tzinfo=timezone.utc).timestamp() - 5) * 1000))
+                pair, int((since.replace(tzinfo=timezone.utc).timestamp() - 5) * 1000),
+                params=_params)
             matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
 
             self._log_exchange_response('get_trades_for_order', matched_trades)
+
+            matched_trades = self._trades_contracts_to_amount(matched_trades)
+
             return matched_trades
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
@@ -1177,9 +1614,11 @@ class Exchange:
                 tick = self.fetch_ticker(comb)
 
                 fee_to_quote_rate = safe_value_fallback2(tick, tick, 'last', 'ask')
-                return round((order['fee']['cost'] * fee_to_quote_rate) / order['cost'], 8)
             except ExchangeError:
-                return None
+                fee_to_quote_rate = self._config['exchange'].get('unknown_fee_rate', None)
+                if not fee_to_quote_rate:
+                    return None
+            return round((order['fee']['cost'] * fee_to_quote_rate) / order['cost'], 8)
 
     def extract_cost_curr_rate(self, order: Dict) -> Tuple[float, str, Optional[float]]:
         """
@@ -1195,7 +1634,8 @@ class Exchange:
     # Historic data
 
     def get_historic_ohlcv(self, pair: str, timeframe: str,
-                           since_ms: int, is_new_pair: bool = False) -> List:
+                           since_ms: int, candle_type: CandleType,
+                           is_new_pair: bool = False) -> List:
         """
         Get candle history using asyncio and returns the list of candles.
         Handles all async work for this.
@@ -1203,31 +1643,38 @@ class Exchange:
         :param pair: Pair to download
         :param timeframe: Timeframe to get data for
         :param since_ms: Timestamp in milliseconds to get history from
+        :param candle_type: '', mark, index, premiumIndex, or funding_rate
         :return: List with candle (OHLCV) data
         """
-        return asyncio.get_event_loop().run_until_complete(
+        pair, _, _, data = self.loop.run_until_complete(
             self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe,
-                                           since_ms=since_ms, is_new_pair=is_new_pair))
+                                           since_ms=since_ms, is_new_pair=is_new_pair,
+                                           candle_type=candle_type))
+        logger.info(f"Downloaded data for {pair} with length {len(data)}.")
+        return data
 
     def get_historic_ohlcv_as_df(self, pair: str, timeframe: str,
-                                 since_ms: int) -> DataFrame:
+                                 since_ms: int, candle_type: CandleType) -> DataFrame:
         """
         Minimal wrapper around get_historic_ohlcv - converting the result into a dataframe
         :param pair: Pair to download
         :param timeframe: Timeframe to get data for
         :param since_ms: Timestamp in milliseconds to get history from
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         :return: OHLCV DataFrame
         """
-        ticks = self.get_historic_ohlcv(pair, timeframe, since_ms=since_ms)
+        ticks = self.get_historic_ohlcv(pair, timeframe, since_ms=since_ms, candle_type=candle_type)
         return ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True,
                                   drop_incomplete=self._ohlcv_partial_candle)
 
     async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
-                                        since_ms: int, is_new_pair: bool
-                                        ) -> List:
+                                        since_ms: int, candle_type: CandleType,
+                                        is_new_pair: bool = False, raise_: bool = False,
+                                        ) -> Tuple[str, str, str, List]:
         """
         Download historic ohlcv
         :param is_new_pair: used by binance subclass to allow "fast" new pair downloading
+        :param candle_type: Any of the enum CandleType (must match trading mode!)
         """
 
         one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit(timeframe)
@@ -1237,7 +1684,7 @@ class Exchange:
             arrow.utcnow().shift(seconds=one_call // 1000).humanize(only_distance=True)
         )
         input_coroutines = [self._async_get_candle_history(
-            pair, timeframe, since) for since in
+            pair, timeframe, candle_type, since) for since in
             range(since_ms, arrow.utcnow().int_timestamp * 1000, one_call)]
 
         data: List = []
@@ -1247,20 +1694,41 @@ class Exchange:
             results = await asyncio.gather(*input_coro, return_exceptions=True)
             for res in results:
                 if isinstance(res, Exception):
-                    logger.warning("Async code raised an exception: %s", res.__class__.__name__)
+                    logger.warning(f"Async code raised an exception: {repr(res)}")
+                    if raise_:
+                        raise
                     continue
-                # Deconstruct tuple if it's not an exception
-                p, _, new_data = res
-                if p == pair:
-                    data.extend(new_data)
+                else:
+                    # Deconstruct tuple if it's not an exception
+                    p, _, c, new_data = res
+                    if p == pair and c == candle_type:
+                        data.extend(new_data)
         # Sort data again after extending the result - above calls return in "async order"
         data = sorted(data, key=lambda x: x[0])
-        logger.info(f"Downloaded data for {pair} with length {len(data)}.")
-        return data
+        return pair, timeframe, candle_type, data
+
+    def _build_coroutine(self, pair: str, timeframe: str, candle_type: CandleType,
+                         since_ms: Optional[int]) -> Coroutine:
+
+        if not since_ms and self.required_candle_call_count > 1:
+            # Multiple calls for one pair - to get more history
+            one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit(timeframe)
+            move_to = one_call * self.required_candle_call_count
+            now = timeframe_to_next_date(timeframe)
+            since_ms = int((now - timedelta(seconds=move_to // 1000)).timestamp() * 1000)
+
+        if since_ms:
+            return self._async_get_historic_ohlcv(
+                pair, timeframe, since_ms=since_ms, raise_=True, candle_type=candle_type)
+        else:
+            # One call ... "regular" refresh
+            return self._async_get_candle_history(
+                pair, timeframe, since_ms=since_ms, candle_type=candle_type)
 
     def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes, *,
-                             since_ms: Optional[int] = None, cache: bool = True
-                             ) -> Dict[Tuple[str, str], DataFrame]:
+                             since_ms: Optional[int] = None, cache: bool = True,
+                             drop_incomplete: bool = None
+                             ) -> Dict[PairWithTimeframe, DataFrame]:
         """
         Refresh in-memory OHLCV asynchronously and set `_klines` with the result
         Loops asynchronously over pair_list and downloads all pairs async (semi-parallel).
@@ -1268,64 +1736,89 @@ class Exchange:
         :param pair_list: List of 2 element tuples containing pair, interval to refresh
         :param since_ms: time since when to download, in milliseconds
         :param cache: Assign result to _klines. Usefull for one-off downloads like for pairlists
+        :param drop_incomplete: Control candle dropping.
+            Specifying None defaults to _ohlcv_partial_candle
         :return: Dict of [{(pair, timeframe): Dataframe}]
         """
         logger.debug("Refreshing candle (OHLCV) data for %d pairs", len(pair_list))
-
+        drop_incomplete = self._ohlcv_partial_candle if drop_incomplete is None else drop_incomplete
         input_coroutines = []
         cached_pairs = []
         # Gather coroutines to run
-        for pair, timeframe in set(pair_list):
-            if (((pair, timeframe) not in self._klines)
-                    or self._now_is_time_to_refresh(pair, timeframe)):
-                input_coroutines.append(self._async_get_candle_history(pair, timeframe,
-                                                                       since_ms=since_ms))
+        for pair, timeframe, candle_type in set(pair_list):
+            if (timeframe not in self.timeframes
+                    and candle_type in (CandleType.SPOT, CandleType.FUTURES)):
+                logger.warning(
+                    f"Cannot download ({pair}, {timeframe}) combination as this timeframe is "
+                    f"not available on {self.name}. Available timeframes are "
+                    f"{', '.join(self.timeframes)}.")
+                continue
+            if ((pair, timeframe, candle_type) not in self._klines or not cache
+                    or self._now_is_time_to_refresh(pair, timeframe, candle_type)):
+                input_coroutines.append(self._build_coroutine(
+                    pair, timeframe, candle_type=candle_type, since_ms=since_ms))
+
             else:
                 logger.debug(
-                    "Using cached candle (OHLCV) data for pair %s, timeframe %s ...",
-                    pair, timeframe
+                    f"Using cached candle (OHLCV) data for {pair}, {timeframe}, {candle_type} ..."
                 )
-                cached_pairs.append((pair, timeframe))
-
-        results = asyncio.get_event_loop().run_until_complete(
-            asyncio.gather(*input_coroutines, return_exceptions=True))
+                cached_pairs.append((pair, timeframe, candle_type))
 
         results_df = {}
-        # handle caching
-        for res in results:
-            if isinstance(res, Exception):
-                logger.warning("Async code raised an exception: %s", res.__class__.__name__)
-                continue
-            # Deconstruct tuple (has 3 elements)
-            pair, timeframe, ticks = res
-            # keeping last candle time as last refreshed time of the pair
-            if ticks:
-                self._pairs_last_refresh_time[(pair, timeframe)] = ticks[-1][0] // 1000
-            # keeping parsed dataframe in cache
-            ohlcv_df = ohlcv_to_dataframe(
-                ticks, timeframe, pair=pair, fill_missing=True,
-                drop_incomplete=self._ohlcv_partial_candle)
-            results_df[(pair, timeframe)] = ohlcv_df
-            if cache:
-                self._klines[(pair, timeframe)] = ohlcv_df
+        # Chunk requests into batches of 100 to avoid overwelming ccxt Throttling
+        for input_coro in chunks(input_coroutines, 100):
+            async def gather_stuff():
+                return await asyncio.gather(*input_coro, return_exceptions=True)
+
+            results = self.loop.run_until_complete(gather_stuff())
+
+            for res in results:
+                if isinstance(res, Exception):
+                    logger.warning(f"Async code raised an exception: {repr(res)}")
+                    continue
+                # Deconstruct tuple (has 4 elements)
+                pair, timeframe, c_type, ticks = res
+                # keeping last candle time as last refreshed time of the pair
+                if ticks:
+                    self._pairs_last_refresh_time[(pair, timeframe, c_type)] = ticks[-1][0] // 1000
+                # keeping parsed dataframe in cache
+                ohlcv_df = ohlcv_to_dataframe(
+                    ticks, timeframe, pair=pair, fill_missing=True,
+                    drop_incomplete=drop_incomplete)
+                results_df[(pair, timeframe, c_type)] = ohlcv_df
+                if cache:
+                    self._klines[(pair, timeframe, c_type)] = ohlcv_df
         # Return cached klines
-        for pair, timeframe in cached_pairs:
-            results_df[(pair, timeframe)] = self.klines((pair, timeframe), copy=False)
+        for pair, timeframe, c_type in cached_pairs:
+            results_df[(pair, timeframe, c_type)] = self.klines(
+                (pair, timeframe, c_type),
+                copy=False
+            )
 
         return results_df
 
-    def _now_is_time_to_refresh(self, pair: str, timeframe: str) -> bool:
+    def _now_is_time_to_refresh(self, pair: str, timeframe: str, candle_type: CandleType) -> bool:
         # Timeframe in seconds
         interval_in_sec = timeframe_to_seconds(timeframe)
 
-        return not ((self._pairs_last_refresh_time.get((pair, timeframe), 0)
-                     + interval_in_sec) >= arrow.utcnow().int_timestamp)
+        return not (
+            (self._pairs_last_refresh_time.get(
+                (pair, timeframe, candle_type),
+                0
+            ) + interval_in_sec) >= arrow.utcnow().int_timestamp
+        )
 
     @retrier_async
-    async def _async_get_candle_history(self, pair: str, timeframe: str,
-                                        since_ms: Optional[int] = None) -> Tuple[str, str, List]:
+    async def _async_get_candle_history(
+        self,
+        pair: str,
+        timeframe: str,
+        candle_type: CandleType,
+        since_ms: Optional[int] = None,
+    ) -> Tuple[str, str, str, List]:
         """
         Asynchronously get candle history data using fetch_ohlcv
+        :param candle_type: '', mark, index, premiumIndex, or funding_rate
         returns tuple: (pair, timeframe, ohlcv_list)
         """
         try:
@@ -1335,12 +1828,20 @@ class Exchange:
                 "Fetching pair %s, interval %s, since %s %s...",
                 pair, timeframe, since_ms, s
             )
-            params = self._ft_has.get('ohlcv_params', {})
-            data = await self._api_async.fetch_ohlcv(pair, timeframe=timeframe,
-                                                     since=since_ms,
-                                                     limit=self.ohlcv_candle_limit(timeframe),
-                                                     params=params)
-
+            params = deepcopy(self._ft_has.get('ohlcv_params', {}))
+            if candle_type != CandleType.SPOT:
+                params.update({'price': candle_type})
+            if candle_type != CandleType.FUNDING_RATE:
+                data = await self._api_async.fetch_ohlcv(
+                    pair, timeframe=timeframe, since=since_ms,
+                    limit=self.ohlcv_candle_limit(timeframe), params=params)
+            else:
+                # Funding rate
+                data = await self._api_async.fetch_funding_rate_history(
+                    pair, since=since_ms,
+                    limit=self.ohlcv_candle_limit(timeframe))
+                # Convert funding rate to candle pattern
+                data = [[x['timestamp'], x['fundingRate'], 0, 0, 0, 0] for x in data]
             # Some exchanges sort OHLCV in ASC order and others in DESC.
             # Ex: Bittrex returns the list of OHLCV in ASC order (oldest first, newest last)
             # while GDAX returns the list of OHLCV in DESC order (newest first, oldest last)
@@ -1350,9 +1851,9 @@ class Exchange:
                     data = sorted(data, key=lambda x: x[0])
             except IndexError:
                 logger.exception("Error loading %s. Result was %s.", pair, data)
-                return pair, timeframe, []
+                return pair, timeframe, candle_type, []
             logger.debug("Done fetching pair %s, interval %s ...", pair, timeframe)
-            return pair, timeframe, data
+            return pair, timeframe, candle_type, data
 
         except ccxt.NotSupported as e:
             raise OperationalException(
@@ -1393,6 +1894,7 @@ class Exchange:
                     '(' + arrow.get(since // 1000).isoformat() + ') ' if since is not None else ''
                 )
                 trades = await self._api_async.fetch_trades(pair, since=since, limit=1000)
+            trades = self._trades_contracts_to_amount(trades)
             return trades_dict_to_list(trades)
         except ccxt.NotSupported as e:
             raise OperationalException(
@@ -1524,17 +2026,553 @@ class Exchange:
         if not self.exchange_has("fetchTrades"):
             raise OperationalException("This exchange does not support downloading Trades.")
 
-        return asyncio.get_event_loop().run_until_complete(
+        return self.loop.run_until_complete(
             self._async_get_trade_history(pair=pair, since=since,
                                           until=until, from_id=from_id))
 
+    @retrier
+    def _get_funding_fees_from_exchange(self, pair: str, since: Union[datetime, int]) -> float:
+        """
+        Returns the sum of all funding fees that were exchanged for a pair within a timeframe
+        Dry-run handling happens as part of _calculate_funding_fees.
+        :param pair: (e.g. ADA/USDT)
+        :param since: The earliest time of consideration for calculating funding fees,
+            in unix time or as a datetime
+        """
+        if not self.exchange_has("fetchFundingHistory"):
+            raise OperationalException(
+                f"fetch_funding_history() is not available using {self.name}"
+            )
+
+        if type(since) is datetime:
+            since = int(since.timestamp()) * 1000   # * 1000 for ms
+
+        try:
+            funding_history = self._api.fetch_funding_history(
+                symbol=pair,
+                since=since
+            )
+            return sum(fee['amount'] for fee in funding_history)
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not get funding fees due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    @retrier
+    def get_leverage_tiers(self) -> Dict[str, List[Dict]]:
+        try:
+            return self._api.fetch_leverage_tiers()
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not load leverage tiers due to {e.__class__.__name__}. Message: {e}'
+            ) from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    @retrier
+    def get_market_leverage_tiers(self, symbol) -> List[Dict]:
+        try:
+            return self._api.fetch_market_leverage_tiers(symbol)
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not load leverage tiers for {symbol}'
+                f' due to {e.__class__.__name__}. Message: {e}'
+            ) from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    def load_leverage_tiers(self) -> Dict[str, List[Dict]]:
+        if self.trading_mode == TradingMode.FUTURES:
+            if self.exchange_has('fetchLeverageTiers'):
+                # Fetch all leverage tiers at once
+                return self.get_leverage_tiers()
+            elif self.exchange_has('fetchMarketLeverageTiers'):
+                # Must fetch the leverage tiers for each market separately
+                # * This is slow(~45s) on Okx, makes ~90 api calls to load all linear swap markets
+                markets = self.markets
+                symbols = []
+
+                for symbol, market in markets.items():
+                    if (self.market_is_future(market)
+                            and market['quote'] == self._config['stake_currency']):
+                        symbols.append(symbol)
+
+                tiers: Dict[str, List[Dict]] = {}
+
+                # Be verbose here, as this delays startup by ~1 minute.
+                logger.info(
+                    f"Initializing leverage_tiers for {len(symbols)} markets. "
+                    "This will take about a minute.")
+
+                for symbol in sorted(symbols):
+                    tiers[symbol] = self.get_market_leverage_tiers(symbol)
+
+                logger.info(f"Done initializing {len(symbols)} markets.")
+
+                return tiers
+            else:
+                return {}
+        else:
+            return {}
+
+    def fill_leverage_tiers(self) -> None:
+        """
+        Assigns property _leverage_tiers to a dictionary of information about the leverage
+        allowed on each pair
+        """
+        leverage_tiers = self.load_leverage_tiers()
+        for pair, tiers in leverage_tiers.items():
+            pair_tiers = []
+            for tier in tiers:
+                pair_tiers.append(self.parse_leverage_tier(tier))
+            self._leverage_tiers[pair] = pair_tiers
+
+    def parse_leverage_tier(self, tier) -> Dict:
+        info = tier.get('info', {})
+        return {
+            'min': tier['notionalFloor'],
+            'max': tier['notionalCap'],
+            'mmr': tier['maintenanceMarginRate'],
+            'lev': tier['maxLeverage'],
+            'maintAmt': float(info['cum']) if 'cum' in info else None,
+        }
+
+    def get_max_leverage(self, pair: str, stake_amount: Optional[float]) -> float:
+        """
+        Returns the maximum leverage that a pair can be traded at
+        :param pair: The base/quote currency pair being traded
+        :stake_amount: The total value of the traders margin_mode in quote currency
+        """
+
+        if self.trading_mode == TradingMode.SPOT:
+            return 1.0
+
+        if self.trading_mode == TradingMode.FUTURES:
+
+            # Checks and edge cases
+            if stake_amount is None:
+                raise OperationalException(
+                    f'{self.name}.get_max_leverage requires argument stake_amount'
+                )
+
+            if pair not in self._leverage_tiers:
+                # Maybe raise exception because it can't be traded on futures?
+                return 1.0
+
+            pair_tiers = self._leverage_tiers[pair]
+
+            if stake_amount == 0:
+                return self._leverage_tiers[pair][0]['lev']  # Max lev for lowest amount
+
+            for tier_index in range(len(pair_tiers)):
+
+                tier = pair_tiers[tier_index]
+                lev = tier['lev']
+
+                if tier_index < len(pair_tiers) - 1:
+                    next_tier = pair_tiers[tier_index + 1]
+                    next_floor = next_tier['min'] / next_tier['lev']
+                    if next_floor > stake_amount:  # Next tier min too high for stake amount
+                        return min((tier['max'] / stake_amount), lev)
+                        #
+                        # With the two leverage tiers below,
+                        # - a stake amount of 150 would mean a max leverage of (10000 / 150) = 66.66
+                        # - stakes below 133.33 = max_lev of 75
+                        # - stakes between 133.33-200 = max_lev of 10000/stake = 50.01-74.99
+                        # - stakes from 200 + 1000 = max_lev of 50
+                        #
+                        # {
+                        #     "min": 0,      # stake = 0.0
+                        #     "max": 10000,  # max_stake@75 = 10000/75 = 133.33333333333334
+                        #     "lev": 75,
+                        # },
+                        # {
+                        #     "min": 10000,  # stake = 200.0
+                        #     "max": 50000,  # max_stake@50 = 50000/50 = 1000.0
+                        #     "lev": 50,
+                        # }
+                        #
+
+                else:  # if on the last tier
+                    if stake_amount > tier['max']:  # If stake is > than max tradeable amount
+                        raise InvalidOrderException(f'Amount {stake_amount} too high for {pair}')
+                    else:
+                        return tier['lev']
+
+            raise OperationalException(
+                'Looped through all tiers without finding a max leverage. Should never be reached'
+            )
+
+        elif self.trading_mode == TradingMode.MARGIN:  # Search markets.limits for max lev
+            market = self.markets[pair]
+            if market['limits']['leverage']['max'] is not None:
+                return market['limits']['leverage']['max']
+            else:
+                return 1.0  # Default if max leverage cannot be found
+        else:
+            return 1.0
+
+    @retrier
+    def _set_leverage(
+        self,
+        leverage: float,
+        pair: Optional[str] = None,
+        trading_mode: Optional[TradingMode] = None
+    ):
+        """
+        Set's the leverage before making a trade, in order to not
+        have the same leverage on every trade
+        """
+        if self._config['dry_run'] or not self.exchange_has("setLeverage"):
+            # Some exchanges only support one margin_mode type
+            return
+
+        try:
+            self._api.set_leverage(symbol=pair, leverage=leverage)
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    def get_interest_rate(self) -> float:
+        """
+        Retrieve interest rate - necessary for Margin trading.
+        Should not call the exchange directly when used from backtesting.
+        """
+        return 0.0
+
+    def get_liquidation_price(
+            self,
+            pair: str,
+            open_rate: float,
+            amount: float,  # quote currency, includes leverage
+            leverage: float,
+            is_short: bool
+    ) -> Optional[float]:
+
+        if self.trading_mode in TradingMode.SPOT:
+            return None
+        elif (
+            self.margin_mode == MarginMode.ISOLATED and
+            self.trading_mode == TradingMode.FUTURES
+        ):
+            wallet_balance = (amount * open_rate) / leverage
+            isolated_liq = self.get_or_calculate_liquidation_price(
+                pair=pair,
+                open_rate=open_rate,
+                is_short=is_short,
+                position=amount,
+                wallet_balance=wallet_balance,
+                mm_ex_1=0.0,
+                upnl_ex_1=0.0,
+            )
+            return isolated_liq
+        else:
+            raise OperationalException(
+                "Freqtrade only supports isolated futures for leverage trading")
+
+    def funding_fee_cutoff(self, open_date: datetime):
+        """
+        :param open_date: The open date for a trade
+        :return: The cutoff open time for when a funding fee is charged
+        """
+        return open_date.minute > 0 or open_date.second > 0
+
+    @retrier
+    def set_margin_mode(self, pair: str, margin_mode: MarginMode, params: dict = {}):
+        """
+        Set's the margin mode on the exchange to cross or isolated for a specific pair
+        :param pair: base/quote currency pair (e.g. "ADA/USDT")
+        """
+        if self._config['dry_run'] or not self.exchange_has("setMarginMode"):
+            # Some exchanges only support one margin_mode type
+            return
+
+        try:
+            self._api.set_margin_mode(margin_mode.value, pair, params)
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not set margin mode due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    def _fetch_and_calculate_funding_fees(
+        self,
+        pair: str,
+        amount: float,
+        is_short: bool,
+        open_date: datetime,
+        close_date: Optional[datetime] = None
+    ) -> float:
+        """
+        Fetches and calculates the sum of all funding fees that occurred for a pair
+        during a futures trade.
+        Only used during dry-run or if the exchange does not provide a funding_rates endpoint.
+        :param pair: The quote/base pair of the trade
+        :param amount: The quantity of the trade
+        :param is_short: trade direction
+        :param open_date: The date and time that the trade started
+        :param close_date: The date and time that the trade ended
+        """
+
+        if self.funding_fee_cutoff(open_date):
+            open_date += timedelta(hours=1)
+        timeframe = self._ft_has['mark_ohlcv_timeframe']
+        timeframe_ff = self._ft_has.get('funding_fee_timeframe',
+                                        self._ft_has['mark_ohlcv_timeframe'])
+
+        if not close_date:
+            close_date = datetime.now(timezone.utc)
+        open_timestamp = int(timeframe_to_prev_date(timeframe, open_date).timestamp()) * 1000
+        # close_timestamp = int(close_date.timestamp()) * 1000
+
+        mark_comb: PairWithTimeframe = (
+            pair, timeframe, CandleType.from_string(self._ft_has["mark_ohlcv_price"]))
+
+        funding_comb: PairWithTimeframe = (pair, timeframe_ff, CandleType.FUNDING_RATE)
+        candle_histories = self.refresh_latest_ohlcv(
+            [mark_comb, funding_comb],
+            since_ms=open_timestamp,
+            cache=False,
+            drop_incomplete=False,
+        )
+        funding_rates = candle_histories[funding_comb]
+        mark_rates = candle_histories[mark_comb]
+        funding_mark_rates = self.combine_funding_and_mark(
+            funding_rates=funding_rates, mark_rates=mark_rates)
+
+        return self.calculate_funding_fees(
+            funding_mark_rates,
+            amount=amount,
+            is_short=is_short,
+            open_date=open_date,
+            close_date=close_date
+        )
+
+    @staticmethod
+    def combine_funding_and_mark(funding_rates: DataFrame, mark_rates: DataFrame) -> DataFrame:
+        """
+        Combine funding-rates and mark-rates dataframes
+        :param funding_rates: Dataframe containing Funding rates (Type FUNDING_RATE)
+        :param mark_rates: Dataframe containing Mark rates (Type mark_ohlcv_price)
+        """
+
+        return funding_rates.merge(mark_rates, on='date', how="inner", suffixes=["_fund", "_mark"])
+
+    def calculate_funding_fees(
+        self,
+        df: DataFrame,
+        amount: float,
+        is_short: bool,
+        open_date: datetime,
+        close_date: Optional[datetime] = None,
+        time_in_ratio: Optional[float] = None
+    ) -> float:
+        """
+        calculates the sum of all funding fees that occurred for a pair during a futures trade
+        :param df: Dataframe containing combined funding and mark rates
+                   as `open_fund` and `open_mark`.
+        :param amount: The quantity of the trade
+        :param is_short: trade direction
+        :param open_date: The date and time that the trade started
+        :param close_date: The date and time that the trade ended
+        :param time_in_ratio: Not used by most exchange classes
+        """
+        fees: float = 0
+
+        if not df.empty:
+            df = df[(df['date'] >= open_date) & (df['date'] <= close_date)]
+            fees = sum(df['open_fund'] * df['open_mark'] * amount)
+
+        # Negate fees for longs as funding_fees expects it this way based on live endpoints.
+        return fees if is_short else -fees
+
+    def get_funding_fees(
+            self, pair: str, amount: float, is_short: bool, open_date: datetime) -> float:
+        """
+        Fetch funding fees, either from the exchange (live) or calculates them
+        based on funding rate/mark price history
+        :param pair: The quote/base pair of the trade
+        :param is_short: trade direction
+        :param amount: Trade amount
+        :param open_date: Open date of the trade
+        """
+        if self.trading_mode == TradingMode.FUTURES:
+            if self._config['dry_run']:
+                funding_fees = self._fetch_and_calculate_funding_fees(
+                    pair, amount, is_short, open_date)
+            else:
+                funding_fees = self._get_funding_fees_from_exchange(pair, open_date)
+            return funding_fees
+        else:
+            return 0.0
+
+    @retrier
+    def get_or_calculate_liquidation_price(
+        self,
+        pair: str,
+        # Dry-run
+        open_rate: float,   # Entry price of position
+        is_short: bool,
+        position: float,  # Absolute value of position size
+        wallet_balance: float,  # Or margin balance
+        mm_ex_1: float = 0.0,  # (Binance) Cross only
+        upnl_ex_1: float = 0.0,  # (Binance) Cross only
+    ) -> Optional[float]:
+        """
+        Set's the margin mode on the exchange to cross or isolated for a specific pair
+        :param pair: base/quote currency pair (e.g. "ADA/USDT")
+        """
+        if self.trading_mode == TradingMode.SPOT:
+            return None
+        elif (self.trading_mode != TradingMode.FUTURES and self.margin_mode != MarginMode.ISOLATED):
+            raise OperationalException(
+                f"{self.name} does not support {self.margin_mode.value} {self.trading_mode.value}")
+
+        if self._config['dry_run'] or not self.exchange_has("fetchPositions"):
+
+            isolated_liq = self.dry_run_liquidation_price(
+                pair=pair,
+                open_rate=open_rate,
+                is_short=is_short,
+                position=position,
+                wallet_balance=wallet_balance,
+                mm_ex_1=mm_ex_1,
+                upnl_ex_1=upnl_ex_1
+            )
+        else:
+            try:
+                positions = self._api.fetch_positions([pair])
+                if len(positions) > 0:
+                    pos = positions[0]
+                    isolated_liq = pos['liquidationPrice']
+                else:
+                    return None
+            except ccxt.DDoSProtection as e:
+                raise DDosProtection(e) from e
+            except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+                raise TemporaryError(
+                    f'Could not set margin mode due to {e.__class__.__name__}. Message: {e}') from e
+            except ccxt.BaseError as e:
+                raise OperationalException(e) from e
+
+        if isolated_liq:
+            buffer_amount = abs(open_rate - isolated_liq) * self.liquidation_buffer
+            isolated_liq = (
+                isolated_liq - buffer_amount
+                if is_short else
+                isolated_liq + buffer_amount
+            )
+            return isolated_liq
+        else:
+            return None
+
+    def dry_run_liquidation_price(
+        self,
+        pair: str,
+        open_rate: float,   # Entry price of position
+        is_short: bool,
+        position: float,  # Absolute value of position size
+        wallet_balance: float,  # Or margin balance
+        mm_ex_1: float = 0.0,  # (Binance) Cross only
+        upnl_ex_1: float = 0.0,  # (Binance) Cross only
+    ) -> Optional[float]:
+        """
+        PERPETUAL:
+         gateio: https://www.gate.io/help/futures/perpetual/22160/calculation-of-liquidation-price
+         okex: https://www.okex.com/support/hc/en-us/articles/
+            360053909592-VI-Introduction-to-the-isolated-mode-of-Single-Multi-currency-Portfolio-margin
+        Important: Must be fetching data from cached values as this is used by backtesting!
+
+        :param exchange_name:
+        :param open_rate: Entry price of position
+        :param is_short: True if the trade is a short, false otherwise
+        :param position: Absolute value of position size incl. leverage (in base currency)
+        :param trading_mode: SPOT, MARGIN, FUTURES, etc.
+        :param margin_mode: Either ISOLATED or CROSS
+        :param wallet_balance: Amount of margin_mode in the wallet being used to trade
+            Cross-Margin Mode: crossWalletBalance
+            Isolated-Margin Mode: isolatedWalletBalance
+
+        # * Not required by Gateio or OKX
+        :param mm_ex_1:
+        :param upnl_ex_1:
+        """
+
+        market = self.markets[pair]
+        taker_fee_rate = market['taker']
+        mm_ratio, _ = self.get_maintenance_ratio_and_amt(pair, position)
+
+        if self.trading_mode == TradingMode.FUTURES and self.margin_mode == MarginMode.ISOLATED:
+
+            if market['inverse']:
+                raise OperationalException(
+                    "Freqtrade does not yet support inverse contracts")
+
+            value = wallet_balance / position
+
+            mm_ratio_taker = (mm_ratio + taker_fee_rate)
+            if is_short:
+                return (open_rate + value) / (1 + mm_ratio_taker)
+            else:
+                return (open_rate - value) / (1 - mm_ratio_taker)
+        else:
+            raise OperationalException(
+                "Freqtrade only supports isolated futures for leverage trading")
+
+    def get_maintenance_ratio_and_amt(
+        self,
+        pair: str,
+        nominal_value: float = 0.0,
+    ) -> Tuple[float, Optional[float]]:
+        """
+        Important: Must be fetching data from cached values as this is used by backtesting!
+        :param pair: Market symbol
+        :param nominal_value: The total trade amount in quote currency including leverage
+        maintenance amount only on Binance
+        :return: (maintenance margin ratio, maintenance amount)
+        """
+
+        if (self._config.get('runmode') in OPTIMIZE_MODES
+                or self.exchange_has('fetchLeverageTiers')
+                or self.exchange_has('fetchMarketLeverageTiers')):
+
+            if pair not in self._leverage_tiers:
+                raise InvalidOrderException(
+                    f"Maintenance margin rate for {pair} is unavailable for {self.name}"
+                )
+
+            pair_tiers = self._leverage_tiers[pair]
+
+            for tier in reversed(pair_tiers):
+                if nominal_value >= tier['min']:
+                    return (tier['mmr'], tier['maintAmt'])
+
+            raise OperationalException("nominal value can not be lower than 0")
+            # The lowest notional_floor for any pair in fetch_leverage_tiers is always 0 because it
+            # describes the min amt for a tier, and the lowest tier will always go down to 0
+        else:
+            raise OperationalException(f"Cannot get maintenance ratio using {self.name}")
+
 
 def is_exchange_known_ccxt(exchange_name: str, ccxt_module: CcxtModuleType = None) -> bool:
     return exchange_name in ccxt_exchanges(ccxt_module)
 
 
 def is_exchange_officially_supported(exchange_name: str) -> bool:
-    return exchange_name in ['bittrex', 'binance', 'kraken']
+    return exchange_name in SUPPORTED_EXCHANGES
 
 
 def ccxt_exchanges(ccxt_module: CcxtModuleType = None) -> List[str]:
diff --git a/freqtrade/exchange/ftx.py b/freqtrade/exchange/ftx.py
index 6cd549d60..f20aab138 100644
--- a/freqtrade/exchange/ftx.py
+++ b/freqtrade/exchange/ftx.py
@@ -1,9 +1,10 @@
 """ FTX exchange subclass """
 import logging
-from typing import Any, Dict
+from typing import Any, Dict, List, Tuple
 
 import ccxt
 
+from freqtrade.enums import MarginMode, TradingMode
 from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
                                   OperationalException, TemporaryError)
 from freqtrade.exchange import Exchange
@@ -19,27 +20,30 @@ class Ftx(Exchange):
     _ft_has: Dict = {
         "stoploss_on_exchange": True,
         "ohlcv_candle_limit": 1500,
+        "ohlcv_volume_currency": "quote",
+        "mark_ohlcv_price": "index",
+        "mark_ohlcv_timeframe": "1h",
     }
 
-    def market_is_tradable(self, market: Dict[str, Any]) -> bool:
-        """
-        Check if the market symbol is tradable by Freqtrade.
-        Default checks + check if pair is spot pair (no futures trading yet).
-        """
-        parent_check = super().market_is_tradable(market)
+    _supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
+        # TradingMode.SPOT always supported and not required in this list
+        # (TradingMode.MARGIN, MarginMode.CROSS),
+        # (TradingMode.FUTURES, MarginMode.CROSS)
+    ]
 
-        return (parent_check and
-                market.get('spot', False) is True)
-
-    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
         """
         Verify stop_loss against stoploss-order value (limit or price)
         Returns True if adjustment is necessary.
         """
-        return order['type'] == 'stop' and stop_loss > float(order['price'])
+        return order['type'] == 'stop' and (
+            side == "sell" and stop_loss > float(order['price']) or
+            side == "buy" and stop_loss < float(order['price'])
+        )
 
     @retrier(retries=0)
-    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+    def stoploss(self, pair: str, amount: float, stop_price: float,
+                 order_types: Dict, side: str, leverage: float) -> Dict:
         """
         Creates a stoploss order.
         depending on order_types.stoploss configuration, uses 'market' or limit order.
@@ -47,7 +51,10 @@ class Ftx(Exchange):
         Limit orders are defined by having orderPrice set, otherwise a market order is used.
         """
         limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
-        limit_rate = stop_price * limit_price_pct
+        if side == "sell":
+            limit_rate = stop_price * limit_price_pct
+        else:
+            limit_rate = stop_price * (2 - limit_price_pct)
 
         ordertype = "stop"
 
@@ -55,7 +62,7 @@ class Ftx(Exchange):
 
         if self._config['dry_run']:
             dry_order = self.create_dry_run_order(
-                pair, ordertype, "sell", amount, stop_price)
+                pair, ordertype, side, amount, stop_price, leverage, stop_loss=True)
             return dry_order
 
         try:
@@ -63,11 +70,14 @@ class Ftx(Exchange):
             if order_types.get('stoploss', 'market') == 'limit':
                 # set orderPrice to place limit order, otherwise it's a market order
                 params['orderPrice'] = limit_rate
+            if self.trading_mode == TradingMode.FUTURES:
+                params.update({'reduceOnly': True})
 
             params['stopPrice'] = stop_price
             amount = self.amount_to_precision(pair, amount)
 
-            order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
+            self._lev_prep(pair, leverage, side)
+            order = self._api.create_order(symbol=pair, type=ordertype, side=side,
                                            amount=amount, params=params)
             self._log_exchange_response('create_stoploss_order', order)
             logger.info('stoploss order added for %s. '
@@ -75,19 +85,19 @@ class Ftx(Exchange):
             return order
         except ccxt.InsufficientFunds as e:
             raise InsufficientFundsError(
-                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
+                f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
                 f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
                 f'Message: {e}') from e
         except ccxt.InvalidOrder as e:
             raise InvalidOrderException(
-                f'Could not create {ordertype} sell order on market {pair}. '
+                f'Could not create {ordertype} {side} order on market {pair}. '
                 f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
                 f'Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
+                f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
 
@@ -105,15 +115,18 @@ class Ftx(Exchange):
                 if order[0].get('status') == 'closed':
                     # Trigger order was triggered ...
                     real_order_id = order[0].get('info', {}).get('orderId')
+                    # OrderId may be None for stoploss-market orders
+                    # But contains "average" in these cases.
+                    if real_order_id:
+                        order1 = self._api.fetch_order(real_order_id, pair)
+                        self._log_exchange_response('fetch_stoploss_order1', order1)
+                        # Fake type to stop - as this was really a stop order.
+                        order1['id_stop'] = order1['id']
+                        order1['id'] = order_id
+                        order1['type'] = 'stop'
+                        order1['status_stop'] = 'triggered'
+                        return order1
 
-                    order1 = self._api.fetch_order(real_order_id, pair)
-                    self._log_exchange_response('fetch_stoploss_order1', order1)
-                    # Fake type to stop - as this was really a stop order.
-                    order1['id_stop'] = order1['id']
-                    order1['id'] = order_id
-                    order1['type'] = 'stop'
-                    order1['status_stop'] = 'triggered'
-                    return order1
                 return order[0]
             else:
                 raise InvalidOrderException(f"Could not get stoploss order for id {order_id}")
diff --git a/freqtrade/exchange/gateio.py b/freqtrade/exchange/gateio.py
index e6ee01c8a..609cf4901 100644
--- a/freqtrade/exchange/gateio.py
+++ b/freqtrade/exchange/gateio.py
@@ -1,7 +1,10 @@
 """ Gate.io exchange subclass """
 import logging
-from typing import Dict
+from datetime import datetime
+from typing import Dict, List, Optional, Tuple
 
+from freqtrade.enums import MarginMode, TradingMode
+from freqtrade.exceptions import OperationalException
 from freqtrade.exchange import Exchange
 
 
@@ -20,6 +23,72 @@ class Gateio(Exchange):
 
     _ft_has: Dict = {
         "ohlcv_candle_limit": 1000,
+        "ohlcv_volume_currency": "quote",
+        "stoploss_order_types": {"limit": "limit"},
+        "stoploss_on_exchange": True,
     }
 
-    _headers = {'X-Gate-Channel-Id': 'freqtrade'}
+    _ft_has_futures: Dict = {
+        "needs_trading_fees": True
+    }
+
+    _supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
+        # TradingMode.SPOT always supported and not required in this list
+        # (TradingMode.MARGIN, MarginMode.CROSS),
+        # (TradingMode.FUTURES, MarginMode.CROSS),
+        (TradingMode.FUTURES, MarginMode.ISOLATED)
+    ]
+
+    def validate_ordertypes(self, order_types: Dict) -> None:
+        super().validate_ordertypes(order_types)
+
+        if self.trading_mode != TradingMode.FUTURES:
+            if any(v == 'market' for k, v in order_types.items()):
+                raise OperationalException(
+                    f'Exchange {self.name} does not support market orders.')
+
+    def get_trades_for_order(self, order_id: str, pair: str, since: datetime,
+                             params: Optional[Dict] = None) -> List:
+        trades = super().get_trades_for_order(order_id, pair, since, params)
+
+        if self.trading_mode == TradingMode.FUTURES:
+            # Futures usually don't contain fees in the response.
+            # As such, futures orders on gateio will not contain a fee, which causes
+            # a repeated "update fee" cycle and wrong calculations.
+            # Therefore we patch the response with fees if it's not available.
+            # An alternative also contianing fees would be
+            # privateFuturesGetSettleAccountBook({"settle": "usdt"})
+            pair_fees = self._trading_fees.get(pair, {})
+            if pair_fees:
+                for idx, trade in enumerate(trades):
+                    if trade.get('fee', {}).get('cost') is None:
+                        takerOrMaker = trade.get('takerOrMaker', 'taker')
+                        if pair_fees.get(takerOrMaker) is not None:
+                            trades[idx]['fee'] = {
+                                'currency': self.get_pair_quote_currency(pair),
+                                'cost': trade['cost'] * pair_fees[takerOrMaker],
+                                'rate': pair_fees[takerOrMaker],
+                            }
+        return trades
+
+    def fetch_stoploss_order(self, order_id: str, pair: str, params={}) -> Dict:
+        return self.fetch_order(
+            order_id=order_id,
+            pair=pair,
+            params={'stop': True}
+        )
+
+    def cancel_stoploss_order(self, order_id: str, pair: str, params={}) -> Dict:
+        return self.cancel_order(
+            order_id=order_id,
+            pair=pair,
+            params={'stop': True}
+        )
+
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
+        """
+        Verify stop_loss against stoploss-order value (limit or price)
+        Returns True if adjustment is necessary.
+        """
+        return ((side == "sell" and stop_loss > float(order['stopPrice'])) or
+                (side == "buy" and stop_loss < float(order['stopPrice'])))
diff --git a/freqtrade/exchange/huobi.py b/freqtrade/exchange/huobi.py
new file mode 100644
index 000000000..71c4d1cf6
--- /dev/null
+++ b/freqtrade/exchange/huobi.py
@@ -0,0 +1,39 @@
+""" Huobi exchange subclass """
+import logging
+from typing import Dict
+
+from freqtrade.exchange import Exchange
+
+
+logger = logging.getLogger(__name__)
+
+
+class Huobi(Exchange):
+    """
+    Huobi exchange class. Contains adjustments needed for Freqtrade to work
+    with this exchange.
+    """
+
+    _ft_has: Dict = {
+        "stoploss_on_exchange": True,
+        "stoploss_order_types": {"limit": "stop-limit"},
+        "ohlcv_candle_limit": 1000,
+        "l2_limit_range": [5, 10, 20],
+        "l2_limit_range_required": False,
+    }
+
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
+        """
+        Verify stop_loss against stoploss-order value (limit or price)
+        Returns True if adjustment is necessary.
+        """
+        return order['type'] == 'stop' and stop_loss > float(order['stopPrice'])
+
+    def _get_stop_params(self, ordertype: str, stop_price: float) -> Dict:
+
+        params = self._params.copy()
+        params.update({
+            "stopPrice": stop_price,
+            "operator": "lte",
+        })
+        return params
diff --git a/freqtrade/exchange/kraken.py b/freqtrade/exchange/kraken.py
index 1b069aa6c..94727afa6 100644
--- a/freqtrade/exchange/kraken.py
+++ b/freqtrade/exchange/kraken.py
@@ -1,9 +1,12 @@
 """ Kraken exchange subclass """
 import logging
-from typing import Any, Dict
+from datetime import datetime
+from typing import Any, Dict, List, Optional, Tuple
 
 import ccxt
+from pandas import DataFrame
 
+from freqtrade.enums import MarginMode, TradingMode
 from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
                                   OperationalException, TemporaryError)
 from freqtrade.exchange import Exchange
@@ -21,8 +24,15 @@ class Kraken(Exchange):
         "ohlcv_candle_limit": 720,
         "trades_pagination": "id",
         "trades_pagination_arg": "since",
+        "mark_ohlcv_timeframe": "4h",
     }
 
+    _supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
+        # TradingMode.SPOT always supported and not required in this list
+        # (TradingMode.MARGIN, MarginMode.CROSS),
+        # (TradingMode.FUTURES, MarginMode.CROSS)
+    ]
+
     def market_is_tradable(self, market: Dict[str, Any]) -> bool:
         """
         Check if the market symbol is tradable by Freqtrade.
@@ -33,6 +43,12 @@ class Kraken(Exchange):
         return (parent_check and
                 market.get('darkpool', False) is False)
 
+    def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
+        # Only fetch tickers for current stake currency
+        # Otherwise the request for kraken becomes too large.
+        symbols = list(self.get_markets(quote_currencies=[self._config['stake_currency']]))
+        return super().get_tickers(symbols=symbols, cached=cached)
+
     @retrier
     def get_balances(self) -> dict:
         if self._config['dry_run']:
@@ -67,26 +83,36 @@ class Kraken(Exchange):
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
 
-    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
         """
         Verify stop_loss against stoploss-order value (limit or price)
         Returns True if adjustment is necessary.
         """
-        return (order['type'] in ('stop-loss', 'stop-loss-limit')
-                and stop_loss > float(order['price']))
+        return (order['type'] in ('stop-loss', 'stop-loss-limit') and (
+                (side == "sell" and stop_loss > float(order['price'])) or
+                (side == "buy" and stop_loss < float(order['price']))
+                ))
 
     @retrier(retries=0)
-    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+    def stoploss(self, pair: str, amount: float, stop_price: float,
+                 order_types: Dict, side: str, leverage: float) -> Dict:
         """
         Creates a stoploss market order.
         Stoploss market orders is the only stoploss type supported by kraken.
+        TODO: investigate if this can be combined with generic implementation
+              (careful, prices are reversed)
         """
         params = self._params.copy()
+        if self.trading_mode == TradingMode.FUTURES:
+            params.update({'reduceOnly': True})
 
         if order_types.get('stoploss', 'market') == 'limit':
             ordertype = "stop-loss-limit"
             limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
-            limit_rate = stop_price * limit_price_pct
+            if side == "sell":
+                limit_rate = stop_price * limit_price_pct
+            else:
+                limit_rate = stop_price * (2 - limit_price_pct)
             params['price2'] = self.price_to_precision(pair, limit_rate)
         else:
             ordertype = "stop-loss"
@@ -95,13 +121,13 @@ class Kraken(Exchange):
 
         if self._config['dry_run']:
             dry_order = self.create_dry_run_order(
-                pair, ordertype, "sell", amount, stop_price)
+                pair, ordertype, side, amount, stop_price, leverage, stop_loss=True)
             return dry_order
 
         try:
             amount = self.amount_to_precision(pair, amount)
 
-            order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
+            order = self._api.create_order(symbol=pair, type=ordertype, side=side,
                                            amount=amount, price=stop_price, params=params)
             self._log_exchange_response('create_stoploss_order', order)
             logger.info('stoploss order added for %s. '
@@ -109,18 +135,81 @@ class Kraken(Exchange):
             return order
         except ccxt.InsufficientFunds as e:
             raise InsufficientFundsError(
-                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
+                f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
                 f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
                 f'Message: {e}') from e
         except ccxt.InvalidOrder as e:
             raise InvalidOrderException(
-                f'Could not create {ordertype} sell order on market {pair}. '
+                f'Could not create {ordertype} {side} order on market {pair}. '
                 f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
                 f'Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
+                f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
+
+    def _set_leverage(
+        self,
+        leverage: float,
+        pair: Optional[str] = None,
+        trading_mode: Optional[TradingMode] = None
+    ):
+        """
+        Kraken set's the leverage as an option in the order object, so we need to
+        add it to params
+        """
+        return
+
+    def _get_params(
+        self,
+        ordertype: str,
+        leverage: float,
+        reduceOnly: bool,
+        time_in_force: str = 'gtc'
+    ) -> Dict:
+        params = super()._get_params(
+            ordertype=ordertype,
+            leverage=leverage,
+            reduceOnly=reduceOnly,
+            time_in_force=time_in_force,
+        )
+        if leverage > 1.0:
+            params['leverage'] = round(leverage)
+        return params
+
+    def calculate_funding_fees(
+        self,
+        df: DataFrame,
+        amount: float,
+        is_short: bool,
+        open_date: datetime,
+        close_date: Optional[datetime] = None,
+        time_in_ratio: Optional[float] = None
+    ) -> float:
+        """
+        # ! This method will always error when run by Freqtrade because time_in_ratio is never
+        # ! passed to _get_funding_fee. For kraken futures to work in dry run and backtesting
+        # ! functionality must be added that passes the parameter time_in_ratio to
+        # ! _get_funding_fee when using Kraken
+        calculates the sum of all funding fees that occurred for a pair during a futures trade
+        :param df: Dataframe containing combined funding and mark rates
+                   as `open_fund` and `open_mark`.
+        :param amount: The quantity of the trade
+        :param is_short: trade direction
+        :param open_date: The date and time that the trade started
+        :param close_date: The date and time that the trade ended
+        :param time_in_ratio: Not used by most exchange classes
+        """
+        if not time_in_ratio:
+            raise OperationalException(
+                f"time_in_ratio is required for {self.name}._get_funding_fee")
+        fees: float = 0
+
+        if not df.empty:
+            df = df[(df['date'] >= open_date) & (df['date'] <= close_date)]
+            fees = sum(df['open_fund'] * df['open_mark'] * amount * time_in_ratio)
+
+        return fees if is_short else -fees
diff --git a/freqtrade/exchange/kucoin.py b/freqtrade/exchange/kucoin.py
index 5d818f6a2..f23189b3c 100644
--- a/freqtrade/exchange/kucoin.py
+++ b/freqtrade/exchange/kucoin.py
@@ -1,4 +1,4 @@
-""" Kucoin exchange subclass """
+"""Kucoin exchange subclass."""
 import logging
 from typing import Dict
 
@@ -9,9 +9,9 @@ logger = logging.getLogger(__name__)
 
 
 class Kucoin(Exchange):
-    """
-    Kucoin exchange class. Contains adjustments needed for Freqtrade to work
-    with this exchange.
+    """Kucoin exchange class.
+
+    Contains adjustments needed for Freqtrade to work with this exchange.
 
     Please note that this exchange is not included in the list of exchanges
     officially supported by the Freqtrade development team. So some features
@@ -19,8 +19,27 @@ class Kucoin(Exchange):
     """
 
     _ft_has: Dict = {
+        "stoploss_on_exchange": True,
+        "stoploss_order_types": {"limit": "limit", "market": "market"},
         "l2_limit_range": [20, 100],
         "l2_limit_range_required": False,
         "order_time_in_force": ['gtc', 'fok', 'ioc'],
         "time_in_force_parameter": "timeInForce",
+        "ohlcv_candle_limit": 1500,
     }
+
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
+        """
+        Verify stop_loss against stoploss-order value (limit or price)
+        Returns True if adjustment is necessary.
+        """
+        return order['info'].get('stop') is not None and stop_loss > float(order['stopPrice'])
+
+    def _get_stop_params(self, ordertype: str, stop_price: float) -> Dict:
+
+        params = self._params.copy()
+        params.update({
+            'stopPrice': stop_price,
+            'stop': 'loss'
+            })
+        return params
diff --git a/freqtrade/exchange/okx.py b/freqtrade/exchange/okx.py
new file mode 100644
index 000000000..fb7388ee1
--- /dev/null
+++ b/freqtrade/exchange/okx.py
@@ -0,0 +1,88 @@
+import logging
+from typing import Dict, List, Tuple
+
+import ccxt
+
+from freqtrade.enums import MarginMode, TradingMode
+from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError
+from freqtrade.exchange import Exchange
+from freqtrade.exchange.common import retrier
+
+
+logger = logging.getLogger(__name__)
+
+
+class Okx(Exchange):
+    """Okx exchange class.
+
+    Contains adjustments needed for Freqtrade to work with this exchange.
+    """
+
+    _ft_has: Dict = {
+        "ohlcv_candle_limit": 300,
+        "mark_ohlcv_timeframe": "4h",
+        "funding_fee_timeframe": "8h",
+    }
+    _ft_has_futures: Dict = {
+        "tickers_have_quoteVolume": False,
+    }
+
+    _supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
+        # TradingMode.SPOT always supported and not required in this list
+        # (TradingMode.MARGIN, MarginMode.CROSS),
+        # (TradingMode.FUTURES, MarginMode.CROSS),
+        (TradingMode.FUTURES, MarginMode.ISOLATED),
+    ]
+
+    def _get_params(
+        self,
+        ordertype: str,
+        leverage: float,
+        reduceOnly: bool,
+        time_in_force: str = 'gtc',
+    ) -> Dict:
+        params = super()._get_params(
+            ordertype=ordertype,
+            leverage=leverage,
+            reduceOnly=reduceOnly,
+            time_in_force=time_in_force,
+        )
+        if self.trading_mode == TradingMode.FUTURES and self.margin_mode:
+            params['tdMode'] = self.margin_mode.value
+        return params
+
+    @retrier
+    def _lev_prep(self, pair: str, leverage: float, side: str):
+        if self.trading_mode != TradingMode.SPOT and self.margin_mode is not None:
+            try:
+                # TODO-lev: Test me properly (check mgnMode passed)
+                self._api.set_leverage(
+                    leverage=leverage,
+                    symbol=pair,
+                    params={
+                        "mgnMode": self.margin_mode.value,
+                        # "posSide": "net"",
+                    })
+            except ccxt.DDoSProtection as e:
+                raise DDosProtection(e) from e
+            except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+                raise TemporaryError(
+                    f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
+            except ccxt.BaseError as e:
+                raise OperationalException(e) from e
+
+    def get_max_pair_stake_amount(
+        self,
+        pair: str,
+        price: float,
+        leverage: float = 1.0
+    ) -> float:
+
+        if self.trading_mode == TradingMode.SPOT:
+            return float('inf')  # Not actually inf, but this probably won't matter for SPOT
+
+        if pair not in self._leverage_tiers:
+            return float('inf')
+
+        pair_tiers = self._leverage_tiers[pair]
+        return pair_tiers[-1]['max'] / leverage
diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 3a9b21b7c..57d7cac3c 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -4,19 +4,21 @@ Freqtrade is the main module of this bot. It contains the class Freqtrade()
 import copy
 import logging
 import traceback
-from datetime import datetime, timezone
+from datetime import datetime, time, timezone
 from math import isclose
 from threading import Lock
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Tuple
 
-import arrow
+from schedule import Scheduler
 
 from freqtrade import __version__, constants
 from freqtrade.configuration import validate_config_consistency
+from freqtrade.constants import LongShort
 from freqtrade.data.converter import order_book_to_dataframe
 from freqtrade.data.dataprovider import DataProvider
 from freqtrade.edge import Edge
-from freqtrade.enums import RPCMessageType, SellType, State
+from freqtrade.enums import (ExitCheckTuple, ExitType, RPCMessageType, RunMode, SignalDirection,
+                             State, TradingMode)
 from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError,
                                   InvalidOrderException, PricingError)
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
@@ -27,7 +29,7 @@ from freqtrade.plugins.pairlistmanager import PairListManager
 from freqtrade.plugins.protectionmanager import ProtectionManager
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
 from freqtrade.rpc import RPCManager
-from freqtrade.strategy.interface import IStrategy, SellCheckTuple
+from freqtrade.strategy.interface import IStrategy
 from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
 from freqtrade.wallets import Wallets
 
@@ -98,10 +100,28 @@ class FreqtradeBot(LoggingMixin):
         initial_state = self.config.get('initial_state')
         self.state = State[initial_state.upper()] if initial_state else State.STOPPED
 
-        # Protect sell-logic from forcesell and vice versa
+        # Protect exit-logic from forcesell and vice versa
         self._exit_lock = Lock()
         LoggingMixin.__init__(self, logger, timeframe_to_seconds(self.strategy.timeframe))
 
+        self.trading_mode: TradingMode = self.config.get('trading_mode', TradingMode.SPOT)
+
+        self._schedule = Scheduler()
+
+        if self.trading_mode == TradingMode.FUTURES:
+
+            def update():
+                self.update_funding_fees()
+                self.wallets.update()
+
+            # TODO: This would be more efficient if scheduled in utc time, and performed at each
+            # TODO: funding interval, specified by funding_fee_times on the exchange classes
+            for time_slot in range(0, 24):
+                for minutes in [0, 15, 30, 45]:
+                    t = str(time(time_slot, minutes, 2))
+                    self._schedule.every().day.at(t).do(update)
+        self.last_process = datetime(1970, 1, 1, tzinfo=timezone.utc)
+
     def notify_status(self, msg: str) -> None:
         """
         Public method for users of this class (worker, etc.) to send notifications
@@ -126,6 +146,7 @@ class FreqtradeBot(LoggingMixin):
 
         self.rpc.cleanup()
         cleanup_db()
+        self.exchange.close()
 
     def startup(self) -> None:
         """
@@ -139,7 +160,7 @@ class FreqtradeBot(LoggingMixin):
 
         # Only update open orders on startup
         # This will update the database after the initial migration
-        self.update_open_orders()
+        self.startup_update_open_orders()
 
     def process(self) -> None:
         """
@@ -170,19 +191,26 @@ class FreqtradeBot(LoggingMixin):
             # Check and handle any timed out open orders
             self.check_handle_timedout()
 
-        # Protect from collisions with forcesell.
+        # Protect from collisions with force_exit.
         # Without this, freqtrade my try to recreate stoploss_on_exchange orders
-        # while selling is in process, since telegram messages arrive in an different thread.
+        # while exiting is in process, since telegram messages arrive in an different thread.
         with self._exit_lock:
             trades = Trade.get_open_trades()
             # First process current opened trades (positions)
             self.exit_positions(trades)
 
+        # Check if we need to adjust our current positions before attempting to buy new trades.
+        if self.strategy.position_adjustment_enable:
+            with self._exit_lock:
+                self.process_open_trade_positions()
+
         # Then looking for buy opportunities
         if self.get_free_open_trades():
             self.enter_positions()
-
+        if self.trading_mode == TradingMode.FUTURES:
+            self._schedule.run_pending()
         Trade.commit()
+        self.last_process = datetime.now(timezone.utc)
 
     def process_stopped(self) -> None:
         """
@@ -193,19 +221,20 @@ class FreqtradeBot(LoggingMixin):
 
     def check_for_open_trades(self):
         """
-        Notify the user when the bot is stopped
+        Notify the user when the bot is stopped (not reloaded)
         and there are still open trades active.
         """
         open_trades = Trade.get_trades([Trade.is_open.is_(True)]).all()
 
-        if len(open_trades) != 0:
+        if len(open_trades) != 0 and self.state != State.RELOAD_CONFIG:
             msg = {
                 'type': RPCMessageType.WARNING,
-                'status':  f"{len(open_trades)} open trades active.\n\n"
-                           f"Handle these trades manually on {self.exchange.name}, "
-                           f"or '/start' the bot again and use '/stopbuy' "
-                           f"to handle open trades gracefully. \n"
-                           f"{'Trades are simulated.' if self.config['dry_run'] else ''}",
+                'status':
+                    f"{len(open_trades)} open trades active.\n\n"
+                    f"Handle these trades manually on {self.exchange.name}, "
+                    f"or '/start' the bot again and use '/stopbuy' "
+                    f"to handle open trades gracefully. \n"
+                    f"{'Note: Trades are simulated (dry run).' if self.config['dry_run'] else ''}",
             }
             self.rpc.send_msg(msg)
 
@@ -237,7 +266,21 @@ class FreqtradeBot(LoggingMixin):
         open_trades = len(Trade.get_open_trades())
         return max(0, self.config['max_open_trades'] - open_trades)
 
-    def update_open_orders(self):
+    def update_funding_fees(self):
+        if self.trading_mode == TradingMode.FUTURES:
+            trades = Trade.get_open_trades()
+            for trade in trades:
+                funding_fees = self.exchange.get_funding_fees(
+                    pair=trade.pair,
+                    amount=trade.amount,
+                    is_short=trade.is_short,
+                    open_date=trade.open_date_utc
+                )
+                trade.funding_fees = funding_fees
+        else:
+            return 0.0
+
+    def startup_update_open_orders(self):
         """
         Updates open orders based on order list kept in the database.
         Mainly updates the state of orders - but may also close trades
@@ -259,6 +302,9 @@ class FreqtradeBot(LoggingMixin):
 
                 logger.warning(f"Error updating Order {order.order_id} due to {e}")
 
+        if self.trading_mode == TradingMode.FUTURES:
+            self._schedule.run_pending()
+
     def update_closed_trades_without_assigned_fees(self):
         """
         Update closed trades without close fees assigned.
@@ -268,51 +314,36 @@ class FreqtradeBot(LoggingMixin):
             # Updating open orders in dry-run does not make sense and will fail.
             return
 
-        trades: List[Trade] = Trade.get_sold_trades_without_assigned_fees()
+        trades: List[Trade] = Trade.get_closed_trades_without_assigned_fees()
         for trade in trades:
-
-            if not trade.is_open and not trade.fee_updated('sell'):
+            if not trade.is_open and not trade.fee_updated(trade.exit_side):
                 # Get sell fee
-                order = trade.select_order('sell', False)
+                order = trade.select_order(trade.exit_side, False)
                 if order:
-                    logger.info(f"Updating sell-fee on trade {trade} for order {order.order_id}.")
+                    logger.info(
+                        f"Updating {trade.exit_side}-fee on trade {trade}"
+                        f"for order {order.order_id}."
+                    )
                     self.update_trade_state(trade, order.order_id,
-                                            stoploss_order=order.ft_order_side == 'stoploss')
+                                            stoploss_order=order.ft_order_side == 'stoploss',
+                                            send_msg=False)
 
         trades: List[Trade] = Trade.get_open_trades_without_assigned_fees()
         for trade in trades:
-            if trade.is_open and not trade.fee_updated('buy'):
-                order = trade.select_order('buy', False)
-                if order:
-                    logger.info(f"Updating buy-fee on trade {trade} for order {order.order_id}.")
-                    self.update_trade_state(trade, order.order_id)
+            if trade.is_open and not trade.fee_updated(trade.entry_side):
+                order = trade.select_order(trade.entry_side, False)
+                open_order = trade.select_order(trade.entry_side, True)
+                if order and open_order is None:
+                    logger.info(
+                        f"Updating {trade.entry_side}-fee on trade {trade}"
+                        f"for order {order.order_id}."
+                    )
+                    self.update_trade_state(trade, order.order_id, send_msg=False)
 
     def handle_insufficient_funds(self, trade: Trade):
-        """
-        Determine if we ever opened a sell order for this trade.
-        If not, try update buy fees - otherwise "refind" the open order we obviously lost.
-        """
-        sell_order = trade.select_order('sell', None)
-        if sell_order:
-            self.refind_lost_order(trade)
-        else:
-            self.reupdate_enter_order_fees(trade)
-
-    def reupdate_enter_order_fees(self, trade: Trade):
-        """
-        Get buy order from database, and try to reupdate.
-        Handles trades where the initial fee-update did not work.
-        """
-        logger.info(f"Trying to reupdate buy fees for {trade}")
-        order = trade.select_order('buy', False)
-        if order:
-            logger.info(f"Updating buy-fee on trade {trade} for order {order.order_id}.")
-            self.update_trade_state(trade, order.order_id)
-
-    def refind_lost_order(self, trade):
         """
         Try refinding a lost trade.
-        Only used when InsufficientFunds appears on sell orders (stoploss or sell).
+        Only used when InsufficientFunds appears on exit orders (stoploss or long sell/short buy).
         Tries to walk the stored orders and sell them off eventually.
         """
         logger.info(f"Trying to refind lost order for {trade}")
@@ -322,9 +353,6 @@ class FreqtradeBot(LoggingMixin):
             if not order.ft_is_open:
                 logger.debug(f"Order {order} is no longer open.")
                 continue
-            if order.ft_order_side == 'buy':
-                # Skip buy side - this is handled by reupdate_buy_order_fees
-                continue
             try:
                 fo = self.exchange.fetch_order_or_stoploss_order(order.order_id, order.ft_pair,
                                                                  order.ft_order_side == 'stoploss')
@@ -332,10 +360,13 @@ class FreqtradeBot(LoggingMixin):
                     if fo and fo['status'] == 'open':
                         # Assume this as the open stoploss order
                         trade.stoploss_order_id = order.order_id
-                elif order.ft_order_side == 'sell':
+                elif order.ft_order_side == trade.exit_side:
                     if fo and fo['status'] == 'open':
                         # Assume this as the open order
                         trade.open_order_id = order.order_id
+                elif order.ft_order_side == trade.entry_side:
+                    if fo and fo['status'] == 'open':
+                        trade.open_order_id = order.order_id
                 if fo:
                     logger.info(f"Found {order} for trade {trade}.")
                     self.update_trade_state(trade, order.order_id, fo,
@@ -350,7 +381,7 @@ class FreqtradeBot(LoggingMixin):
 
     def enter_positions(self) -> int:
         """
-        Tries to execute buy orders for new trades (positions)
+        Tries to execute entry orders for new trades (positions)
         """
         trades_created = 0
 
@@ -366,7 +397,7 @@ class FreqtradeBot(LoggingMixin):
 
         if not whitelist:
             logger.info("No currency pair in active pair whitelist, "
-                        "but checking to sell open trades.")
+                        "but checking to exit open trades.")
             return trades_created
         if PairLocks.is_global_lock():
             lock = PairLocks.get_pair_longest_lock('*')
@@ -385,7 +416,7 @@ class FreqtradeBot(LoggingMixin):
                 logger.warning('Unable to create trade for %s: %s', pair, exception)
 
         if not trades_created:
-            logger.debug("Found no buy signals for whitelisted currencies. Trying again...")
+            logger.debug("Found no enter signals for whitelisted currencies. Trying again...")
 
         return trades_created
 
@@ -420,28 +451,94 @@ class FreqtradeBot(LoggingMixin):
             return False
 
         # running get_signal on historical data fetched
-        (buy, sell, buy_tag) = self.strategy.get_signal(
+        (signal, enter_tag) = self.strategy.get_entry_signal(
             pair,
             self.strategy.timeframe,
             analyzed_df
         )
 
-        if buy and not sell:
+        if signal:
             stake_amount = self.wallets.get_trade_stake_amount(pair, self.edge)
 
-            bid_check_dom = self.config.get('bid_strategy', {}).get('check_depth_of_market', {})
+            bid_check_dom = self.config.get('entry_pricing', {}).get('check_depth_of_market', {})
             if ((bid_check_dom.get('enabled', False)) and
                     (bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
-                if self._check_depth_of_market_buy(pair, bid_check_dom):
-                    return self.execute_entry(pair, stake_amount, buy_tag=buy_tag)
+                if self._check_depth_of_market(pair, bid_check_dom, side=signal):
+                    return self.execute_entry(
+                        pair,
+                        stake_amount,
+                        enter_tag=enter_tag,
+                        is_short=(signal == SignalDirection.SHORT)
+                    )
                 else:
                     return False
 
-            return self.execute_entry(pair, stake_amount, buy_tag=buy_tag)
+            return self.execute_entry(
+                pair,
+                stake_amount,
+                enter_tag=enter_tag,
+                is_short=(signal == SignalDirection.SHORT)
+            )
         else:
             return False
 
-    def _check_depth_of_market_buy(self, pair: str, conf: Dict) -> bool:
+#
+# BUY / increase positions / DCA logic and methods
+#
+    def process_open_trade_positions(self):
+        """
+        Tries to execute additional buy or sell orders for open trades (positions)
+        """
+        # Walk through each pair and check if it needs changes
+        for trade in Trade.get_open_trades():
+            # If there is any open orders, wait for them to finish.
+            if trade.open_order_id is None:
+                try:
+                    self.check_and_call_adjust_trade_position(trade)
+                except DependencyException as exception:
+                    logger.warning(
+                        f"Unable to adjust position of trade for {trade.pair}: {exception}")
+
+    def check_and_call_adjust_trade_position(self, trade: Trade):
+        """
+        Check the implemented trading strategy for adjustment command.
+        If the strategy triggers the adjustment, a new order gets issued.
+        Once that completes, the existing trade is modified to match new data.
+        """
+        if self.strategy.max_entry_position_adjustment > -1:
+            count_of_buys = trade.nr_of_successful_entries
+            if count_of_buys > self.strategy.max_entry_position_adjustment:
+                logger.debug(f"Max adjustment entries for {trade.pair} has been reached.")
+                return
+        else:
+            logger.debug("Max adjustment entries is set to unlimited.")
+        current_rate = self.exchange.get_rate(
+            trade.pair, side='entry', is_short=trade.is_short, refresh=True)
+        current_profit = trade.calc_profit_ratio(current_rate)
+
+        min_stake_amount = self.exchange.get_min_pair_stake_amount(trade.pair,
+                                                                   current_rate,
+                                                                   self.strategy.stoploss)
+        max_stake_amount = self.exchange.get_max_pair_stake_amount(trade.pair, current_rate)
+        stake_available = self.wallets.get_available_stake_amount()
+        logger.debug(f"Calling adjust_trade_position for pair {trade.pair}")
+        stake_amount = strategy_safe_wrapper(self.strategy.adjust_trade_position,
+                                             default_retval=None)(
+            trade=trade, current_time=datetime.now(timezone.utc), current_rate=current_rate,
+            current_profit=current_profit, min_stake=min_stake_amount,
+            max_stake=min(max_stake_amount, stake_available))
+
+        if stake_amount is not None and stake_amount > 0.0:
+            # We should increase our position
+            self.execute_entry(trade.pair, stake_amount, trade=trade, is_short=trade.is_short)
+
+        if stake_amount is not None and stake_amount < 0.0:
+            # We should decrease our position
+            # TODO: Selling part of the trade not implemented yet.
+            logger.error(f"Unable to decrease trade position / sell partially"
+                         f" for pair {trade.pair}, feature not implemented.")
+
+    def _check_depth_of_market(self, pair: str, conf: Dict, side: SignalDirection) -> bool:
         """
         Checks depth of market before executing a buy
         """
@@ -451,9 +548,17 @@ class FreqtradeBot(LoggingMixin):
         order_book_data_frame = order_book_to_dataframe(order_book['bids'], order_book['asks'])
         order_book_bids = order_book_data_frame['b_size'].sum()
         order_book_asks = order_book_data_frame['a_size'].sum()
-        bids_ask_delta = order_book_bids / order_book_asks
+
+        entry_side = order_book_bids if side == SignalDirection.LONG else order_book_asks
+        exit_side = order_book_asks if side == SignalDirection.LONG else order_book_bids
+        bids_ask_delta = entry_side / exit_side
+
+        bids = f"Bids: {order_book_bids}"
+        asks = f"Asks: {order_book_asks}"
+        delta = f"Delta: {bids_ask_delta}"
+
         logger.info(
-            f"Bids: {order_book_bids}, Asks: {order_book_asks}, Delta: {bids_ask_delta}, "
+            f"{bids}, {asks}, {delta}, Direction: {side.value}"
             f"Bid Price: {order_book['bids'][0][0]}, Ask Price: {order_book['asks'][0][0]}, "
             f"Immediate Bid Quantity: {order_book['bids'][0][1]}, "
             f"Immediate Ask Quantity: {order_book['asks'][0][1]}."
@@ -465,153 +570,287 @@ class FreqtradeBot(LoggingMixin):
             logger.info(f"Bids to asks delta for {pair} does not satisfy condition.")
             return False
 
-    def execute_entry(self, pair: str, stake_amount: float, price: Optional[float] = None,
-                      forcebuy: bool = False, buy_tag: Optional[str] = None) -> bool:
+    def execute_entry(
+        self,
+        pair: str,
+        stake_amount: float,
+        price: Optional[float] = None,
+        *,
+        is_short: bool = False,
+        ordertype: Optional[str] = None,
+        enter_tag: Optional[str] = None,
+        trade: Optional[Trade] = None,
+    ) -> bool:
         """
         Executes a limit buy for the given pair
         :param pair: pair for which we want to create a LIMIT_BUY
         :param stake_amount: amount of stake-currency for the pair
+        :param leverage: amount of leverage applied to this trade
         :return: True if a buy order is created, false if it fails.
         """
-        time_in_force = self.strategy.order_time_in_force['buy']
+        time_in_force = self.strategy.order_time_in_force['entry']
 
-        if price:
-            enter_limit_requested = price
-        else:
-            # Calculate price
-            proposed_enter_rate = self.exchange.get_rate(pair, refresh=True, side="buy")
-            custom_entry_price = strategy_safe_wrapper(self.strategy.custom_entry_price,
-                                                       default_retval=proposed_enter_rate)(
-                pair=pair, current_time=datetime.now(timezone.utc),
-                proposed_rate=proposed_enter_rate)
+        [side, name] = ['sell', 'Short'] if is_short else ['buy', 'Long']
+        trade_side: LongShort = 'short' if is_short else 'long'
+        pos_adjust = trade is not None
 
-            enter_limit_requested = self.get_valid_price(custom_entry_price, proposed_enter_rate)
-
-        if not enter_limit_requested:
-            raise PricingError('Could not determine buy price.')
-
-        min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, enter_limit_requested,
-                                                                   self.strategy.stoploss)
-
-        if not self.edge:
-            max_stake_amount = self.wallets.get_available_stake_amount()
-            stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
-                                                 default_retval=stake_amount)(
-                pair=pair, current_time=datetime.now(timezone.utc),
-                current_rate=enter_limit_requested, proposed_stake=stake_amount,
-                min_stake=min_stake_amount, max_stake=max_stake_amount)
-        stake_amount = self.wallets._validate_stake_amount(pair, stake_amount, min_stake_amount)
+        enter_limit_requested, stake_amount, leverage = self.get_valid_enter_price_and_stake(
+            pair, price, stake_amount, trade_side, enter_tag, trade)
 
         if not stake_amount:
+            logger.info(f"No stake amount to enter a trade for {pair}.")
             return False
 
-        logger.info(f"Buy signal found: about create a new trade for {pair} with stake_amount: "
-                    f"{stake_amount} ...")
+        if pos_adjust:
+            logger.info(f"Position adjust: about to create a new order for {pair} with stake: "
+                        f"{stake_amount} for {trade}")
+        else:
+            logger.info(
+                f"{name} signal found: about create a new trade for {pair} with stake_amount: "
+                f"{stake_amount} ...")
 
-        amount = stake_amount / enter_limit_requested
-        order_type = self.strategy.order_types['buy']
-        if forcebuy:
-            # Forcebuy can define a different ordertype
-            order_type = self.strategy.order_types.get('forcebuy', order_type)
+        amount = (stake_amount / enter_limit_requested) * leverage
+        order_type = ordertype or self.strategy.order_types['entry']
 
-        if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
+        if not pos_adjust and not strategy_safe_wrapper(
+                self.strategy.confirm_trade_entry, default_retval=True)(
                 pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
-                time_in_force=time_in_force, current_time=datetime.now(timezone.utc)):
+                time_in_force=time_in_force, current_time=datetime.now(timezone.utc),
+                entry_tag=enter_tag, side=trade_side):
             logger.info(f"User requested abortion of buying {pair}")
             return False
-        amount = self.exchange.amount_to_precision(pair, amount)
-        order = self.exchange.create_order(pair=pair, ordertype=order_type, side="buy",
-                                           amount=amount, rate=enter_limit_requested,
-                                           time_in_force=time_in_force)
-        order_obj = Order.parse_from_ccxt_object(order, pair, 'buy')
+        order = self.exchange.create_order(
+            pair=pair,
+            ordertype=order_type,
+            side=side,
+            amount=amount,
+            rate=enter_limit_requested,
+            reduceOnly=False,
+            time_in_force=time_in_force,
+            leverage=leverage
+        )
+        order_obj = Order.parse_from_ccxt_object(order, pair, side)
         order_id = order['id']
         order_status = order.get('status', None)
+        logger.info(f"Order #{order_id} was created for {pair} and status is {order_status}.")
 
         # we assume the order is executed at the price requested
         enter_limit_filled_price = enter_limit_requested
         amount_requested = amount
 
         if order_status == 'expired' or order_status == 'rejected':
-            order_tif = self.strategy.order_time_in_force['buy']
 
             # return false if the order is not filled
             if float(order['filled']) == 0:
-                logger.warning('Buy %s order with time in force %s for %s is %s by %s.'
-                               ' zero amount is fulfilled.',
-                               order_tif, order_type, pair, order_status, self.exchange.name)
+                logger.warning(f'{name} {time_in_force} order with time in force {order_type} '
+                               f'for {pair} is {order_status} by {self.exchange.name}.'
+                               ' zero amount is fulfilled.')
                 return False
             else:
                 # the order is partially fulfilled
                 # in case of IOC orders we can check immediately
                 # if the order is fulfilled fully or partially
-                logger.warning('Buy %s order with time in force %s for %s is %s by %s.'
+                logger.warning('%s %s order with time in force %s for %s is %s by %s.'
                                ' %s amount fulfilled out of %s (%s remaining which is canceled).',
-                               order_tif, order_type, pair, order_status, self.exchange.name,
-                               order['filled'], order['amount'], order['remaining']
+                               name, time_in_force, order_type, pair, order_status,
+                               self.exchange.name, order['filled'], order['amount'],
+                               order['remaining']
                                )
-                stake_amount = order['cost']
                 amount = safe_value_fallback(order, 'filled', 'amount')
                 enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
 
         # in case of FOK the order may be filled immediately and fully
         elif order_status == 'closed':
-            stake_amount = order['cost']
             amount = safe_value_fallback(order, 'filled', 'amount')
             enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
 
+        # TODO: this might be unnecessary, as we're calling it in update_trade_state.
+        isolated_liq = self.exchange.get_liquidation_price(
+            leverage=leverage,
+            pair=pair,
+            amount=amount,
+            open_rate=enter_limit_filled_price,
+            is_short=is_short
+        )
+        interest_rate = self.exchange.get_interest_rate()
+
         # Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
         fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
-        trade = Trade(
-            pair=pair,
-            stake_amount=stake_amount,
-            amount=amount,
-            is_open=True,
-            amount_requested=amount_requested,
-            fee_open=fee,
-            fee_close=fee,
-            open_rate=enter_limit_filled_price,
-            open_rate_requested=enter_limit_requested,
-            open_date=datetime.utcnow(),
-            exchange=self.exchange.id,
-            open_order_id=order_id,
-            strategy=self.strategy.get_strategy_name(),
-            buy_tag=buy_tag,
-            timeframe=timeframe_to_minutes(self.config['timeframe'])
-        )
+        base_currency = self.exchange.get_pair_base_currency(pair)
+        open_date = datetime.now(timezone.utc)
+        funding_fees = self.exchange.get_funding_fees(
+            pair=pair, amount=amount, is_short=is_short, open_date=open_date)
+        # This is a new trade
+        if trade is None:
+            trade = Trade(
+                pair=pair,
+                base_currency=base_currency,
+                stake_currency=self.config['stake_currency'],
+                stake_amount=stake_amount,
+                amount=amount,
+                is_open=True,
+                amount_requested=amount_requested,
+                fee_open=fee,
+                fee_close=fee,
+                open_rate=enter_limit_filled_price,
+                open_rate_requested=enter_limit_requested,
+                open_date=open_date,
+                exchange=self.exchange.id,
+                open_order_id=order_id,
+                strategy=self.strategy.get_strategy_name(),
+                enter_tag=enter_tag,
+                timeframe=timeframe_to_minutes(self.config['timeframe']),
+                leverage=leverage,
+                is_short=is_short,
+                interest_rate=interest_rate,
+                liquidation_price=isolated_liq,
+                trading_mode=self.trading_mode,
+                funding_fees=funding_fees
+            )
+        else:
+            # This is additional buy, we reset fee_open_currency so timeout checking can work
+            trade.is_open = True
+            trade.fee_open_currency = None
+            trade.open_rate_requested = enter_limit_requested
+            trade.open_order_id = order_id
+
         trade.orders.append(order_obj)
-
-        # Update fees if order is closed
-        if order_status == 'closed':
-            self.update_trade_state(trade, order_id, order)
-
+        trade.recalc_trade_from_orders()
         Trade.query.session.add(trade)
         Trade.commit()
 
         # Updating wallets
         self.wallets.update()
 
-        self._notify_enter(trade, order_type)
+        self._notify_enter(trade, order, order_type)
+
+        if pos_adjust:
+            if order_status == 'closed':
+                logger.info(f"DCA order closed, trade should be up to date: {trade}")
+                trade = self.cancel_stoploss_on_exchange(trade)
+            else:
+                logger.info(f"DCA order {order_status}, will wait for resolution: {trade}")
+
+        # Update fees if order is closed
+        if order_status == 'closed':
+            self.update_trade_state(trade, order_id, order)
 
         return True
 
-    def _notify_enter(self, trade: Trade, order_type: str) -> None:
+    def cancel_stoploss_on_exchange(self, trade: Trade) -> Trade:
+        # First cancelling stoploss on exchange ...
+        if self.strategy.order_types.get('stoploss_on_exchange') and trade.stoploss_order_id:
+            try:
+                logger.info(f"Canceling stoploss on exchange for {trade}")
+                co = self.exchange.cancel_stoploss_order_with_result(
+                    trade.stoploss_order_id, trade.pair, trade.amount)
+                trade.update_order(co)
+            except InvalidOrderException:
+                logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}")
+        return trade
+
+    def get_valid_enter_price_and_stake(
+        self, pair: str, price: Optional[float], stake_amount: float,
+        trade_side: LongShort,
+        entry_tag: Optional[str],
+        trade: Optional[Trade]
+    ) -> Tuple[float, float, float]:
+
+        if price:
+            enter_limit_requested = price
+        else:
+            # Calculate price
+            proposed_enter_rate = self.exchange.get_rate(
+                pair, side='entry', is_short=(trade_side == 'short'), refresh=True)
+            custom_entry_price = strategy_safe_wrapper(self.strategy.custom_entry_price,
+                                                       default_retval=proposed_enter_rate)(
+                pair=pair, current_time=datetime.now(timezone.utc),
+                proposed_rate=proposed_enter_rate, entry_tag=entry_tag,
+                side=trade_side,
+            )
+
+            enter_limit_requested = self.get_valid_price(custom_entry_price, proposed_enter_rate)
+
+        if not enter_limit_requested:
+            raise PricingError('Could not determine entry price.')
+
+        if trade is None:
+            max_leverage = self.exchange.get_max_leverage(pair, stake_amount)
+            leverage = strategy_safe_wrapper(self.strategy.leverage, default_retval=1.0)(
+                pair=pair,
+                current_time=datetime.now(timezone.utc),
+                current_rate=enter_limit_requested,
+                proposed_leverage=1.0,
+                max_leverage=max_leverage,
+                side=trade_side,
+            ) if self.trading_mode != TradingMode.SPOT else 1.0
+            # Cap leverage between 1.0 and max_leverage.
+            leverage = min(max(leverage, 1.0), max_leverage)
+        else:
+            # Changing leverage currently not possible
+            leverage = trade.leverage if trade else 1.0
+
+        # Min-stake-amount should actually include Leverage - this way our "minimal"
+        # stake- amount might be higher than necessary.
+        # We do however also need min-stake to determine leverage, therefore this is ignored as
+        # edge-case for now.
+        min_stake_amount = self.exchange.get_min_pair_stake_amount(
+            pair, enter_limit_requested, self.strategy.stoploss, leverage)
+        max_stake_amount = self.exchange.get_max_pair_stake_amount(
+            pair, enter_limit_requested, leverage)
+
+        if not self.edge and trade is None:
+            stake_available = self.wallets.get_available_stake_amount()
+            stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
+                                                 default_retval=stake_amount)(
+                pair=pair, current_time=datetime.now(timezone.utc),
+                current_rate=enter_limit_requested, proposed_stake=stake_amount,
+                min_stake=min_stake_amount, max_stake=min(max_stake_amount, stake_available),
+                entry_tag=entry_tag, side=trade_side
+            )
+
+        stake_amount = self.wallets.validate_stake_amount(
+            pair=pair,
+            stake_amount=stake_amount,
+            min_stake_amount=min_stake_amount,
+            max_stake_amount=max_stake_amount,
+        )
+
+        return enter_limit_requested, stake_amount, leverage
+
+    def _notify_enter(self, trade: Trade, order: Dict, order_type: Optional[str] = None,
+                      fill: bool = False) -> None:
         """
-        Sends rpc notification when a buy occurred.
+        Sends rpc notification when a entry order occurred.
         """
+        msg_type = RPCMessageType.ENTRY_FILL if fill else RPCMessageType.ENTRY
+        open_rate = safe_value_fallback(order, 'average', 'price')
+        if open_rate is None:
+            open_rate = trade.open_rate
+
+        current_rate = trade.open_rate_requested
+        if self.dataprovider.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
+            current_rate = self.exchange.get_rate(
+                trade.pair, side='entry', is_short=trade.is_short, refresh=False)
+
         msg = {
             'trade_id': trade.id,
-            'type': RPCMessageType.BUY,
-            'buy_tag': trade.buy_tag,
+            'type': msg_type,
+            'buy_tag': trade.enter_tag,
+            'enter_tag': trade.enter_tag,
             'exchange': self.exchange.name.capitalize(),
             'pair': trade.pair,
-            'limit': trade.open_rate,
+            'leverage': trade.leverage if trade.leverage else None,
+            'direction': 'Short' if trade.is_short else 'Long',
+            'limit': open_rate,  # Deprecated (?)
+            'open_rate': open_rate,
             'order_type': order_type,
             'stake_amount': trade.stake_amount,
             'stake_currency': self.config['stake_currency'],
             'fiat_currency': self.config.get('fiat_display_currency', None),
-            'amount': trade.amount,
+            'amount': safe_value_fallback(order, 'filled', 'amount') or trade.amount,
             'open_date': trade.open_date or datetime.utcnow(),
-            'current_rate': trade.open_rate_requested,
+            'current_rate': current_rate,
         }
 
         # Send the message
@@ -619,16 +858,20 @@ class FreqtradeBot(LoggingMixin):
 
     def _notify_enter_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
         """
-        Sends rpc notification when a buy cancel occurred.
+        Sends rpc notification when a entry order cancel occurred.
         """
-        current_rate = self.exchange.get_rate(trade.pair, refresh=False, side="buy")
+        current_rate = self.exchange.get_rate(
+            trade.pair, side='entry', is_short=trade.is_short, refresh=False)
 
         msg = {
             'trade_id': trade.id,
-            'type': RPCMessageType.BUY_CANCEL,
-            'buy_tag': trade.buy_tag,
+            'type': RPCMessageType.ENTRY_CANCEL,
+            'buy_tag': trade.enter_tag,
+            'enter_tag': trade.enter_tag,
             'exchange': self.exchange.name.capitalize(),
             'pair': trade.pair,
+            'leverage': trade.leverage,
+            'direction': 'Short' if trade.is_short else 'Long',
             'limit': trade.open_rate,
             'order_type': order_type,
             'stake_amount': trade.stake_amount,
@@ -643,29 +886,13 @@ class FreqtradeBot(LoggingMixin):
         # Send the message
         self.rpc.send_msg(msg)
 
-    def _notify_enter_fill(self, trade: Trade) -> None:
-        msg = {
-            'trade_id': trade.id,
-            'type': RPCMessageType.BUY_FILL,
-            'buy_tag': trade.buy_tag,
-            'exchange': self.exchange.name.capitalize(),
-            'pair': trade.pair,
-            'open_rate': trade.open_rate,
-            'stake_amount': trade.stake_amount,
-            'stake_currency': self.config['stake_currency'],
-            'fiat_currency': self.config.get('fiat_display_currency', None),
-            'amount': trade.amount,
-            'open_date': trade.open_date,
-        }
-        self.rpc.send_msg(msg)
-
 #
 # SELL / exit positions / close trades logic and methods
 #
 
     def exit_positions(self, trades: List[Any]) -> int:
         """
-        Tries to execute sell orders for open trades (positions)
+        Tries to execute exit orders for open trades (positions)
         """
         trades_closed = 0
         for trade in trades:
@@ -681,7 +908,7 @@ class FreqtradeBot(LoggingMixin):
                     trades_closed += 1
 
             except DependencyException as exception:
-                logger.warning('Unable to sell trade %s: %s', trade.pair, exception)
+                logger.warning(f'Unable to exit trade {trade.pair}: {exception}')
 
         # Updating wallets if any trade occurred
         if trades_closed:
@@ -691,33 +918,37 @@ class FreqtradeBot(LoggingMixin):
 
     def handle_trade(self, trade: Trade) -> bool:
         """
-        Sells the current pair if the threshold is reached and updates the trade record.
-        :return: True if trade has been sold, False otherwise
+        Sells/exits_short the current pair if the threshold is reached and updates the trade record.
+        :return: True if trade has been sold/exited_short, False otherwise
         """
         if not trade.is_open:
             raise DependencyException(f'Attempt to handle closed trade: {trade}')
 
         logger.debug('Handling %s ...', trade)
 
-        (buy, sell) = (False, False)
+        (enter, exit_) = (False, False)
+        exit_tag = None
+        exit_signal_type = "exit_short" if trade.is_short else "exit_long"
 
-        if (self.config.get('use_sell_signal', True) or
-                self.config.get('ignore_roi_if_buy_signal', False)):
+        if (self.config.get('use_exit_signal', True) or
+                self.config.get('ignore_roi_if_entry_signal', False)):
             analyzed_df, _ = self.dataprovider.get_analyzed_dataframe(trade.pair,
                                                                       self.strategy.timeframe)
 
-            (buy, sell, _) = self.strategy.get_signal(
+            (enter, exit_, exit_tag) = self.strategy.get_exit_signal(
                 trade.pair,
                 self.strategy.timeframe,
-                analyzed_df
+                analyzed_df,
+                is_short=trade.is_short
             )
 
-        logger.debug('checking sell')
-        exit_rate = self.exchange.get_rate(trade.pair, refresh=True, side="sell")
-        if self._check_and_execute_exit(trade, exit_rate, buy, sell):
+        logger.debug('checking exit')
+        exit_rate = self.exchange.get_rate(
+            trade.pair, side='exit', is_short=trade.is_short, refresh=True)
+        if self._check_and_execute_exit(trade, exit_rate, enter, exit_, exit_tag):
             return True
 
-        logger.debug('Found no sell signal for %s.', trade)
+        logger.debug(f'Found no {exit_signal_type} signal for %s.', trade)
         return False
 
     def create_stoploss_order(self, trade: Trade, stop_price: float) -> bool:
@@ -728,9 +959,14 @@ class FreqtradeBot(LoggingMixin):
         :return: True if the order succeeded, and False in case of problems.
         """
         try:
-            stoploss_order = self.exchange.stoploss(pair=trade.pair, amount=trade.amount,
-                                                    stop_price=stop_price,
-                                                    order_types=self.strategy.order_types)
+            stoploss_order = self.exchange.stoploss(
+                pair=trade.pair,
+                amount=trade.amount,
+                stop_price=stop_price,
+                order_types=self.strategy.order_types,
+                side=trade.exit_side,
+                leverage=trade.leverage
+            )
 
             order_obj = Order.parse_from_ccxt_object(stoploss_order, trade.pair, 'stoploss')
             trade.orders.append(order_obj)
@@ -745,8 +981,8 @@ class FreqtradeBot(LoggingMixin):
             trade.stoploss_order_id = None
             logger.error(f'Unable to place a stoploss order on exchange. {e}')
             logger.warning('Exiting the trade forcefully')
-            self.execute_trade_exit(trade, trade.stop_loss, sell_reason=SellCheckTuple(
-                sell_type=SellType.EMERGENCY_SELL))
+            self.execute_trade_exit(trade, trade.stop_loss, exit_check=ExitCheckTuple(
+                exit_type=ExitType.EMERGENCY_EXIT))
 
         except ExchangeError:
             trade.stoploss_order_id = None
@@ -758,6 +994,8 @@ class FreqtradeBot(LoggingMixin):
         Check if trade is fulfilled in which case the stoploss
         on exchange should be added immediately if stoploss on exchange
         is enabled.
+        # TODO: liquidation price always on exchange, even without stoploss_on_exchange
+        # Therefore fetching account liquidations for open pairs may make sense.
         """
 
         logger.debug('Handling stoploss on exchange %s ...', trade)
@@ -776,7 +1014,7 @@ class FreqtradeBot(LoggingMixin):
 
         # We check if stoploss order is fulfilled
         if stoploss_order and stoploss_order['status'] in ('closed', 'triggered'):
-            trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
+            trade.exit_reason = ExitType.STOPLOSS_ON_EXCHANGE.value
             self.update_trade_state(trade, trade.stoploss_order_id, stoploss_order,
                                     stoploss_order=True)
             # Lock pair for one candle to prevent immediate rebuys
@@ -791,17 +1029,28 @@ class FreqtradeBot(LoggingMixin):
             # The trade can be closed already (sell-order fill confirmation came in this iteration)
             return False
 
-        # If buy order is fulfilled but there is no stoploss, we add a stoploss on exchange
+        # If enter order is fulfilled but there is no stoploss, we add a stoploss on exchange
         if not stoploss_order:
-            stoploss = self.edge.stoploss(pair=trade.pair) if self.edge else self.strategy.stoploss
-            stop_price = trade.open_rate * (1 + stoploss)
+            stoploss = (
+                self.edge.stoploss(pair=trade.pair)
+                if self.edge else
+                self.strategy.stoploss / trade.leverage
+            )
+            if trade.is_short:
+                stop_price = trade.open_rate * (1 - stoploss)
+            else:
+                stop_price = trade.open_rate * (1 + stoploss)
 
             if self.create_stoploss_order(trade=trade, stop_price=stop_price):
+                # The above will return False if the placement failed and the trade was force-sold.
+                # in which case the trade will be closed - which we must check below.
                 trade.stoploss_last_update = datetime.utcnow()
                 return False
 
         # If stoploss order is canceled for some reason we add it
-        if stoploss_order and stoploss_order['status'] in ('canceled', 'cancelled'):
+        if (trade.is_open
+                and stoploss_order
+                and stoploss_order['status'] in ('canceled', 'cancelled')):
             if self.create_stoploss_order(trade=trade, stop_price=trade.stop_loss):
                 return False
             else:
@@ -811,7 +1060,7 @@ class FreqtradeBot(LoggingMixin):
         # Finally we check if stoploss on exchange should be moved up because of trailing.
         # Triggered Orders are now real orders - so don't replace stoploss anymore
         if (
-            stoploss_order
+            trade.is_open and stoploss_order
             and stoploss_order.get('status_stop') != 'triggered'
             and (self.config.get('trailing_stop', False)
                  or self.config.get('use_custom_stoploss', False))
@@ -823,7 +1072,7 @@ class FreqtradeBot(LoggingMixin):
 
         return False
 
-    def handle_trailing_stoploss_on_exchange(self, trade: Trade, order: dict) -> None:
+    def handle_trailing_stoploss_on_exchange(self, trade: Trade, order: Dict) -> None:
         """
         Check to see if stoploss on exchange should be updated
         in case of trailing stoploss on exchange
@@ -831,7 +1080,9 @@ class FreqtradeBot(LoggingMixin):
         :param order: Current on exchange stoploss order
         :return: None
         """
-        if self.exchange.stoploss_adjust(trade.stop_loss, order):
+        stoploss_norm = self.exchange.price_to_precision(trade.pair, trade.stop_loss)
+
+        if self.exchange.stoploss_adjust(stoploss_norm, order, side=trade.exit_side):
             # we check if the update is necessary
             update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60)
             if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() >= update_beat:
@@ -852,35 +1103,26 @@ class FreqtradeBot(LoggingMixin):
                                    f"for pair {trade.pair}.")
 
     def _check_and_execute_exit(self, trade: Trade, exit_rate: float,
-                                buy: bool, sell: bool) -> bool:
+                                enter: bool, exit_: bool, exit_tag: Optional[str]) -> bool:
         """
-        Check and execute exit
+        Check and execute trade exit
         """
-        should_sell = self.strategy.should_sell(
-            trade, exit_rate, datetime.now(timezone.utc), buy, sell,
+        should_exit: ExitCheckTuple = self.strategy.should_exit(
+            trade,
+            exit_rate,
+            datetime.now(timezone.utc),
+            enter=enter,
+            exit_=exit_,
             force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0
         )
 
-        if should_sell.sell_flag:
-            logger.info(f'Executing Sell for {trade.pair}. Reason: {should_sell.sell_type}')
-            self.execute_trade_exit(trade, exit_rate, should_sell)
+        if should_exit.exit_flag:
+            logger.info(f'Exit for {trade.pair} detected. Reason: {should_exit.exit_type}'
+                        f'Tag: {exit_tag if exit_tag is not None else "None"}')
+            self.execute_trade_exit(trade, exit_rate, should_exit, exit_tag=exit_tag)
             return True
         return False
 
-    def _check_timed_out(self, side: str, order: dict) -> bool:
-        """
-        Check if timeout is active, and if the order is still open and timed out
-        """
-        timeout = self.config.get('unfilledtimeout', {}).get(side)
-        ordertime = arrow.get(order['datetime']).datetime
-        if timeout is not None:
-            timeout_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
-            timeout_kwargs = {timeout_unit: -timeout}
-            timeout_threshold = arrow.utcnow().shift(**timeout_kwargs).datetime
-            return (order['status'] == 'open' and order['side'] == side
-                    and ordertime < timeout_threshold)
-        return False
-
     def check_handle_timedout(self) -> None:
         """
         Check if any orders are timed out and cancel if necessary
@@ -898,24 +1140,33 @@ class FreqtradeBot(LoggingMixin):
                 continue
 
             fully_cancelled = self.update_trade_state(trade, trade.open_order_id, order)
+            is_entering = order['side'] == trade.entry_side
+            not_closed = order['status'] == 'open' or fully_cancelled
+            max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0)
 
-            if (order['side'] == 'buy' and (order['status'] == 'open' or fully_cancelled) and (
-                    fully_cancelled
-                    or self._check_timed_out('buy', order)
-                    or strategy_safe_wrapper(self.strategy.check_buy_timeout,
-                                             default_retval=False)(pair=trade.pair,
-                                                                   trade=trade,
-                                                                   order=order))):
-                self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['TIMEOUT'])
+            order_obj = trade.select_order_by_order_id(trade.open_order_id)
 
-            elif (order['side'] == 'sell' and (order['status'] == 'open' or fully_cancelled) and (
-                  fully_cancelled
-                  or self._check_timed_out('sell', order)
-                  or strategy_safe_wrapper(self.strategy.check_sell_timeout,
-                                           default_retval=False)(pair=trade.pair,
-                                                                 trade=trade,
-                                                                 order=order))):
-                self.handle_cancel_exit(trade, order, constants.CANCEL_REASON['TIMEOUT'])
+            if not_closed and (fully_cancelled or (order_obj and self.strategy.ft_check_timed_out(
+                trade, order_obj, datetime.now(timezone.utc)))
+            ):
+                if is_entering:
+                    self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['TIMEOUT'])
+                else:
+                    canceled = self.handle_cancel_exit(
+                        trade, order, constants.CANCEL_REASON['TIMEOUT'])
+                    canceled_count = trade.get_exit_order_count()
+                    max_timeouts = self.config.get(
+                        'unfilledtimeout', {}).get('exit_timeout_count', 0)
+                    if canceled and max_timeouts > 0 and canceled_count >= max_timeouts:
+                        logger.warning(f'Emergency exiting trade {trade}, as the exit order '
+                                       f'timed out {max_timeouts} times.')
+                        try:
+                            self.execute_trade_exit(
+                                trade, order.get('price'),
+                                exit_check=ExitCheckTuple(exit_type=ExitType.EMERGENCY_EXIT))
+                        except DependencyException as exception:
+                            logger.warning(
+                                f'Unable to emergency sell trade {trade.pair}: {exception}')
 
     def cancel_all_open_orders(self) -> None:
         """
@@ -930,10 +1181,10 @@ class FreqtradeBot(LoggingMixin):
                 logger.info('Cannot query order for %s due to %s', trade, traceback.format_exc())
                 continue
 
-            if order['side'] == 'buy':
+            if order['side'] == trade.entry_side:
                 self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['ALL_CANCELLED'])
 
-            elif order['side'] == 'sell':
+            elif order['side'] == trade.exit_side:
                 self.handle_cancel_exit(trade, order, constants.CANCEL_REASON['ALL_CANCELLED'])
         Trade.commit()
 
@@ -946,15 +1197,15 @@ class FreqtradeBot(LoggingMixin):
 
         # Cancelled orders may have the status of 'canceled' or 'closed'
         if order['status'] not in constants.NON_OPEN_EXCHANGE_STATES:
-            filled_val = order.get('filled', 0.0) or 0.0
+            filled_val: float = order.get('filled', 0.0) or 0.0
             filled_stake = filled_val * trade.open_rate
             minstake = self.exchange.get_min_pair_stake_amount(
                 trade.pair, trade.open_rate, self.strategy.stoploss)
 
-            if filled_val > 0 and filled_stake < minstake:
+            if filled_val > 0 and minstake and filled_stake < minstake:
                 logger.warning(
                     f"Order {trade.open_order_id} for {trade.pair} not cancelled, "
-                    f"as the filled amount of {filled_val} would result in an unsellable trade.")
+                    f"as the filled amount of {filled_val} would result in an unexitable trade.")
                 return False
             corder = self.exchange.cancel_order_with_result(trade.open_order_id, trade.pair,
                                                             trade.amount)
@@ -969,16 +1220,23 @@ class FreqtradeBot(LoggingMixin):
             corder = order
             reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE']
 
-        logger.info('Buy order %s for %s.', reason, trade)
+        side = trade.entry_side.capitalize()
+        logger.info('%s order %s for %s.', side, reason, trade)
 
         # Using filled to determine the filled amount
         filled_amount = safe_value_fallback2(corder, order, 'filled', 'filled')
         if isclose(filled_amount, 0.0, abs_tol=constants.MATH_CLOSE_PREC):
-            logger.info('Buy order fully cancelled. Removing %s from database.', trade)
-            # if trade is not partially completed, just delete the trade
-            trade.delete()
-            was_trade_fully_canceled = True
-            reason += f", {constants.CANCEL_REASON['FULLY_CANCELLED']}"
+            logger.info(f'{side} order fully cancelled. Removing {trade} from database.')
+            # if trade is not partially completed and it's the only order, just delete the trade
+            if len(trade.orders) <= 1:
+                trade.delete()
+                was_trade_fully_canceled = True
+                reason += f", {constants.CANCEL_REASON['FULLY_CANCELLED']}"
+            else:
+                # FIXME TODO: This could possibly reworked to not duplicate the code 15 lines below.
+                self.update_trade_state(trade, trade.open_order_id, corder)
+                trade.open_order_id = None
+                logger.info(f'Partial {side} order timeout for {trade}.')
         else:
             # if trade is partially complete, edit the stake details for the trade
             # and close the order
@@ -986,23 +1244,27 @@ class FreqtradeBot(LoggingMixin):
             # to the order dict acquired before cancelling.
             # we need to fall back to the values from order if corder does not contain these keys.
             trade.amount = filled_amount
-            trade.stake_amount = trade.amount * trade.open_rate
+            # * Check edge cases, we don't want to make leverage > 1.0 if we don't have to
+            # * (for leverage modes which aren't isolated futures)
+
+            trade.stake_amount = trade.amount * trade.open_rate / trade.leverage
             self.update_trade_state(trade, trade.open_order_id, corder)
 
             trade.open_order_id = None
-            logger.info('Partial buy order timeout for %s.', trade)
+            logger.info(f'Partial {trade.entry_side} order timeout for {trade}.')
             reason += f", {constants.CANCEL_REASON['PARTIALLY_FILLED']}"
 
         self.wallets.update()
-        self._notify_enter_cancel(trade, order_type=self.strategy.order_types['buy'],
+        self._notify_enter_cancel(trade, order_type=self.strategy.order_types['entry'],
                                   reason=reason)
         return was_trade_fully_canceled
 
-    def handle_cancel_exit(self, trade: Trade, order: Dict, reason: str) -> str:
+    def handle_cancel_exit(self, trade: Trade, order: Dict, reason: str) -> bool:
         """
-        Sell cancel - cancel order and update trade
-        :return: Reason for cancel
+        exit order cancel - cancel order and update trade
+        :return: True if exit order was cancelled, false otherwise
         """
+        cancelled = False
         # if trade is not partially completed, just cancel the order
         if order['remaining'] == order['amount'] or order.get('filled') == 0.0:
             if not self.exchange.check_order_canceled_empty(order):
@@ -1012,12 +1274,13 @@ class FreqtradeBot(LoggingMixin):
                                                                 trade.amount)
                     trade.update_order(co)
                 except InvalidOrderException:
-                    logger.exception(f"Could not cancel sell order {trade.open_order_id}")
-                    return 'error cancelling order'
-                logger.info('Sell order %s for %s.', reason, trade)
+                    logger.exception(
+                        f"Could not cancel {trade.exit_side} order {trade.open_order_id}")
+                    return False
+                logger.info('%s order %s for %s.', trade.exit_side.capitalize(), reason, trade)
             else:
                 reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE']
-                logger.info('Sell order %s for %s.', reason, trade)
+                logger.info('%s order %s for %s.', trade.exit_side.capitalize(), reason, trade)
                 trade.update_order(order)
 
             trade.close_rate = None
@@ -1027,17 +1290,20 @@ class FreqtradeBot(LoggingMixin):
             trade.close_date = None
             trade.is_open = True
             trade.open_order_id = None
+            trade.exit_reason = None
+            cancelled = True
         else:
             # TODO: figure out how to handle partially complete sell orders
             reason = constants.CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
+            cancelled = False
 
         self.wallets.update()
         self._notify_exit_cancel(
             trade,
-            order_type=self.strategy.order_types['sell'],
+            order_type=self.strategy.order_types['exit'],
             reason=reason
         )
-        return reason
+        return cancelled
 
     def _safe_exit_amount(self, pair: str, amount: float) -> float:
         """
@@ -1052,34 +1318,52 @@ class FreqtradeBot(LoggingMixin):
         """
         # Update wallets to ensure amounts tied up in a stoploss is now free!
         self.wallets.update()
+        if self.trading_mode == TradingMode.FUTURES:
+            return amount
+
         trade_base_currency = self.exchange.get_pair_base_currency(pair)
         wallet_amount = self.wallets.get_free(trade_base_currency)
         logger.debug(f"{pair} - Wallet: {wallet_amount} - Trade-amount: {amount}")
         if wallet_amount >= amount:
+            # A safe exit amount isn't needed for futures, you can just exit/close the position
             return amount
         elif wallet_amount > amount * 0.98:
             logger.info(f"{pair} - Falling back to wallet-amount {wallet_amount} -> {amount}.")
             return wallet_amount
         else:
             raise DependencyException(
-                f"Not enough amount to sell. Trade-amount: {amount}, Wallet: {wallet_amount}")
+                f"Not enough amount to exit trade. Trade-amount: {amount}, Wallet: {wallet_amount}")
 
-    def execute_trade_exit(self, trade: Trade, limit: float, sell_reason: SellCheckTuple) -> bool:
+    def execute_trade_exit(
+            self,
+            trade: Trade,
+            limit: float,
+            exit_check: ExitCheckTuple,
+            *,
+            exit_tag: Optional[str] = None,
+            ordertype: Optional[str] = None,
+    ) -> bool:
         """
         Executes a trade exit for the given trade and limit
         :param trade: Trade instance
         :param limit: limit rate for the sell order
-        :param sell_reason: Reason the sell was triggered
+        :param exit_check: CheckTuple with signal and reason
         :return: True if it succeeds (supported) False (not supported)
         """
-        sell_type = 'sell'
-        if sell_reason.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
-            sell_type = 'stoploss'
+        trade.funding_fees = self.exchange.get_funding_fees(
+            pair=trade.pair,
+            amount=trade.amount,
+            is_short=trade.is_short,
+            open_date=trade.open_date_utc,
+        )
+        exit_type = 'exit'
+        if exit_check.exit_type in (ExitType.STOP_LOSS, ExitType.TRAILING_STOP_LOSS):
+            exit_type = 'stoploss'
 
         # if stoploss is on exchange and we are on dry_run mode,
         # we consider the sell price stop price
-        if self.config['dry_run'] and sell_type == 'stoploss' \
-           and self.strategy.order_types['stoploss_on_exchange']:
+        if (self.config['dry_run'] and exit_type == 'stoploss'
+           and self.strategy.order_types['stoploss_on_exchange']):
             limit = trade.stop_loss
 
         # set custom_exit_price if available
@@ -1094,63 +1378,59 @@ class FreqtradeBot(LoggingMixin):
         limit = self.get_valid_price(custom_exit_price, proposed_limit_rate)
 
         # First cancelling stoploss on exchange ...
-        if self.strategy.order_types.get('stoploss_on_exchange') and trade.stoploss_order_id:
-            try:
-                co = self.exchange.cancel_stoploss_order_with_result(trade.stoploss_order_id,
-                                                                     trade.pair, trade.amount)
-                trade.update_order(co)
-            except InvalidOrderException:
-                logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}")
+        trade = self.cancel_stoploss_on_exchange(trade)
 
-        order_type = self.strategy.order_types[sell_type]
-        if sell_reason.sell_type == SellType.EMERGENCY_SELL:
+        order_type = ordertype or self.strategy.order_types[exit_type]
+        if exit_check.exit_type == ExitType.EMERGENCY_EXIT:
             # Emergency sells (default to market!)
-            order_type = self.strategy.order_types.get("emergencysell", "market")
-        if sell_reason.sell_type == SellType.FORCE_SELL:
-            # Force sells (default to the sell_type defined in the strategy,
-            # but we allow this value to be changed)
-            order_type = self.strategy.order_types.get("forcesell", order_type)
+            order_type = self.strategy.order_types.get("emergency_exit", "market")
 
         amount = self._safe_exit_amount(trade.pair, trade.amount)
-        time_in_force = self.strategy.order_time_in_force['sell']
+        time_in_force = self.strategy.order_time_in_force['exit']
 
         if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
                 pair=trade.pair, trade=trade, order_type=order_type, amount=amount, rate=limit,
-                time_in_force=time_in_force, sell_reason=sell_reason.sell_reason,
+                time_in_force=time_in_force, exit_reason=exit_check.exit_reason,
+                sell_reason=exit_check.exit_reason,  # sellreason -> compatibility
                 current_time=datetime.now(timezone.utc)):
-            logger.info(f"User requested abortion of selling {trade.pair}")
+            logger.info(f"User requested abortion of exiting {trade.pair}")
             return False
 
         try:
             # Execute sell and update trade record
-            order = self.exchange.create_order(pair=trade.pair,
-                                               ordertype=order_type, side="sell",
-                                               amount=amount, rate=limit,
-                                               time_in_force=time_in_force
-                                               )
+            order = self.exchange.create_order(
+                pair=trade.pair,
+                ordertype=order_type,
+                side=trade.exit_side,
+                amount=amount,
+                rate=limit,
+                leverage=trade.leverage,
+                reduceOnly=self.trading_mode == TradingMode.FUTURES,
+                time_in_force=time_in_force
+            )
         except InsufficientFundsError as e:
             logger.warning(f"Unable to place order {e}.")
             # Try to figure out what went wrong
             self.handle_insufficient_funds(trade)
             return False
 
-        order_obj = Order.parse_from_ccxt_object(order, trade.pair, 'sell')
+        order_obj = Order.parse_from_ccxt_object(order, trade.pair, trade.exit_side)
         trade.orders.append(order_obj)
 
         trade.open_order_id = order['id']
-        trade.sell_order_status = ''
+        trade.exit_order_status = ''
         trade.close_rate_requested = limit
-        trade.sell_reason = sell_reason.sell_reason
-        # In case of market sell orders the order can be closed immediately
-        if order.get('status', 'unknown') in ('closed', 'expired'):
-            self.update_trade_state(trade, trade.open_order_id, order)
-        Trade.commit()
+        trade.exit_reason = exit_tag or exit_check.exit_reason
 
-        # Lock pair for one candle to prevent immediate re-buys
+        # Lock pair for one candle to prevent immediate re-trading
         self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
                                 reason='Auto lock')
 
         self._notify_exit(trade, order_type)
+        # In case of market sell orders the order can be closed immediately
+        if order.get('status', 'unknown') in ('closed', 'expired'):
+            self.update_trade_state(trade, trade.open_order_id, order)
+        Trade.commit()
 
         return True
 
@@ -1162,16 +1442,18 @@ class FreqtradeBot(LoggingMixin):
         profit_trade = trade.calc_profit(rate=profit_rate)
         # Use cached rates here - it was updated seconds ago.
         current_rate = self.exchange.get_rate(
-            trade.pair, refresh=False, side="sell") if not fill else None
+            trade.pair, side='exit', is_short=trade.is_short, refresh=False) if not fill else None
         profit_ratio = trade.calc_profit_ratio(profit_rate)
         gain = "profit" if profit_ratio > 0 else "loss"
 
         msg = {
-            'type': (RPCMessageType.SELL_FILL if fill
-                     else RPCMessageType.SELL),
+            'type': (RPCMessageType.EXIT_FILL if fill
+                     else RPCMessageType.EXIT),
             'trade_id': trade.id,
             'exchange': trade.exchange.capitalize(),
             'pair': trade.pair,
+            'leverage': trade.leverage,
+            'direction': 'Short' if trade.is_short else 'Long',
             'gain': gain,
             'limit': profit_rate,
             'order_type': order_type,
@@ -1181,7 +1463,10 @@ class FreqtradeBot(LoggingMixin):
             'current_rate': current_rate,
             'profit_amount': profit_trade,
             'profit_ratio': profit_ratio,
-            'sell_reason': trade.sell_reason,
+            'buy_tag': trade.enter_tag,
+            'enter_tag': trade.enter_tag,
+            'sell_reason': trade.exit_reason,  # Deprecated
+            'exit_reason': trade.exit_reason,
             'open_date': trade.open_date,
             'close_date': trade.close_date or datetime.utcnow(),
             'stake_currency': self.config['stake_currency'],
@@ -1200,22 +1485,25 @@ class FreqtradeBot(LoggingMixin):
         """
         Sends rpc notification when a sell cancel occurred.
         """
-        if trade.sell_order_status == reason:
+        if trade.exit_order_status == reason:
             return
         else:
-            trade.sell_order_status = reason
+            trade.exit_order_status = reason
 
         profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
         profit_trade = trade.calc_profit(rate=profit_rate)
-        current_rate = self.exchange.get_rate(trade.pair, refresh=False, side="sell")
+        current_rate = self.exchange.get_rate(
+            trade.pair, side='exit', is_short=trade.is_short, refresh=False)
         profit_ratio = trade.calc_profit_ratio(profit_rate)
         gain = "profit" if profit_ratio > 0 else "loss"
 
         msg = {
-            'type': RPCMessageType.SELL_CANCEL,
+            'type': RPCMessageType.EXIT_CANCEL,
             'trade_id': trade.id,
             'exchange': trade.exchange.capitalize(),
             'pair': trade.pair,
+            'leverage': trade.leverage,
+            'direction': 'Short' if trade.is_short else 'Long',
             'gain': gain,
             'limit': profit_rate or 0,
             'order_type': order_type,
@@ -1224,7 +1512,10 @@ class FreqtradeBot(LoggingMixin):
             'current_rate': current_rate,
             'profit_amount': profit_trade,
             'profit_ratio': profit_ratio,
-            'sell_reason': trade.sell_reason,
+            'buy_tag': trade.enter_tag,
+            'enter_tag': trade.enter_tag,
+            'sell_reason': trade.exit_reason,  # Deprecated
+            'exit_reason': trade.exit_reason,
             'open_date': trade.open_date,
             'close_date': trade.close_date or datetime.now(timezone.utc),
             'stake_currency': self.config['stake_currency'],
@@ -1245,13 +1536,14 @@ class FreqtradeBot(LoggingMixin):
 #
 
     def update_trade_state(self, trade: Trade, order_id: str, action_order: Dict[str, Any] = None,
-                           stoploss_order: bool = False) -> bool:
+                           stoploss_order: bool = False, send_msg: bool = True) -> bool:
         """
         Checks trades with open orders and updates the amount if necessary
         Handles closing both buy and sell orders.
         :param trade: Trade object of the trade we're analyzing
         :param order_id: Order-id of the order we're analyzing
         :param action_order: Already acquired order object
+        :param send_msg: Send notification - should always be True except in "recovery" methods
         :return: True if order has been cancelled without being filled partially, False otherwise
         """
         if not order_id:
@@ -1259,7 +1551,7 @@ class FreqtradeBot(LoggingMixin):
             return False
 
         # Update trade with order values
-        logger.info('Found open order for %s', trade)
+        logger.info(f'Found open order for {trade}')
         try:
             order = action_order or self.exchange.fetch_order_or_stoploss_order(order_id,
                                                                                 trade.pair,
@@ -1270,33 +1562,52 @@ class FreqtradeBot(LoggingMixin):
 
         trade.update_order(order)
 
-        # Try update amount (binance-fix)
-        try:
-            new_amount = self.get_real_amount(trade, order)
-            if not isclose(safe_value_fallback(order, 'filled', 'amount'), new_amount,
-                           abs_tol=constants.MATH_CLOSE_PREC):
-                order['amount'] = new_amount
-                order.pop('filled', None)
-                trade.recalc_open_trade_value()
-        except DependencyException as exception:
-            logger.warning("Could not update trade amount: %s", exception)
-
         if self.exchange.check_order_canceled_empty(order):
             # Trade has been cancelled on exchange
-            # Handling of this will happen in check_handle_timeout.
+            # Handling of this will happen in check_handle_timedout.
             return True
-        trade.update(order)
+
+        order_obj = trade.select_order_by_order_id(order_id)
+        if not order_obj:
+            raise DependencyException(
+                f"Order_obj not found for {order_id}. This should not have happened.")
+
+        self.handle_order_fee(trade, order_obj, order)
+
+        trade.update_trade(order_obj)
+        # TODO: is the below necessary? it's already done in update_trade for filled buys
+        trade.recalc_trade_from_orders()
         Trade.commit()
 
-        # Updating wallets when order is closed
+        if order['status'] in constants.NON_OPEN_EXCHANGE_STATES:
+            # If a entry order was closed, force update on stoploss on exchange
+            if order.get('side', None) == trade.entry_side:
+                trade = self.cancel_stoploss_on_exchange(trade)
+                # TODO: Margin will need to use interest_rate as well.
+                # interest_rate = self.exchange.get_interest_rate()
+                trade.set_isolated_liq(self.exchange.get_liquidation_price(
+
+                    leverage=trade.leverage,
+                    pair=trade.pair,
+                    amount=trade.amount,
+                    open_rate=trade.open_rate,
+                    is_short=trade.is_short
+                ))
+                if not self.edge:
+                    # TODO: should shorting/leverage be supported by Edge,
+                    # then this will need to be fixed.
+                    trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
+
+            # Updating wallets when order is closed
+            self.wallets.update()
+
         if not trade.is_open:
-            if not stoploss_order and not trade.open_order_id:
+            if send_msg and not stoploss_order and not trade.open_order_id:
                 self._notify_exit(trade, '', True)
             self.handle_protections(trade.pair)
-            self.wallets.update()
-        elif not trade.open_order_id:
-            # Buy fill
-            self._notify_enter_fill(trade)
+        elif send_msg and not trade.open_order_id:
+            # Enter fill
+            self._notify_enter(trade, order, fill=True)
 
         return False
 
@@ -1318,6 +1629,8 @@ class FreqtradeBot(LoggingMixin):
         """
         Applies the fee to amount (either from Order or from Trades).
         Can eat into dust if more than the required asset is available.
+        Can't happen in Futures mode - where Fees are always in settlement currency,
+        never in base currency.
         """
         self.wallets.update()
         if fee_abs != 0 and self.wallets.get_free(trade_base_currency) >= amount:
@@ -1331,7 +1644,17 @@ class FreqtradeBot(LoggingMixin):
             return real_amount
         return amount
 
-    def get_real_amount(self, trade: Trade, order: Dict) -> float:
+    def handle_order_fee(self, trade: Trade, order_obj: Order, order: Dict[str, Any]) -> None:
+        # Try update amount (binance-fix)
+        try:
+            new_amount = self.get_real_amount(trade, order, order_obj)
+            if not isclose(safe_value_fallback(order, 'filled', 'amount'), new_amount,
+                           abs_tol=constants.MATH_CLOSE_PREC):
+                order_obj.ft_fee_base = trade.amount - new_amount
+        except DependencyException as exception:
+            logger.warning("Could not update trade amount: %s", exception)
+
+    def get_real_amount(self, trade: Trade, order: Dict, order_obj: Order) -> float:
         """
         Detect and update trade fee.
         Calls trade.update_fee() upon correct detection.
@@ -1349,7 +1672,7 @@ class FreqtradeBot(LoggingMixin):
         # use fee from order-dict if possible
         if self.exchange.order_has_fee(order):
             fee_cost, fee_currency, fee_rate = self.exchange.extract_cost_curr_rate(order)
-            logger.info(f"Fee for Trade {trade} [{order.get('side')}]: "
+            logger.info(f"Fee for Trade {trade} [{order_obj.ft_order_side}]: "
                         f"{fee_cost:.8g} {fee_currency} - rate: {fee_rate}")
             if fee_rate is None or fee_rate < 0.02:
                 # Reject all fees that report as > 2%.
@@ -1361,14 +1684,18 @@ class FreqtradeBot(LoggingMixin):
                     return self.apply_fee_conditional(trade, trade_base_currency,
                                                       amount=order_amount, fee_abs=fee_cost)
                 return order_amount
-        return self.fee_detection_from_trades(trade, order, order_amount)
+        return self.fee_detection_from_trades(
+            trade, order, order_obj, order_amount, order.get('trades', []))
 
-    def fee_detection_from_trades(self, trade: Trade, order: Dict, order_amount: float) -> float:
+    def fee_detection_from_trades(self, trade: Trade, order: Dict, order_obj: Order,
+                                  order_amount: float, trades: List) -> float:
         """
-        fee-detection fallback to Trades. Parses result of fetch_my_trades to get correct fee.
+        fee-detection fallback to Trades.
+        Either uses provided trades list or the result of fetch_my_trades to get correct fee.
         """
-        trades = self.exchange.get_trades_for_order(self.exchange.get_order_id_conditional(order),
-                                                    trade.pair, trade.open_date)
+        if not trades:
+            trades = self.exchange.get_trades_for_order(
+                self.exchange.get_order_id_conditional(order), trade.pair, order_obj.order_date)
 
         if len(trades) == 0:
             logger.info("Applying fee on amount for %s failed: myTrade-Dict empty found", trade)
@@ -1398,6 +1725,7 @@ class FreqtradeBot(LoggingMixin):
                 trade.update_fee(fee_cost, fee_currency, fee_rate, order.get('side', ''))
 
         if not isclose(amount, order_amount, abs_tol=constants.MATH_CLOSE_PREC):
+            # * Leverage could be a cause for this warning
             logger.warning(f"Amount {amount} does not match amount {trade.amount}")
             raise DependencyException("Half bought? Amounts don't match")
 
diff --git a/freqtrade/leverage/__init__.py b/freqtrade/leverage/__init__.py
new file mode 100644
index 000000000..ae78f4722
--- /dev/null
+++ b/freqtrade/leverage/__init__.py
@@ -0,0 +1,2 @@
+# flake8: noqa: F401
+from freqtrade.leverage.interest import interest
diff --git a/freqtrade/leverage/interest.py b/freqtrade/leverage/interest.py
new file mode 100644
index 000000000..367df5821
--- /dev/null
+++ b/freqtrade/leverage/interest.py
@@ -0,0 +1,43 @@
+from decimal import Decimal
+from math import ceil
+
+from freqtrade.exceptions import OperationalException
+
+
+one = Decimal(1.0)
+four = Decimal(4.0)
+twenty_four = Decimal(24.0)
+
+
+def interest(
+    exchange_name: str,
+    borrowed: Decimal,
+    rate: Decimal,
+    hours: Decimal
+) -> Decimal:
+    """
+    Equation to calculate interest on margin trades
+
+    :param exchange_name: The exchanged being trading on
+    :param borrowed: The amount of currency being borrowed
+    :param rate: The rate of interest (i.e daily interest rate)
+    :param hours: The time in hours that the currency has been borrowed for
+
+    Raises:
+        OperationalException: Raised if freqtrade does
+        not support margin trading for this exchange
+
+    Returns: The amount of interest owed (currency matches borrowed)
+    """
+    exchange_name = exchange_name.lower()
+    if exchange_name == "binance":
+        return borrowed * rate * ceil(hours) / twenty_four
+    elif exchange_name == "kraken":
+        # Rounded based on https://kraken-fees-calculator.github.io/
+        return borrowed * rate * (one + ceil(hours / four))
+    elif exchange_name == "ftx":
+        # As Explained under #Interest rates section in
+        # https://help.ftx.com/hc/en-us/articles/360053007671-Spot-Margin-Trading-Explainer
+        return borrowed * rate * ceil(hours) / twenty_four
+    else:
+        raise OperationalException(f"Leverage not available on {exchange_name} with freqtrade")
diff --git a/freqtrade/loggers.py b/freqtrade/loggers.py
index 5c5831695..e5b6ddbe9 100644
--- a/freqtrade/loggers.py
+++ b/freqtrade/loggers.py
@@ -7,11 +7,25 @@ from typing import Any, Dict
 from freqtrade.exceptions import OperationalException
 
 
+class FTBufferingHandler(BufferingHandler):
+    def flush(self):
+        """
+        Override Flush behaviour - we keep half of the configured capacity
+        otherwise, we have moments with "empty" logs.
+        """
+        self.acquire()
+        try:
+            # Keep half of the records in buffer.
+            self.buffer = self.buffer[-int(self.capacity / 2):]
+        finally:
+            self.release()
+
+
 logger = logging.getLogger(__name__)
 LOGFORMAT = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
 
 # Initialize bufferhandler - will be used for /log endpoints
-bufferHandler = BufferingHandler(1000)
+bufferHandler = FTBufferingHandler(1000)
 bufferHandler.setFormatter(Formatter(LOGFORMAT))
 
 
diff --git a/freqtrade/main.py b/freqtrade/main.py
index 6593fbcb6..162b4d029 100755
--- a/freqtrade/main.py
+++ b/freqtrade/main.py
@@ -9,8 +9,8 @@ from typing import Any, List
 
 
 # check min. python version
-if sys.version_info < (3, 7):  # pragma: no cover
-    sys.exit("Freqtrade requires Python version >= 3.7")
+if sys.version_info < (3, 8):  # pragma: no cover
+    sys.exit("Freqtrade requires Python version >= 3.8")
 
 from freqtrade.commands import Arguments
 from freqtrade.exceptions import FreqtradeException, OperationalException
diff --git a/freqtrade/misc.py b/freqtrade/misc.py
index 6f439866b..d5572ea0b 100644
--- a/freqtrade/misc.py
+++ b/freqtrade/misc.py
@@ -2,11 +2,13 @@
 Various tool function for Freqtrade and scripts
 """
 import gzip
+import hashlib
 import logging
 import re
+from copy import deepcopy
 from datetime import datetime
 from pathlib import Path
-from typing import Any, Iterator, List
+from typing import Any, Iterator, List, Union
 from typing.io import IO
 from urllib.parse import urlparse
 
@@ -27,18 +29,23 @@ def decimals_per_coin(coin: str):
     return DECIMALS_PER_COIN.get(coin, DECIMAL_PER_COIN_FALLBACK)
 
 
-def round_coin_value(value: float, coin: str, show_coin_name=True) -> str:
+def round_coin_value(
+        value: float, coin: str, show_coin_name=True, keep_trailing_zeros=False) -> str:
     """
     Get price value for this coin
     :param value: Value to be printed
     :param coin: Which coin are we printing the price / value for
     :param show_coin_name: Return string in format: "222.22 USDT" or "222.22"
+    :param keep_trailing_zeros: Keep trailing zeros "222.200" vs. "222.2"
     :return: Formatted / rounded value (with or without coin name)
     """
+    val = f"{value:.{decimals_per_coin(coin)}f}"
+    if not keep_trailing_zeros:
+        val = val.rstrip('0').rstrip('.')
     if show_coin_name:
-        return f"{value:.{decimals_per_coin(coin)}f} {coin}"
-    else:
-        return f"{value:.{decimals_per_coin(coin)}f}"
+        val = f"{val} {coin}"
+
+    return val
 
 
 def shorten_date(_date: str) -> str:
@@ -109,7 +116,7 @@ def file_load_json(file):
 
 
 def pair_to_filename(pair: str) -> str:
-    for ch in ['/', '-', ' ', '.', '@', '$', '+', ':']:
+    for ch in ['/', ' ', '.', '@', '$', '+', ':']:
         pair = pair.replace(ch, '_')
     return pair
 
@@ -119,10 +126,10 @@ def format_ms_time(date: int) -> str:
     convert MS date to readable format.
     : epoch-string in ms
     """
-    return datetime.fromtimestamp(date/1000.0).strftime('%Y-%m-%dT%H:%M:%S')
+    return datetime.fromtimestamp(date / 1000.0).strftime('%Y-%m-%dT%H:%M:%S')
 
 
-def deep_merge_dicts(source, destination):
+def deep_merge_dicts(source, destination, allow_null_overrides: bool = True):
     """
     Values from Source override destination, destination is returned (and modified!!)
     Sample:
@@ -135,8 +142,8 @@ def deep_merge_dicts(source, destination):
         if isinstance(value, dict):
             # get node or create one
             node = destination.setdefault(key, {})
-            deep_merge_dicts(value, node)
-        else:
+            deep_merge_dicts(value, node, allow_null_overrides)
+        elif value is not None or allow_null_overrides:
             destination[key] = value
 
     return destination
@@ -228,3 +235,34 @@ def parse_db_uri_for_logging(uri: str):
         return uri
     pwd = parsed_db_uri.netloc.split(':')[1].split('@')[0]
     return parsed_db_uri.geturl().replace(f':{pwd}@', ':*****@')
+
+
+def get_strategy_run_id(strategy) -> str:
+    """
+    Generate unique identification hash for a backtest run. Identical config and strategy file will
+    always return an identical hash.
+    :param strategy: strategy object.
+    :return: hex string id.
+    """
+    digest = hashlib.sha1()
+    config = deepcopy(strategy.config)
+
+    # Options that have no impact on results of individual backtest.
+    not_important_keys = ('strategy_list', 'original_config', 'telegram', 'api_server')
+    for k in not_important_keys:
+        if k in config:
+            del config[k]
+
+    # Explicitly allow NaN values (e.g. max_open_trades).
+    # as it does not matter for getting the hash.
+    digest.update(rapidjson.dumps(config, default=str,
+                                  number_mode=rapidjson.NM_NAN).encode('utf-8'))
+    with open(strategy.__file__, 'rb') as fp:
+        digest.update(fp.read())
+    return digest.hexdigest().lower()
+
+
+def get_backtest_metadata_filename(filename: Union[Path, str]) -> Path:
+    """Return metadata filename for specified backtest results file."""
+    filename = Path(filename)
+    return filename.parent / Path(f'{filename.stem}.meta{filename.suffix}')
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 1a8c0903c..11704a70b 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -9,26 +9,29 @@ from copy import deepcopy
 from datetime import datetime, timedelta, timezone
 from typing import Any, Dict, List, Optional, Tuple
 
+from numpy import nan
 from pandas import DataFrame
 
+from freqtrade import constants
 from freqtrade.configuration import TimeRange, validate_config_consistency
-from freqtrade.constants import DATETIME_PRINT_FORMAT
+from freqtrade.constants import DATETIME_PRINT_FORMAT, LongShort
 from freqtrade.data import history
-from freqtrade.data.btanalysis import trade_list_to_dataframe
+from freqtrade.data.btanalysis import find_existing_backtest_stats, trade_list_to_dataframe
 from freqtrade.data.converter import trim_dataframe, trim_dataframes
 from freqtrade.data.dataprovider import DataProvider
-from freqtrade.enums import BacktestState, SellType
+from freqtrade.enums import BacktestState, CandleType, ExitCheckTuple, ExitType, TradingMode
 from freqtrade.exceptions import DependencyException, OperationalException
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
+from freqtrade.misc import get_strategy_run_id
 from freqtrade.mixins import LoggingMixin
 from freqtrade.optimize.bt_progress import BTProgress
 from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results,
                                                  store_backtest_stats)
-from freqtrade.persistence import LocalTrade, PairLocks, Trade
+from freqtrade.persistence import LocalTrade, Order, PairLocks, Trade
 from freqtrade.plugins.pairlistmanager import PairListManager
 from freqtrade.plugins.protectionmanager import ProtectionManager
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
-from freqtrade.strategy.interface import IStrategy, SellCheckTuple
+from freqtrade.strategy.interface import IStrategy
 from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
 from freqtrade.wallets import Wallets
 
@@ -37,13 +40,16 @@ logger = logging.getLogger(__name__)
 
 # Indexes for backtest tuples
 DATE_IDX = 0
-BUY_IDX = 1
-OPEN_IDX = 2
-CLOSE_IDX = 3
-SELL_IDX = 4
-LOW_IDX = 5
-HIGH_IDX = 6
-BUY_TAG_IDX = 7
+OPEN_IDX = 1
+HIGH_IDX = 2
+LOW_IDX = 3
+CLOSE_IDX = 4
+LONG_IDX = 5
+ELONG_IDX = 6  # Exit long
+SHORT_IDX = 7
+ESHORT_IDX = 8  # Exit short
+ENTER_TAG_IDX = 9
+EXIT_TAG_IDX = 10
 
 
 class Backtesting:
@@ -59,15 +65,19 @@ class Backtesting:
 
         LoggingMixin.show_output = False
         self.config = config
-        self.results: Optional[Dict[str, Any]] = None
+        self.results: Dict[str, Any] = {}
+        self.trade_id_counter: int = 0
+        self.order_id_counter: int = 0
 
         config['dry_run'] = True
+        self.run_ids: Dict[str, str] = {}
         self.strategylist: List[IStrategy] = []
         self.all_results: Dict[str, Dict] = {}
         self.processed_dfs: Dict[str, Dict] = {}
         
-        self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
-        self.dataprovider = DataProvider(self.config, None)
+        self._exchange_name = self.config['exchange']['name']
+        self.exchange = ExchangeResolver.load_exchange(self._exchange_name, self.config)
+        self.dataprovider = DataProvider(self.config, self.exchange)
 
         if self.config.get('strategy_list', None):
             for strat in list(self.config['strategy_list']):
@@ -82,25 +92,15 @@ class Backtesting:
             validate_config_consistency(self.config)
 
         if "timeframe" not in self.config:
-            raise OperationalException("Timeframe (ticker interval) needs to be set in either "
+            raise OperationalException("Timeframe needs to be set in either "
                                        "configuration or as cli argument `--timeframe 5m`")
         self.timeframe = str(self.config.get('timeframe'))
         self.timeframe_min = timeframe_to_minutes(self.timeframe)
-        # Load detail timeframe if specified
-        self.timeframe_detail = str(self.config.get('timeframe_detail', ''))
-        if self.timeframe_detail:
-            self.timeframe_detail_min = timeframe_to_minutes(self.timeframe_detail)
-            if self.timeframe_min <= self.timeframe_detail_min:
-                raise OperationalException(
-                    "Detail timeframe must be smaller than strategy timeframe.")
-
-        else:
-            self.timeframe_detail_min = 0
-        self.detail_data: Dict[str, DataFrame] = {}
-
+        self.init_backtest_detail()
         self.pairlists = PairListManager(self.exchange, self.config)
         if 'VolumePairList' in self.pairlists.name_list:
-            raise OperationalException("VolumePairList not allowed for backtesting.")
+            raise OperationalException("VolumePairList not allowed for backtesting. "
+                                       "Please use StaticPairlist instead.")
         if 'PerformanceFilter' in self.pairlists.name_list:
             raise OperationalException("PerformanceFilter not allowed for backtesting.")
 
@@ -120,14 +120,6 @@ class Backtesting:
         else:
             self.fee = self.exchange.get_fee(symbol=self.pairlists.whitelist[0])
 
-        Trade.use_db = False
-        Trade.reset_trades()
-        PairLocks.timeframe = self.config['timeframe']
-        PairLocks.use_db = False
-        PairLocks.reset_locks()
-
-        self.wallets = Wallets(self.config, self.exchange, log=False)
-
         self.timerange = TimeRange.parse_timerange(
             None if self.config.get('timerange') is None else str(self.config.get('timerange')))
 
@@ -141,17 +133,44 @@ class Backtesting:
         if self.config.get('enable_backtest_signal_candle_export', None) is not None:
             self.enable_backtest_signal_candle_export = bool(self.config.get('enable_backtest_signal_candle_export'))
 
-        self.progress = BTProgress()
-        self.abort = False
+        self.trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT)
+        # strategies which define "can_short=True" will fail to load in Spot mode.
+        self._can_short = self.trading_mode != TradingMode.SPOT
+
+        self.init_backtest()
 
     def __del__(self):
         self.cleanup()
 
-    def cleanup(self):
+    @staticmethod
+    def cleanup():
         LoggingMixin.show_output = True
         PairLocks.use_db = True
         Trade.use_db = True
 
+    def init_backtest_detail(self):
+        # Load detail timeframe if specified
+        self.timeframe_detail = str(self.config.get('timeframe_detail', ''))
+        if self.timeframe_detail:
+            self.timeframe_detail_min = timeframe_to_minutes(self.timeframe_detail)
+            if self.timeframe_min <= self.timeframe_detail_min:
+                raise OperationalException(
+                    "Detail timeframe must be smaller than strategy timeframe.")
+
+        else:
+            self.timeframe_detail_min = 0
+        self.detail_data: Dict[str, DataFrame] = {}
+        self.futures_data: Dict[str, DataFrame] = {}
+
+    def init_backtest(self):
+
+        self.prepare_backtest(False)
+
+        self.wallets = Wallets(self.config, self.exchange, log=False)
+
+        self.progress = BTProgress()
+        self.abort = False
+
     def _set_strategy(self, strategy: IStrategy):
         """
         Load strategy into backtesting
@@ -188,6 +207,7 @@ class Backtesting:
             startup_candles=self.required_startup,
             fail_without_data=True,
             data_format=self.config.get('dataformat_ohlcv', 'json'),
+            candle_type=self.config.get('candle_type_def', CandleType.SPOT)
         )
 
         min_date, max_date = history.get_timerange(data)
@@ -216,9 +236,41 @@ class Backtesting:
                 startup_candles=0,
                 fail_without_data=True,
                 data_format=self.config.get('dataformat_ohlcv', 'json'),
+                candle_type=self.config.get('candle_type_def', CandleType.SPOT)
             )
         else:
             self.detail_data = {}
+        if self.trading_mode == TradingMode.FUTURES:
+            # Load additional futures data.
+            funding_rates_dict = history.load_data(
+                datadir=self.config['datadir'],
+                pairs=self.pairlists.whitelist,
+                timeframe=self.exchange._ft_has['mark_ohlcv_timeframe'],
+                timerange=self.timerange,
+                startup_candles=0,
+                fail_without_data=True,
+                data_format=self.config.get('dataformat_ohlcv', 'json'),
+                candle_type=CandleType.FUNDING_RATE
+            )
+
+            # For simplicity, assign to CandleType.Mark (might contian index candles!)
+            mark_rates_dict = history.load_data(
+                datadir=self.config['datadir'],
+                pairs=self.pairlists.whitelist,
+                timeframe=self.exchange._ft_has['mark_ohlcv_timeframe'],
+                timerange=self.timerange,
+                startup_candles=0,
+                fail_without_data=True,
+                data_format=self.config.get('dataformat_ohlcv', 'json'),
+                candle_type=CandleType.from_string(self.exchange._ft_has["mark_ohlcv_price"])
+            )
+            # Combine data to avoid combining the data per trade.
+            for pair in self.pairlists.whitelist:
+                self.futures_data[pair] = funding_rates_dict[pair].merge(
+                    mark_rates_dict[pair], on='date', how="inner", suffixes=["_fund", "_mark"])
+
+        else:
+            self.futures_data = {}
 
     def prepare_backtest(self, enable_protections):
         """
@@ -230,8 +282,11 @@ class Backtesting:
         PairLocks.reset_locks()
         Trade.reset_trades()
         self.rejected_trades = 0
+        self.timedout_entry_orders = 0
+        self.timedout_exit_orders = 0
         self.dataprovider.clear_cache()
-        self._load_protections(self.strategy)
+        if enable_protections:
+            self._load_protections(self.strategy)
 
     def check_abort(self):
         """
@@ -247,154 +302,332 @@ class Backtesting:
         Helper function to convert a processed dataframes into lists for performance reasons.
 
         Used by backtest() - so keep this optimized for performance.
+
+        :param processed: a processed dictionary with format {pair, data}, which gets cleared to
+        optimize memory usage!
         """
         # Every change to this headers list must evaluate further usages of the resulting tuple
         # and eventually change the constants for indexes at the top
-        headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high', 'buy_tag']
+        headers = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
+                   'enter_short', 'exit_short', 'enter_tag', 'exit_tag']
         data: Dict = {}
         self.progress.init_step(BacktestState.CONVERT, len(processed))
 
         # Create dict with data
-        for pair, pair_data in processed.items():
+        for pair in processed.keys():
+            pair_data = processed[pair]
             self.check_abort()
             self.progress.increment()
-            if not pair_data.empty:
-                pair_data.loc[:, 'buy'] = 0  # cleanup if buy_signal is exist
-                pair_data.loc[:, 'sell'] = 0  # cleanup if sell_signal is exist
-                pair_data.loc[:, 'buy_tag'] = None  # cleanup if buy_tag is exist
 
-            df_analyzed = self.strategy.advise_sell(
-                self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair}).copy()
+            if not pair_data.empty:
+                # Cleanup from prior runs
+                pair_data.drop(headers[5:] + ['buy', 'sell'], axis=1, errors='ignore')
+
+            df_analyzed = self.strategy.advise_exit(
+                self.strategy.advise_entry(pair_data, {'pair': pair}),
+                {'pair': pair}
+            ).copy()
             # Trim startup period from analyzed dataframe
-            df_analyzed = trim_dataframe(df_analyzed, self.timerange,
-                                         startup_candles=self.required_startup)
+            df_analyzed = processed[pair] = pair_data = trim_dataframe(
+                df_analyzed, self.timerange, startup_candles=self.required_startup)
+            # Update dataprovider cache
+            self.dataprovider._set_cached_df(
+                pair, self.timeframe, df_analyzed, self.config['candle_type_def'])
+
+            # Create a copy of the dataframe before shifting, that way the buy signal/tag
+            # remains on the correct candle for callbacks.
+            df_analyzed = df_analyzed.copy()
+
             # To avoid using data from future, we use buy/sell signals shifted
             # from the previous candle
-            df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
-            df_analyzed.loc[:, 'sell'] = df_analyzed.loc[:, 'sell'].shift(1)
-            df_analyzed.loc[:, 'buy_tag'] = df_analyzed.loc[:, 'buy_tag'].shift(1)
-
-            # Update dataprovider cache
-            self.dataprovider._set_cached_df(pair, self.timeframe, df_analyzed)
+            for col in headers[5:]:
+                tag_col = col in ('enter_tag', 'exit_tag')
+                if col in df_analyzed.columns:
+                    df_analyzed.loc[:, col] = df_analyzed.loc[:, col].replace(
+                        [nan], [0 if not tag_col else None]).shift(1)
+                elif not df_analyzed.empty:
+                    df_analyzed.loc[:, col] = 0 if not tag_col else None
 
             df_analyzed = df_analyzed.drop(df_analyzed.head(1).index)
 
             # Convert from Pandas to list for performance reasons
             # (Looping Pandas is slow.)
-            data[pair] = df_analyzed[headers].values.tolist()
+            data[pair] = df_analyzed[headers].values.tolist() if not df_analyzed.empty else []
         return data
 
-    def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade, sell: SellCheckTuple,
+    def _get_close_rate(self, row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,
                         trade_dur: int) -> float:
         """
         Get close rate for backtesting result
         """
         # Special handling if high or low hit STOP_LOSS or ROI
-        if sell.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
-            if trade.stop_loss > sell_row[HIGH_IDX]:
-                # our stoploss was already higher than candle high,
-                # possibly due to a cancelled trade exit.
-                # sell at open price.
-                return sell_row[OPEN_IDX]
-
-            # Special case: trailing triggers within same candle as trade opened. Assume most
-            # pessimistic price movement, which is moving just enough to arm stoploss and
-            # immediately going down to stop price.
-            if sell.sell_type == SellType.TRAILING_STOP_LOSS and trade_dur == 0:
-                if (
-                    not self.strategy.use_custom_stoploss and self.strategy.trailing_stop
-                    and self.strategy.trailing_only_offset_is_reached
-                    and self.strategy.trailing_stop_positive_offset is not None
-                    and self.strategy.trailing_stop_positive
-                ):
-                    # Worst case: price reaches stop_positive_offset and dives down.
-                    stop_rate = (sell_row[OPEN_IDX] *
-                                 (1 + abs(self.strategy.trailing_stop_positive_offset) -
-                                  abs(self.strategy.trailing_stop_positive)))
-                else:
-                    # Worst case: price ticks tiny bit above open and dives down.
-                    stop_rate = sell_row[OPEN_IDX] * (1 - abs(trade.stop_loss_pct))
-                    assert stop_rate < sell_row[HIGH_IDX]
-                return stop_rate
-
-            # Set close_rate to stoploss
-            return trade.stop_loss
-        elif sell.sell_type == (SellType.ROI):
-            roi_entry, roi = self.strategy.min_roi_reached_entry(trade_dur)
-            if roi is not None and roi_entry is not None:
-                if roi == -1 and roi_entry % self.timeframe_min == 0:
-                    # When forceselling with ROI=-1, the roi time will always be equal to trade_dur.
-                    # If that entry is a multiple of the timeframe (so on candle open)
-                    # - we'll use open instead of close
-                    return sell_row[OPEN_IDX]
-
-                # - (Expected abs profit + open_rate + open_fee) / (fee_close -1)
-                close_rate = - (trade.open_rate * roi + trade.open_rate *
-                                (1 + trade.fee_open)) / (trade.fee_close - 1)
-
-                if (trade_dur > 0 and trade_dur == roi_entry
-                        and roi_entry % self.timeframe_min == 0
-                        and sell_row[OPEN_IDX] > close_rate):
-                    # new ROI entry came into effect.
-                    # use Open rate if open_rate > calculated sell rate
-                    return sell_row[OPEN_IDX]
-
-                # Use the maximum between close_rate and low as we
-                # cannot sell outside of a candle.
-                # Applies when a new ROI setting comes in place and the whole candle is above that.
-                return min(max(close_rate, sell_row[LOW_IDX]), sell_row[HIGH_IDX])
-
-            else:
-                # This should not be reached...
-                return sell_row[OPEN_IDX]
+        if sell.exit_type in (ExitType.STOP_LOSS, ExitType.TRAILING_STOP_LOSS):
+            return self._get_close_rate_for_stoploss(row, trade, sell, trade_dur)
+        elif sell.exit_type == (ExitType.ROI):
+            return self._get_close_rate_for_roi(row, trade, sell, trade_dur)
         else:
-            return sell_row[OPEN_IDX]
+            return row[OPEN_IDX]
+
+    def _get_close_rate_for_stoploss(self, row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,
+                                     trade_dur: int) -> float:
+        # our stoploss was already lower than candle high,
+        # possibly due to a cancelled trade exit.
+        # sell at open price.
+        is_short = trade.is_short or False
+        leverage = trade.leverage or 1.0
+        side_1 = -1 if is_short else 1
+        if is_short:
+            if trade.stop_loss < row[LOW_IDX]:
+                return row[OPEN_IDX]
+        else:
+            if trade.stop_loss > row[HIGH_IDX]:
+                return row[OPEN_IDX]
+
+        # Special case: trailing triggers within same candle as trade opened. Assume most
+        # pessimistic price movement, which is moving just enough to arm stoploss and
+        # immediately going down to stop price.
+        if sell.exit_type == ExitType.TRAILING_STOP_LOSS and trade_dur == 0:
+            if (
+                not self.strategy.use_custom_stoploss and self.strategy.trailing_stop
+                and self.strategy.trailing_only_offset_is_reached
+                and self.strategy.trailing_stop_positive_offset is not None
+                and self.strategy.trailing_stop_positive
+            ):
+                # Worst case: price reaches stop_positive_offset and dives down.
+                stop_rate = (row[OPEN_IDX] *
+                             (1 + side_1 * abs(self.strategy.trailing_stop_positive_offset) -
+                              side_1 * abs(self.strategy.trailing_stop_positive / leverage)))
+            else:
+                # Worst case: price ticks tiny bit above open and dives down.
+                stop_rate = row[OPEN_IDX] * (1 - side_1 * abs(trade.stop_loss_pct / leverage))
+                if is_short:
+                    assert stop_rate > row[LOW_IDX]
+                else:
+                    assert stop_rate < row[HIGH_IDX]
+
+            # Limit lower-end to candle low to avoid sells below the low.
+            # This still remains "worst case" - but "worst realistic case".
+            if is_short:
+                return min(row[HIGH_IDX], stop_rate)
+            else:
+                return max(row[LOW_IDX], stop_rate)
+
+        # Set close_rate to stoploss
+        return trade.stop_loss
+
+    def _get_close_rate_for_roi(self, row: Tuple, trade: LocalTrade, sell: ExitCheckTuple,
+                                trade_dur: int) -> float:
+        is_short = trade.is_short or False
+        leverage = trade.leverage or 1.0
+        side_1 = -1 if is_short else 1
+        roi_entry, roi = self.strategy.min_roi_reached_entry(trade_dur)
+        if roi is not None and roi_entry is not None:
+            if roi == -1 and roi_entry % self.timeframe_min == 0:
+                # When force_exiting with ROI=-1, the roi time will always be equal to trade_dur.
+                # If that entry is a multiple of the timeframe (so on candle open)
+                # - we'll use open instead of close
+                return row[OPEN_IDX]
+
+            # - (Expected abs profit - open_rate - open_fee) / (fee_close -1)
+            roi_rate = trade.open_rate * roi / leverage
+            open_fee_rate = side_1 * trade.open_rate * (1 + side_1 * trade.fee_open)
+            close_rate = -(roi_rate + open_fee_rate) / (trade.fee_close - side_1 * 1)
+            if is_short:
+                is_new_roi = row[OPEN_IDX] < close_rate
+            else:
+                is_new_roi = row[OPEN_IDX] > close_rate
+            if (trade_dur > 0 and trade_dur == roi_entry
+                    and roi_entry % self.timeframe_min == 0
+                    and is_new_roi):
+                # new ROI entry came into effect.
+                # use Open rate if open_rate > calculated sell rate
+                return row[OPEN_IDX]
+
+            if (trade_dur == 0 and (
+                (
+                    is_short
+                    # Red candle (for longs)
+                    and row[OPEN_IDX] < row[CLOSE_IDX]  # Red candle
+                    and trade.open_rate > row[OPEN_IDX]  # trade-open above open_rate
+                    and close_rate < row[CLOSE_IDX]  # closes below close
+                )
+                or
+                (
+                    not is_short
+                    # green candle (for shorts)
+                    and row[OPEN_IDX] > row[CLOSE_IDX]  # green candle
+                    and trade.open_rate < row[OPEN_IDX]  # trade-open below open_rate
+                    and close_rate > row[CLOSE_IDX]  # closes above close
+                )
+            )):
+                # ROI on opening candles with custom pricing can only
+                # trigger if the entry was at Open or lower wick.
+                # details: https: // github.com/freqtrade/freqtrade/issues/6261
+                # If open_rate is < open, only allow sells below the close on red candles.
+                raise ValueError("Opening candle ROI on red candles.")
+
+            # Use the maximum between close_rate and low as we
+            # cannot sell outside of a candle.
+            # Applies when a new ROI setting comes in place and the whole candle is above that.
+            return min(max(close_rate, row[LOW_IDX]), row[HIGH_IDX])
+
+        else:
+            # This should not be reached...
+            return row[OPEN_IDX]
+
+    def _get_adjust_trade_entry_for_candle(self, trade: LocalTrade, row: Tuple
+                                           ) -> LocalTrade:
+        current_profit = trade.calc_profit_ratio(row[OPEN_IDX])
+        min_stake = self.exchange.get_min_pair_stake_amount(trade.pair, row[OPEN_IDX], -0.1)
+        max_stake = self.exchange.get_max_pair_stake_amount(trade.pair, row[OPEN_IDX])
+        stake_available = self.wallets.get_available_stake_amount()
+        stake_amount = strategy_safe_wrapper(self.strategy.adjust_trade_position,
+                                             default_retval=None)(
+            trade=trade, current_time=row[DATE_IDX].to_pydatetime(), current_rate=row[OPEN_IDX],
+            current_profit=current_profit, min_stake=min_stake,
+            max_stake=min(max_stake, stake_available))
+
+        # Check if we should increase our position
+        if stake_amount is not None and stake_amount > 0.0:
+
+            pos_trade = self._enter_trade(
+                trade.pair, row, 'short' if trade.is_short else 'long', stake_amount, trade)
+            if pos_trade is not None:
+                self.wallets.update()
+                return pos_trade
+
+        return trade
+
+    def _get_order_filled(self, rate: float, row: Tuple) -> bool:
+        """ Rate is within candle, therefore filled"""
+        return row[LOW_IDX] <= rate <= row[HIGH_IDX]
 
     def _get_sell_trade_entry_for_candle(self, trade: LocalTrade,
-                                         sell_row: Tuple) -> Optional[LocalTrade]:
-        sell_candle_time = sell_row[DATE_IDX].to_pydatetime()
-        sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX],  # type: ignore
-                                         sell_candle_time, sell_row[BUY_IDX],
-                                         sell_row[SELL_IDX],
-                                         low=sell_row[LOW_IDX], high=sell_row[HIGH_IDX])
+                                         row: Tuple) -> Optional[LocalTrade]:
 
-        if sell.sell_flag:
+        # Check if we need to adjust our current positions
+        if self.strategy.position_adjustment_enable:
+            check_adjust_entry = True
+            if self.strategy.max_entry_position_adjustment > -1:
+                entry_count = trade.nr_of_successful_entries
+                check_adjust_entry = (entry_count <= self.strategy.max_entry_position_adjustment)
+            if check_adjust_entry:
+                trade = self._get_adjust_trade_entry_for_candle(trade, row)
+
+        sell_candle_time: datetime = row[DATE_IDX].to_pydatetime()
+        enter = row[SHORT_IDX] if trade.is_short else row[LONG_IDX]
+        exit_ = row[ESHORT_IDX] if trade.is_short else row[ELONG_IDX]
+        sell = self.strategy.should_exit(
+            trade, row[OPEN_IDX], sell_candle_time,  # type: ignore
+            enter=enter, exit_=exit_,
+            low=row[LOW_IDX], high=row[HIGH_IDX]
+        )
+
+        if sell.exit_flag:
             trade.close_date = sell_candle_time
-            trade.sell_reason = sell.sell_reason
-            trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60)
-            closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
 
+            trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60)
+            try:
+                closerate = self._get_close_rate(row, trade, sell, trade_dur)
+            except ValueError:
+                return None
+            # call the custom exit price,with default value as previous closerate
+            current_profit = trade.calc_profit_ratio(closerate)
+            order_type = self.strategy.order_types['exit']
+            if sell.exit_type in (ExitType.EXIT_SIGNAL, ExitType.CUSTOM_EXIT):
+                # Custom exit pricing only for sell-signals
+                if order_type == 'limit':
+                    closerate = strategy_safe_wrapper(self.strategy.custom_exit_price,
+                                                      default_retval=closerate)(
+                        pair=trade.pair, trade=trade,
+                        current_time=sell_candle_time,
+                        proposed_rate=closerate, current_profit=current_profit)
+                    # We can't place orders lower than current low.
+                    # freqtrade does not support this in live, and the order would fill immediately
+                    if trade.is_short:
+                        closerate = min(closerate, row[HIGH_IDX])
+                    else:
+                        closerate = max(closerate, row[LOW_IDX])
             # Confirm trade exit:
-            time_in_force = self.strategy.order_time_in_force['sell']
+            time_in_force = self.strategy.order_time_in_force['exit']
+
             if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
                     pair=trade.pair, trade=trade, order_type='limit', amount=trade.amount,
                     rate=closerate,
                     time_in_force=time_in_force,
-                    sell_reason=sell.sell_reason,
+                    sell_reason=sell.exit_reason,  # deprecated
+                    exit_reason=sell.exit_reason,
                     current_time=sell_candle_time):
                 return None
 
-            trade.close(closerate, show_msg=False)
+            trade.exit_reason = sell.exit_reason
+
+            # Checks and adds an exit tag, after checking that the length of the
+            # row has the length for an exit tag column
+            if(
+                len(row) > EXIT_TAG_IDX
+                and row[EXIT_TAG_IDX] is not None
+                and len(row[EXIT_TAG_IDX]) > 0
+            ):
+                trade.exit_reason = row[EXIT_TAG_IDX]
+
+            self.order_id_counter += 1
+            order = Order(
+                id=self.order_id_counter,
+                ft_trade_id=trade.id,
+                order_date=sell_candle_time,
+                order_update_date=sell_candle_time,
+                ft_is_open=True,
+                ft_pair=trade.pair,
+                order_id=str(self.order_id_counter),
+                symbol=trade.pair,
+                ft_order_side=trade.exit_side,
+                side=trade.exit_side,
+                order_type=order_type,
+                status="open",
+                price=closerate,
+                average=closerate,
+                amount=trade.amount,
+                filled=0,
+                remaining=trade.amount,
+                cost=trade.amount * closerate,
+            )
+            trade.orders.append(order)
             return trade
 
         return None
 
-    def _get_sell_trade_entry(self, trade: LocalTrade, sell_row: Tuple) -> Optional[LocalTrade]:
+    def _get_sell_trade_entry(self, trade: LocalTrade, row: Tuple) -> Optional[LocalTrade]:
+        sell_candle_time: datetime = row[DATE_IDX].to_pydatetime()
+
+        if self.trading_mode == TradingMode.FUTURES:
+            trade.funding_fees = self.exchange.calculate_funding_fees(
+                self.futures_data[trade.pair],
+                amount=trade.amount,
+                is_short=trade.is_short,
+                open_date=trade.open_date_utc,
+                close_date=sell_candle_time,
+            )
+
         if self.timeframe_detail and trade.pair in self.detail_data:
-            sell_candle_time = sell_row[DATE_IDX].to_pydatetime()
             sell_candle_end = sell_candle_time + timedelta(minutes=self.timeframe_min)
 
             detail_data = self.detail_data[trade.pair]
             detail_data = detail_data.loc[
                 (detail_data['date'] >= sell_candle_time) &
                 (detail_data['date'] < sell_candle_end)
-             ]
+            ].copy()
             if len(detail_data) == 0:
                 # Fall back to "regular" data if no detail data was found for this candle
-                return self._get_sell_trade_entry_for_candle(trade, sell_row)
-            detail_data['buy'] = sell_row[BUY_IDX]
-            detail_data['sell'] = sell_row[SELL_IDX]
-            headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high']
+                return self._get_sell_trade_entry_for_candle(trade, row)
+            detail_data.loc[:, 'enter_long'] = row[LONG_IDX]
+            detail_data.loc[:, 'exit_long'] = row[ELONG_IDX]
+            detail_data.loc[:, 'enter_short'] = row[SHORT_IDX]
+            detail_data.loc[:, 'exit_short'] = row[ESHORT_IDX]
+            detail_data.loc[:, 'enter_tag'] = row[ENTER_TAG_IDX]
+            detail_data.loc[:, 'exit_tag'] = row[EXIT_TAG_IDX]
+            headers = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
+                       'enter_short', 'exit_short', 'enter_tag', 'exit_tag']
             for det_row in detail_data[headers].values.tolist():
                 res = self._get_sell_trade_entry_for_candle(trade, det_row)
                 if res:
@@ -403,51 +636,174 @@ class Backtesting:
             return None
 
         else:
-            return self._get_sell_trade_entry_for_candle(trade, sell_row)
+            return self._get_sell_trade_entry_for_candle(trade, row)
 
-    def _enter_trade(self, pair: str, row: List) -> Optional[LocalTrade]:
-        try:
-            stake_amount = self.wallets.get_trade_stake_amount(pair, None)
-        except DependencyException:
-            return None
+    def get_valid_price_and_stake(
+        self, pair: str, row: Tuple, propose_rate: float, stake_amount: Optional[float],
+        direction: LongShort, current_time: datetime, entry_tag: Optional[str],
+        trade: Optional[LocalTrade], order_type: str
+    ) -> Tuple[float, float, float, float]:
 
-        min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, row[OPEN_IDX], -0.05) or 0
-        max_stake_amount = self.wallets.get_available_stake_amount()
+        if order_type == 'limit':
+            propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
+                                                 default_retval=propose_rate)(
+                pair=pair, current_time=current_time,
+                proposed_rate=propose_rate, entry_tag=entry_tag,
+                side=direction,
+            )  # default value is the open rate
+            # We can't place orders higher than current high (otherwise it'd be a stop limit buy)
+            # which freqtrade does not support in live.
+            if direction == "short":
+                propose_rate = max(propose_rate, row[LOW_IDX])
+            else:
+                propose_rate = min(propose_rate, row[HIGH_IDX])
 
-        stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
-                                             default_retval=stake_amount)(
-            pair=pair, current_time=row[DATE_IDX].to_pydatetime(), current_rate=row[OPEN_IDX],
-            proposed_stake=stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount)
-        stake_amount = self.wallets._validate_stake_amount(pair, stake_amount, min_stake_amount)
+        pos_adjust = trade is not None
+        leverage = trade.leverage if trade else 1.0
+        if not pos_adjust:
+            try:
+                stake_amount = self.wallets.get_trade_stake_amount(pair, None, update=False)
+            except DependencyException:
+                return 0, 0, 0, 0
+
+            max_leverage = self.exchange.get_max_leverage(pair, stake_amount)
+            leverage = strategy_safe_wrapper(self.strategy.leverage, default_retval=1.0)(
+                pair=pair,
+                current_time=current_time,
+                current_rate=row[OPEN_IDX],
+                proposed_leverage=1.0,
+                max_leverage=max_leverage,
+                side=direction,
+            ) if self._can_short else 1.0
+            # Cap leverage between 1.0 and max_leverage.
+            leverage = min(max(leverage, 1.0), max_leverage)
+
+        min_stake_amount = self.exchange.get_min_pair_stake_amount(
+            pair, propose_rate, -0.05, leverage=leverage) or 0
+        max_stake_amount = self.exchange.get_max_pair_stake_amount(
+            pair, propose_rate, leverage=leverage)
+        stake_available = self.wallets.get_available_stake_amount()
+
+        if not pos_adjust:
+            stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
+                                                 default_retval=stake_amount)(
+                pair=pair, current_time=current_time, current_rate=propose_rate,
+                proposed_stake=stake_amount, min_stake=min_stake_amount,
+                max_stake=min(stake_available, max_stake_amount),
+                entry_tag=entry_tag, side=direction)
+
+        stake_amount_val = self.wallets.validate_stake_amount(
+            pair=pair,
+            stake_amount=stake_amount,
+            min_stake_amount=min_stake_amount,
+            max_stake_amount=max_stake_amount,
+        )
+
+        return propose_rate, stake_amount_val, leverage, min_stake_amount
+
+    def _enter_trade(self, pair: str, row: Tuple, direction: LongShort,
+                     stake_amount: Optional[float] = None,
+                     trade: Optional[LocalTrade] = None) -> Optional[LocalTrade]:
+
+        current_time = row[DATE_IDX].to_pydatetime()
+        entry_tag = row[ENTER_TAG_IDX] if len(row) >= ENTER_TAG_IDX + 1 else None
+        # let's call the custom entry price, using the open price as default price
+        order_type = self.strategy.order_types['entry']
+        pos_adjust = trade is not None
+
+        propose_rate, stake_amount, leverage, min_stake_amount = self.get_valid_price_and_stake(
+            pair, row, row[OPEN_IDX], stake_amount, direction, current_time, entry_tag, trade,
+            order_type
+        )
 
         if not stake_amount:
-            return None
+            # In case of pos adjust, still return the original trade
+            # If not pos adjust, trade is None
+            return trade
+        time_in_force = self.strategy.order_time_in_force['entry']
 
-        order_type = self.strategy.order_types['buy']
-        time_in_force = self.strategy.order_time_in_force['sell']
-        # Confirm trade entry:
-        if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
-                pair=pair, order_type=order_type, amount=stake_amount, rate=row[OPEN_IDX],
-                time_in_force=time_in_force, current_time=row[DATE_IDX].to_pydatetime()):
-            return None
+        if not pos_adjust:
+            # Confirm trade entry:
+            if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
+                    pair=pair, order_type=order_type, amount=stake_amount, rate=propose_rate,
+                    time_in_force=time_in_force, current_time=current_time,
+                    entry_tag=entry_tag, side=direction):
+                return trade
 
         if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount):
-            # Enter trade
-            has_buy_tag = len(row) >= BUY_TAG_IDX + 1
-            trade = LocalTrade(
+            self.order_id_counter += 1
+            base_currency = self.exchange.get_pair_base_currency(pair)
+            amount = round((stake_amount / propose_rate) * leverage, 8)
+            is_short = (direction == 'short')
+            # Necessary for Margin trading. Disabled until support is enabled.
+            # interest_rate = self.exchange.get_interest_rate()
+
+            if trade is None:
+                # Enter trade
+                self.trade_id_counter += 1
+                trade = LocalTrade(
+                    id=self.trade_id_counter,
+                    open_order_id=self.order_id_counter,
+                    pair=pair,
+                    base_currency=base_currency,
+                    stake_currency=self.config['stake_currency'],
+                    open_rate=propose_rate,
+                    open_rate_requested=propose_rate,
+                    open_date=current_time,
+                    stake_amount=stake_amount,
+                    amount=amount,
+                    amount_requested=amount,
+                    fee_open=self.fee,
+                    fee_close=self.fee,
+                    is_open=True,
+                    enter_tag=entry_tag,
+                    exchange=self._exchange_name,
+                    is_short=is_short,
+                    trading_mode=self.trading_mode,
+                    leverage=leverage,
+                    # interest_rate=interest_rate,
+                    orders=[],
+                )
+
+            trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
+
+            trade.set_isolated_liq(self.exchange.get_liquidation_price(
                 pair=pair,
-                open_rate=row[OPEN_IDX],
-                open_date=row[DATE_IDX].to_pydatetime(),
-                stake_amount=stake_amount,
-                amount=round(stake_amount / row[OPEN_IDX], 8),
-                fee_open=self.fee,
-                fee_close=self.fee,
-                is_open=True,
-                buy_tag=row[BUY_TAG_IDX] if has_buy_tag else None,
-                exchange='backtesting',
+                open_rate=propose_rate,
+                amount=amount,
+                leverage=leverage,
+                is_short=is_short,
+            ))
+
+            order = Order(
+                id=self.order_id_counter,
+                ft_trade_id=trade.id,
+                ft_is_open=True,
+                ft_pair=trade.pair,
+                order_id=str(self.order_id_counter),
+                symbol=trade.pair,
+                ft_order_side=trade.entry_side,
+                side=trade.entry_side,
+                order_type=order_type,
+                status="open",
+                order_date=current_time,
+                order_filled_date=current_time,
+                order_update_date=current_time,
+                price=propose_rate,
+                average=propose_rate,
+                amount=amount,
+                filled=0,
+                remaining=amount,
+                cost=stake_amount + trade.fee_open,
             )
-            return trade
-        return None
+            if pos_adjust and self._get_order_filled(order.price, row):
+                order.close_bt_order(current_time)
+            else:
+                trade.open_order_id = str(self.order_id_counter)
+            trade.orders.append(order)
+            trade.recalc_trade_from_orders()
+
+        return trade
 
     def handle_left_open(self, open_trades: Dict[str, List[LocalTrade]],
                          data: Dict[str, List[Tuple]]) -> List[LocalTrade]:
@@ -458,10 +814,13 @@ class Backtesting:
         for pair in open_trades.keys():
             if len(open_trades[pair]) > 0:
                 for trade in open_trades[pair]:
+                    if trade.open_order_id and trade.nr_of_successful_entries == 0:
+                        # Ignore trade if buy-order did not fill yet
+                        continue
                     sell_row = data[pair][-1]
 
                     trade.close_date = sell_row[DATE_IDX].to_pydatetime()
-                    trade.sell_reason = SellType.FORCE_SELL.value
+                    trade.exit_reason = ExitType.FORCE_EXIT.value
                     trade.close(sell_row[OPEN_IDX], show_msg=False)
                     LocalTrade.close_bt_trade(trade)
                     # Deepcopy object to have wallets update correctly
@@ -478,6 +837,65 @@ class Backtesting:
         self.rejected_trades += 1
         return False
 
+    def check_for_trade_entry(self, row) -> Optional[LongShort]:
+        enter_long = row[LONG_IDX] == 1
+        exit_long = row[ELONG_IDX] == 1
+        enter_short = self._can_short and row[SHORT_IDX] == 1
+        exit_short = self._can_short and row[ESHORT_IDX] == 1
+
+        if enter_long == 1 and not any([exit_long, enter_short]):
+            # Long
+            return 'long'
+        if enter_short == 1 and not any([exit_short, enter_long]):
+            # Short
+            return 'short'
+        return None
+
+    def run_protections(self, enable_protections, pair: str, current_time: datetime):
+        if enable_protections:
+            self.protections.stop_per_pair(pair, current_time)
+            self.protections.global_stop(current_time)
+
+    def check_order_cancel(self, trade: LocalTrade, current_time) -> bool:
+        """
+        Check if an order has been canceled.
+        Returns True if the trade should be Deleted (initial order was canceled).
+        """
+        for order in [o for o in trade.orders if o.ft_is_open]:
+
+            timedout = self.strategy.ft_check_timed_out(trade, order, current_time)
+            if timedout:
+                if order.side == trade.entry_side:
+                    self.timedout_entry_orders += 1
+                    if trade.nr_of_successful_entries == 0:
+                        # Remove trade due to entry timeout expiration.
+                        return True
+                    else:
+                        # Close additional buy order
+                        del trade.orders[trade.orders.index(order)]
+                if order.side == trade.exit_side:
+                    self.timedout_exit_orders += 1
+                    # Close exit order and retry exiting on next signal.
+                    del trade.orders[trade.orders.index(order)]
+
+        return False
+
+    def validate_row(
+            self, data: Dict, pair: str, row_index: int, current_time: datetime) -> Optional[Tuple]:
+        try:
+            # Row is treated as "current incomplete candle".
+            # Buy / sell signals are shifted by 1 to compensate for this.
+            row = data[pair][row_index]
+        except IndexError:
+            # missing Data for one pair at the end.
+            # Warnings for this are shown during data loading
+            return None
+
+        # Waits until the time-counter reaches the start of the data for this pair.
+        if row[DATE_IDX] > current_time:
+            return None
+        return row
+
     def backtest(self, processed: Dict,
                  start_date: datetime, end_date: datetime,
                  max_open_trades: int = 0, position_stacking: bool = False,
@@ -489,7 +907,8 @@ class Backtesting:
         Of course try to not have ugly code. By some accessor are sometime slower than functions.
         Avoid extensive logging in this method and functions it calls.
 
-        :param processed: a processed dictionary with format {pair, data}
+        :param processed: a processed dictionary with format {pair, data}, which gets cleared to
+        optimize memory usage!
         :param start_date: backtesting timerange start datetime
         :param end_date: backtesting timerange end datetime
         :param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited
@@ -499,14 +918,15 @@ class Backtesting:
         """
         trades: List[LocalTrade] = []
         self.prepare_backtest(enable_protections)
-
+        # Ensure wallets are uptodate (important for --strategy-list)
+        self.wallets.update()
         # Use dict of lists with data for performance
         # (looping lists is a lot faster than pandas DataFrames)
         data: Dict = self._get_ohlcv_as_lists(processed)
 
         # Indexes per pair, so some pairs are allowed to have a missing start.
         indexes: Dict = defaultdict(int)
-        tmp = start_date + timedelta(minutes=self.timeframe_min)
+        current_time = start_date + timedelta(minutes=self.timeframe_min)
 
         open_trades: Dict[str, List[LocalTrade]] = defaultdict(list)
         open_trade_count = 0
@@ -515,68 +935,80 @@ class Backtesting:
             (end_date - start_date) / timedelta(minutes=self.timeframe_min)))
 
         # Loop timerange and get candle for each pair at that point in time
-        while tmp <= end_date:
+        while current_time <= end_date:
             open_trade_count_start = open_trade_count
             self.check_abort()
             for i, pair in enumerate(data):
                 row_index = indexes[pair]
-                try:
-                    # Row is treated as "current incomplete candle".
-                    # Buy / sell signals are shifted by 1 to compensate for this.
-                    row = data[pair][row_index]
-                except IndexError:
-                    # missing Data for one pair at the end.
-                    # Warnings for this are shown during data loading
-                    continue
-
-                # Waits until the time-counter reaches the start of the data for this pair.
-                if row[DATE_IDX] > tmp:
+                row = self.validate_row(data, pair, row_index, current_time)
+                if not row:
                     continue
 
                 row_index += 1
                 indexes[pair] = row_index
                 self.dataprovider._set_dataframe_max_index(row_index)
 
+                for t in list(open_trades[pair]):
+                    # 1. Cancel expired buy/sell orders.
+                    if self.check_order_cancel(t, current_time):
+                        # Close trade due to buy timeout expiration.
+                        open_trade_count -= 1
+                        open_trades[pair].remove(t)
+                        self.wallets.update()
+
+                # 2. Process buys.
                 # without positionstacking, we can only have one open trade per pair.
                 # max_open_trades must be respected
                 # don't open on the last row
+                trade_dir = self.check_for_trade_entry(row)
                 if (
                     (position_stacking or len(open_trades[pair]) == 0)
                     and self.trade_slot_available(max_open_trades, open_trade_count_start)
-                    and tmp != end_date
-                    and row[BUY_IDX] == 1
-                    and row[SELL_IDX] != 1
+                    and current_time != end_date
+                    and trade_dir is not None
                     and not PairLocks.is_pair_locked(pair, row[DATE_IDX])
                 ):
-                    trade = self._enter_trade(pair, row)
+                    trade = self._enter_trade(pair, row, trade_dir)
                     if trade:
                         # TODO: hacky workaround to avoid opening > max_open_trades
-                        # This emulates previous behaviour - not sure if this is correct
+                        # This emulates previous behavior - not sure if this is correct
                         # Prevents buying if the trade-slot was freed in this candle
                         open_trade_count_start += 1
                         open_trade_count += 1
                         # logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
                         open_trades[pair].append(trade)
-                        LocalTrade.add_bt_trade(trade)
 
                 for trade in list(open_trades[pair]):
-                    # also check the buying candle for sell conditions.
-                    trade_entry = self._get_sell_trade_entry(trade, row)
-                    # Sell occurred
-                    if trade_entry:
+                    # 3. Process entry orders.
+                    order = trade.select_order(trade.entry_side, is_open=True)
+                    if order and self._get_order_filled(order.price, row):
+                        order.close_bt_order(current_time)
+                        trade.open_order_id = None
+                        LocalTrade.add_bt_trade(trade)
+                        self.wallets.update()
+
+                    # 4. Create sell orders (if any)
+                    if not trade.open_order_id:
+                        self._get_sell_trade_entry(trade, row)  # Place sell order if necessary
+
+                    # 5. Process sell orders.
+                    order = trade.select_order(trade.exit_side, is_open=True)
+                    if order and self._get_order_filled(order.price, row):
+                        trade.open_order_id = None
+                        trade.close_date = current_time
+                        trade.close(order.price, show_msg=False)
+
                         # logger.debug(f"{pair} - Backtesting sell {trade}")
                         open_trade_count -= 1
                         open_trades[pair].remove(trade)
-
                         LocalTrade.close_bt_trade(trade)
-                        trades.append(trade_entry)
-                        if enable_protections:
-                            self.protections.stop_per_pair(pair, row[DATE_IDX])
-                            self.protections.global_stop(tmp)
+                        trades.append(trade)
+                        self.wallets.update()
+                        self.run_protections(enable_protections, pair, current_time)
 
             # Move time one configured time_interval ahead.
             self.progress.increment()
-            tmp += timedelta(minutes=self.timeframe_min)
+            current_time += timedelta(minutes=self.timeframe_min)
 
         trades += self.handle_left_open(open_trades, data=data)
         self.wallets.update()
@@ -587,6 +1019,8 @@ class Backtesting:
             'config': self.strategy.config,
             'locks': PairLocks.get_all_locks(),
             'rejected_signals': self.rejected_trades,
+            'timedout_entry_orders': self.timedout_entry_orders,
+            'timedout_exit_orders': self.timedout_exit_orders,
             'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']),
         }
 
@@ -636,6 +1070,7 @@ class Backtesting:
         )
         backtest_end_time = datetime.now(timezone.utc)
         results.update({
+            'run_id': self.run_ids.get(strat.get_strategy_name(), ''),
             'backtest_start_time': int(backtest_start_time.timestamp()),
             'backtest_end_time': int(backtest_end_time.timestamp()),
         })
@@ -662,6 +1097,33 @@ class Backtesting:
 
         return min_date, max_date
 
+    def _get_min_cached_backtest_date(self):
+        min_backtest_date = None
+        backtest_cache_age = self.config.get('backtest_cache', constants.BACKTEST_CACHE_DEFAULT)
+        if self.timerange.stopts == 0 or datetime.fromtimestamp(
+           self.timerange.stopts, tz=timezone.utc) > datetime.now(tz=timezone.utc):
+            logger.warning('Backtest result caching disabled due to use of open-ended timerange.')
+        elif backtest_cache_age == 'day':
+            min_backtest_date = datetime.now(tz=timezone.utc) - timedelta(days=1)
+        elif backtest_cache_age == 'week':
+            min_backtest_date = datetime.now(tz=timezone.utc) - timedelta(weeks=1)
+        elif backtest_cache_age == 'month':
+            min_backtest_date = datetime.now(tz=timezone.utc) - timedelta(weeks=4)
+        return min_backtest_date
+
+    def load_prior_backtest(self):
+        self.run_ids = {
+            strategy.get_strategy_name(): get_strategy_run_id(strategy)
+            for strategy in self.strategylist
+        }
+
+        # Load previous result that will be updated incrementally.
+        # This can be circumvented in certain instances in combination with downloading more data
+        min_backtest_date = self._get_min_cached_backtest_date()
+        if min_backtest_date is not None:
+            self.results = find_existing_backtest_stats(
+                self.config['user_data_dir'] / 'backtest_results', self.run_ids, min_backtest_date)
+
     def start(self) -> None:
         """
         Run backtesting end-to-end
@@ -673,15 +1135,38 @@ class Backtesting:
         self.load_bt_data_detail()
         logger.info("Dataload complete. Calculating indicators")
 
-        for strat in self.strategylist:
-            min_date, max_date = self.backtest_one_strategy(strat, data, timerange)
-        if len(self.strategylist) > 0:
+        self.load_prior_backtest()
 
-            self.results = generate_backtest_stats(data, self.all_results,
-                                                   min_date=min_date, max_date=max_date)
+        for strat in self.strategylist:
+            if self.results and strat.get_strategy_name() in self.results['strategy']:
+                # When previous result hash matches - reuse that result and skip backtesting.
+                logger.info(f'Reusing result of previous backtest for {strat.get_strategy_name()}')
+                continue
+            min_date, max_date = self.backtest_one_strategy(strat, data, timerange)
+
+        # Update old results with new ones.
+        if len(self.all_results) > 0:
+            results = generate_backtest_stats(
+                data, self.all_results, min_date=min_date, max_date=max_date)
+            if self.results:
+                self.results['metadata'].update(results['metadata'])
+                self.results['strategy'].update(results['strategy'])
+                self.results['strategy_comparison'].extend(results['strategy_comparison'])
+            else:
+                self.results = results
 
             if self.config.get('export', 'none') == 'trades':
                 store_backtest_stats(self.config['exportfilename'], self.results)
 
+        # Results may be mixed up now. Sort them so they follow --strategy-list order.
+        if 'strategy_list' in self.config and len(self.results) > 0:
+            self.results['strategy_comparison'] = sorted(
+                self.results['strategy_comparison'],
+                key=lambda c: self.config['strategy_list'].index(c['key']))
+            self.results['strategy'] = dict(
+                sorted(self.results['strategy'].items(),
+                       key=lambda kv: self.config['strategy_list'].index(kv[0])))
+
+        if len(self.strategylist) > 0:
             # Show backtest results
             show_backtest_results(self.config, self.results)
diff --git a/freqtrade/optimize/bt_progress.py b/freqtrade/optimize/bt_progress.py
index d295956c7..c3b105915 100644
--- a/freqtrade/optimize/bt_progress.py
+++ b/freqtrade/optimize/bt_progress.py
@@ -12,7 +12,7 @@ class BTProgress:
     def init_step(self, action: BacktestState, max_steps: float):
         self._action = action
         self._max_steps = max_steps
-        self._proress = 0
+        self._progress = 0
 
     def set_new_value(self, new_value: float):
         self._progress = new_value
diff --git a/freqtrade/optimize/edge_cli.py b/freqtrade/optimize/edge_cli.py
index f211da750..cc9bafb0b 100644
--- a/freqtrade/optimize/edge_cli.py
+++ b/freqtrade/optimize/edge_cli.py
@@ -34,7 +34,7 @@ class EdgeCli:
         self.config['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
         self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
         self.strategy = StrategyResolver.load_strategy(self.config)
-        self.strategy.dp = DataProvider(config, None)
+        self.strategy.dp = DataProvider(config, self.exchange)
 
         validate_config_consistency(self.config)
 
diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py
index 9549b4054..eb8f7ec94 100644
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -45,7 +45,7 @@ progressbar.streams.wrap_stdout()
 logger = logging.getLogger(__name__)
 
 
-INITIAL_POINTS = 5
+INITIAL_POINTS = 30
 
 # Keep no more than SKOPT_MODEL_QUEUE_SIZE models
 # in the skopt model queue, to optimize memory consumption
@@ -76,6 +76,7 @@ class Hyperopt:
         self.config = config
 
         self.backtesting = Backtesting(self.config)
+        self.pairlist = self.backtesting.pairlists.whitelist
 
         if not self.config.get('hyperopt'):
             self.custom_hyperopt = HyperOptAuto(self.config)
@@ -113,10 +114,8 @@ class Hyperopt:
         self.position_stacking = self.config.get('position_stacking', False)
 
         if HyperoptTools.has_space(self.config, 'sell'):
-            # Make sure use_sell_signal is enabled
-            if 'ask_strategy' not in self.config:
-                self.config['ask_strategy'] = {}
-            self.config['ask_strategy']['use_sell_signal'] = True
+            # Make sure use_exit_signal is enabled
+            self.config['use_exit_signal'] = True
 
         self.print_all = self.config.get('print_all', False)
         self.hyperopt_table_header = 0
@@ -258,6 +257,7 @@ class Hyperopt:
         if HyperoptTools.has_space(self.config, 'trailing'):
             logger.debug("Hyperopt has 'trailing' space")
             self.trailing_space = self.custom_hyperopt.trailing_space()
+
         self.dimensions = (self.buy_space + self.sell_space + self.protection_space
                            + self.roi_space + self.stoploss_space + self.trailing_space)
 
@@ -331,7 +331,7 @@ class Hyperopt:
         params_details = self._get_params_details(params_dict)
 
         strat_stats = generate_strategy_stats(
-            processed, self.backtesting.strategy.get_strategy_name(),
+            self.pairlist, self.backtesting.strategy.get_strategy_name(),
             backtesting_results, min_date, max_date, market_change=0
         )
         results_explanation = HyperoptTools.format_results_explanation_string(
@@ -365,7 +365,7 @@ class Hyperopt:
         }
 
     def get_optimizer(self, dimensions: List[Dimension], cpu_count) -> Optimizer:
-        estimator = self.custom_hyperopt.generate_estimator()
+        estimator = self.custom_hyperopt.generate_estimator(dimensions=dimensions)
 
         acq_optimizer = "sampling"
         if isinstance(estimator, str):
@@ -394,6 +394,7 @@ class Hyperopt:
 
     def prepare_hyperopt_data(self) -> None:
         data, timerange = self.backtesting.load_bt_data()
+        self.backtesting.load_bt_data_detail()
         logger.info("Dataload complete. Calculating indicators")
 
         preprocessed = self.backtesting.strategy.advise_all_indicators(data)
@@ -421,6 +422,7 @@ class Hyperopt:
         self.backtesting.exchange.close()
         self.backtesting.exchange._api = None  # type: ignore
         self.backtesting.exchange._api_async = None  # type: ignore
+        self.backtesting.exchange.loop = None  # type: ignore
         # self.backtesting.exchange = None  # type: ignore
         self.backtesting.pairlists = None  # type: ignore
 
diff --git a/freqtrade/optimize/hyperopt_auto.py b/freqtrade/optimize/hyperopt_auto.py
index c1c769c72..5bc0af42b 100644
--- a/freqtrade/optimize/hyperopt_auto.py
+++ b/freqtrade/optimize/hyperopt_auto.py
@@ -3,6 +3,7 @@ HyperOptAuto class.
 This module implements a convenience auto-hyperopt class, which can be used together with strategies
  that implement IHyperStrategy interface.
 """
+import logging
 from contextlib import suppress
 from typing import Callable, Dict, List
 
@@ -15,12 +16,19 @@ with suppress(ImportError):
 from freqtrade.optimize.hyperopt_interface import EstimatorType, IHyperOpt
 
 
-def _format_exception_message(space: str) -> str:
-    raise OperationalException(
-        f"The '{space}' space is included into the hyperoptimization "
-        f"but no parameter for this space was not found in your Strategy. "
-        f"Please make sure to have parameters for this space enabled for optimization "
-        f"or remove the '{space}' space from hyperoptimization.")
+logger = logging.getLogger(__name__)
+
+
+def _format_exception_message(space: str, ignore_missing_space: bool) -> None:
+    msg = (f"The '{space}' space is included into the hyperoptimization "
+           f"but no parameter for this space was not found in your Strategy. "
+           )
+    if ignore_missing_space:
+        logger.warning(msg + "This space will be ignored.")
+    else:
+        raise OperationalException(
+            msg + f"Please make sure to have parameters for this space enabled for optimization "
+            f"or remove the '{space}' space from hyperoptimization.")
 
 
 class HyperOptAuto(IHyperOpt):
@@ -48,13 +56,16 @@ class HyperOptAuto(IHyperOpt):
             if attr.optimize:
                 yield attr.get_space(attr_name)
 
-    def _get_indicator_space(self, category):
+    def _get_indicator_space(self, category) -> List:
         # TODO: is this necessary, or can we call "generate_space" directly?
         indicator_space = list(self._generate_indicator_space(category))
         if len(indicator_space) > 0:
             return indicator_space
         else:
-            _format_exception_message(category)
+            _format_exception_message(
+                category,
+                self.config.get("hyperopt_ignore_missing_space", False))
+            return []
 
     def buy_indicator_space(self) -> List['Dimension']:
         return self._get_indicator_space('buy')
@@ -80,5 +91,5 @@ class HyperOptAuto(IHyperOpt):
     def trailing_space(self) -> List['Dimension']:
         return self._get_func('trailing_space')()
 
-    def generate_estimator(self) -> EstimatorType:
-        return self._get_func('generate_estimator')()
+    def generate_estimator(self, dimensions: List['Dimension'], **kwargs) -> EstimatorType:
+        return self._get_func('generate_estimator')(dimensions=dimensions, **kwargs)
diff --git a/freqtrade/optimize/hyperopt_interface.py b/freqtrade/optimize/hyperopt_interface.py
index 53b4f087c..b1c68caca 100644
--- a/freqtrade/optimize/hyperopt_interface.py
+++ b/freqtrade/optimize/hyperopt_interface.py
@@ -29,18 +29,16 @@ class IHyperOpt(ABC):
     Class attributes you can use:
         timeframe -> int: value of the timeframe to use for the strategy
     """
-    ticker_interval: str  # DEPRECATED
     timeframe: str
     strategy: IStrategy
 
     def __init__(self, config: dict) -> None:
         self.config = config
 
-        # Assign ticker_interval to be used in hyperopt
-        IHyperOpt.ticker_interval = str(config['timeframe'])  # DEPRECATED
+        # Assign timeframe to be used in hyperopt
         IHyperOpt.timeframe = str(config['timeframe'])
 
-    def generate_estimator(self) -> EstimatorType:
+    def generate_estimator(self, dimensions: List[Dimension], **kwargs) -> EstimatorType:
         """
         Return base_estimator.
         Can be any of "GP", "RF", "ET", "GBRT" or an instance of a class
@@ -192,7 +190,7 @@ class IHyperOpt(ABC):
             Categorical([True, False], name='trailing_only_offset_is_reached'),
         ]
 
-    # This is needed for proper unpickling the class attribute ticker_interval
+    # This is needed for proper unpickling the class attribute timeframe
     # which is set to the actual value by the resolver.
     # Why do I still need such shamanic mantras in modern python?
     def __getstate__(self):
@@ -202,5 +200,4 @@ class IHyperOpt(ABC):
 
     def __setstate__(self, state):
         self.__dict__.update(state)
-        IHyperOpt.ticker_interval = state['timeframe']
         IHyperOpt.timeframe = state['timeframe']
diff --git a/freqtrade/optimize/hyperopt_loss_calmar.py b/freqtrade/optimize/hyperopt_loss_calmar.py
new file mode 100644
index 000000000..846dae9ea
--- /dev/null
+++ b/freqtrade/optimize/hyperopt_loss_calmar.py
@@ -0,0 +1,63 @@
+"""
+CalmarHyperOptLoss
+
+This module defines the alternative HyperOptLoss class which can be used for
+Hyperoptimization.
+"""
+from datetime import datetime
+from math import sqrt as msqrt
+from typing import Any, Dict
+
+from pandas import DataFrame
+
+from freqtrade.data.btanalysis import calculate_max_drawdown
+from freqtrade.optimize.hyperopt import IHyperOptLoss
+
+
+class CalmarHyperOptLoss(IHyperOptLoss):
+    """
+    Defines the loss function for hyperopt.
+
+    This implementation uses the Calmar Ratio calculation.
+    """
+
+    @staticmethod
+    def hyperopt_loss_function(
+        results: DataFrame,
+        trade_count: int,
+        min_date: datetime,
+        max_date: datetime,
+        config: Dict,
+        processed: Dict[str, DataFrame],
+        backtest_stats: Dict[str, Any],
+        *args,
+        **kwargs
+    ) -> float:
+        """
+        Objective function, returns smaller number for more optimal results.
+
+        Uses Calmar Ratio calculation.
+        """
+        total_profit = backtest_stats["profit_total"]
+        days_period = (max_date - min_date).days
+
+        # adding slippage of 0.1% per trade
+        total_profit = total_profit - 0.0005
+        expected_returns_mean = total_profit.sum() / days_period * 100
+
+        # calculate max drawdown
+        try:
+            _, _, _, _, _, max_drawdown = calculate_max_drawdown(
+                results, value_col="profit_abs"
+            )
+        except ValueError:
+            max_drawdown = 0
+
+        if max_drawdown != 0:
+            calmar_ratio = expected_returns_mean / max_drawdown * msqrt(365)
+        else:
+            # Define high (negative) calmar ratio to be clear that this is NOT optimal.
+            calmar_ratio = -20.0
+
+        # print(expected_returns_mean, max_drawdown, calmar_ratio)
+        return -calmar_ratio
diff --git a/freqtrade/optimize/hyperopt_loss_max_drawdown.py b/freqtrade/optimize/hyperopt_loss_max_drawdown.py
new file mode 100644
index 000000000..ce955d928
--- /dev/null
+++ b/freqtrade/optimize/hyperopt_loss_max_drawdown.py
@@ -0,0 +1,41 @@
+"""
+MaxDrawDownHyperOptLoss
+
+This module defines the alternative HyperOptLoss class which can be used for
+Hyperoptimization.
+"""
+from datetime import datetime
+
+from pandas import DataFrame
+
+from freqtrade.data.btanalysis import calculate_max_drawdown
+from freqtrade.optimize.hyperopt import IHyperOptLoss
+
+
+class MaxDrawDownHyperOptLoss(IHyperOptLoss):
+
+    """
+    Defines the loss function for hyperopt.
+
+    This implementation optimizes for max draw down and profit
+    Less max drawdown more profit -> Lower return value
+    """
+
+    @staticmethod
+    def hyperopt_loss_function(results: DataFrame, trade_count: int,
+                               min_date: datetime, max_date: datetime,
+                               *args, **kwargs) -> float:
+
+        """
+        Objective function.
+
+        Uses profit ratio weighted max_drawdown when drawdown is available.
+        Otherwise directly optimizes profit ratio.
+        """
+        total_profit = results['profit_abs'].sum()
+        try:
+            max_drawdown = calculate_max_drawdown(results, value_col='profit_abs')
+        except ValueError:
+            # No losing trade, therefore no drawdown.
+            return -total_profit
+        return -total_profit / max_drawdown[0]
diff --git a/freqtrade/optimize/hyperopt_loss_profit_drawdown.py b/freqtrade/optimize/hyperopt_loss_profit_drawdown.py
new file mode 100644
index 000000000..5bd12ff52
--- /dev/null
+++ b/freqtrade/optimize/hyperopt_loss_profit_drawdown.py
@@ -0,0 +1,30 @@
+"""
+ProfitDrawDownHyperOptLoss
+
+This module defines the alternative HyperOptLoss class based on Profit &
+Drawdown objective which can be used for Hyperoptimization.
+
+Possible to change `DRAWDOWN_MULT` to penalize drawdown objective for
+individual needs.
+"""
+from pandas import DataFrame
+
+from freqtrade.data.btanalysis import calculate_max_drawdown
+from freqtrade.optimize.hyperopt import IHyperOptLoss
+
+
+# higher numbers penalize drawdowns more severely
+DRAWDOWN_MULT = 0.075
+
+
+class ProfitDrawDownHyperOptLoss(IHyperOptLoss):
+    @staticmethod
+    def hyperopt_loss_function(results: DataFrame, trade_count: int, *args, **kwargs) -> float:
+        total_profit = results["profit_abs"].sum()
+
+        try:
+            max_drawdown_abs = calculate_max_drawdown(results, value_col="profit_abs")[5]
+        except ValueError:
+            max_drawdown_abs = 0
+
+        return -1 * (total_profit * (1 - max_drawdown_abs * DRAWDOWN_MULT))
diff --git a/freqtrade/optimize/hyperopt_tools.py b/freqtrade/optimize/hyperopt_tools.py
index cfbc2757e..8d3c3a266 100755
--- a/freqtrade/optimize/hyperopt_tools.py
+++ b/freqtrade/optimize/hyperopt_tools.py
@@ -1,4 +1,3 @@
-
 import io
 import logging
 from copy import deepcopy
@@ -64,10 +63,11 @@ class HyperoptTools():
             'export_time': datetime.now(timezone.utc),
         }
         logger.info(f"Dumping parameters to {filename}")
-        rapidjson.dump(final_params, filename.open('w'), indent=2,
-                       default=hyperopt_serializer,
-                       number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN
-                       )
+        with filename.open('w') as f:
+            rapidjson.dump(final_params, f, indent=2,
+                           default=hyperopt_serializer,
+                           number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN
+                           )
 
     @staticmethod
     def try_export_params(config: Dict[str, Any], strategy_name: str, params: Dict):
@@ -137,6 +137,7 @@ class HyperoptTools():
         }
         if not HyperoptTools._test_hyperopt_results_exist(results_file):
             # No file found.
+            logger.warning(f"Hyperopt file {results_file} not found.")
             return [], 0
 
         epochs = []
@@ -284,10 +285,10 @@ class HyperoptTools():
         return (f"{results_metrics['total_trades']:6d} trades. "
                 f"{results_metrics['wins']}/{results_metrics['draws']}"
                 f"/{results_metrics['losses']} Wins/Draws/Losses. "
-                f"Avg profit {results_metrics['profit_mean'] * 100: 6.2f}%. "
-                f"Median profit {results_metrics['profit_median'] * 100: 6.2f}%. "
-                f"Total profit {results_metrics['profit_total_abs']: 11.8f} {stake_currency} "
-                f"({results_metrics['profit_total'] * 100: 7.2f}%). "
+                f"Avg profit {results_metrics['profit_mean']:7.2%}. "
+                f"Median profit {results_metrics['profit_median']:7.2%}. "
+                f"Total profit {results_metrics['profit_total_abs']:11.8f} {stake_currency} "
+                f"({results_metrics['profit_total']:8.2%}). "
                 f"Avg duration {results_metrics['holding_avg']} min."
                 )
 
@@ -299,8 +300,7 @@ class HyperoptTools():
                 f"Objective: {results['loss']:.5f}")
 
     @staticmethod
-    def prepare_trials_columns(trials: pd.DataFrame, legacy_mode: bool,
-                               has_drawdown: bool) -> pd.DataFrame:
+    def prepare_trials_columns(trials: pd.DataFrame, has_drawdown: bool) -> pd.DataFrame:
         trials['Best'] = ''
 
         if 'results_metrics.winsdrawslosses' not in trials.columns:
@@ -309,33 +309,26 @@ class HyperoptTools():
 
         if not has_drawdown:
             # Ensure compatibility with older versions of hyperopt results
-            trials['results_metrics.max_drawdown_abs'] = None
-            trials['results_metrics.max_drawdown'] = None
+            trials['results_metrics.max_drawdown_account'] = None
 
-        if not legacy_mode:
-            # New mode, using backtest result for metrics
-            trials['results_metrics.winsdrawslosses'] = trials.apply(
-                lambda x: f"{x['results_metrics.wins']} {x['results_metrics.draws']:>4} "
-                          f"{x['results_metrics.losses']:>4}", axis=1)
-            trials = trials[['Best', 'current_epoch', 'results_metrics.total_trades',
-                             'results_metrics.winsdrawslosses',
-                             'results_metrics.profit_mean', 'results_metrics.profit_total_abs',
-                             'results_metrics.profit_total', 'results_metrics.holding_avg',
-                             'results_metrics.max_drawdown', 'results_metrics.max_drawdown_abs',
-                             'loss', 'is_initial_point', 'is_best']]
+        # New mode, using backtest result for metrics
+        trials['results_metrics.winsdrawslosses'] = trials.apply(
+            lambda x: f"{x['results_metrics.wins']} {x['results_metrics.draws']:>4} "
+                      f"{x['results_metrics.losses']:>4}", axis=1)
 
-        else:
-            # Legacy mode
-            trials = trials[['Best', 'current_epoch', 'results_metrics.trade_count',
-                             'results_metrics.winsdrawslosses', 'results_metrics.avg_profit',
-                             'results_metrics.total_profit', 'results_metrics.profit',
-                             'results_metrics.duration', 'results_metrics.max_drawdown',
-                             'results_metrics.max_drawdown_abs', 'loss', 'is_initial_point',
-                             'is_best']]
+        trials = trials[['Best', 'current_epoch', 'results_metrics.total_trades',
+                         'results_metrics.winsdrawslosses',
+                         'results_metrics.profit_mean', 'results_metrics.profit_total_abs',
+                         'results_metrics.profit_total', 'results_metrics.holding_avg',
+                         'results_metrics.max_drawdown',
+                         'results_metrics.max_drawdown_account', 'results_metrics.max_drawdown_abs',
+                         'loss', 'is_initial_point', 'is_best']]
 
-        trials.columns = ['Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit',
-                          'Total profit', 'Profit', 'Avg duration', 'Max Drawdown',
-                          'max_drawdown_abs', 'Objective', 'is_initial_point', 'is_best']
+        trials.columns = [
+            'Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit',
+            'Total profit', 'Profit', 'Avg duration', 'max_drawdown', 'max_drawdown_account',
+            'max_drawdown_abs', 'Objective', 'is_initial_point', 'is_best'
+            ]
 
         return trials
 
@@ -351,10 +344,9 @@ class HyperoptTools():
         tabulate.PRESERVE_WHITESPACE = True
         trials = json_normalize(results, max_level=1)
 
-        legacy_mode = 'results_metrics.total_trades' not in trials
-        has_drawdown = 'results_metrics.max_drawdown_abs' in trials.columns
+        has_account_drawdown = 'results_metrics.max_drawdown_account' in trials.columns
 
-        trials = HyperoptTools.prepare_trials_columns(trials, legacy_mode, has_drawdown)
+        trials = HyperoptTools.prepare_trials_columns(trials, has_account_drawdown)
 
         trials['is_profit'] = False
         trials.loc[trials['is_initial_point'], 'Best'] = '*     '
@@ -362,12 +354,12 @@ class HyperoptTools():
         trials.loc[trials['is_initial_point'] & trials['is_best'], 'Best'] = '* Best'
         trials.loc[trials['Total profit'] > 0, 'is_profit'] = True
         trials['Trades'] = trials['Trades'].astype(str)
-        perc_multi = 1 if legacy_mode else 100
+        # perc_multi = 1 if legacy_mode else 100
         trials['Epoch'] = trials['Epoch'].apply(
             lambda x: '{}/{}'.format(str(x).rjust(len(str(total_epochs)), ' '), total_epochs)
         )
         trials['Avg profit'] = trials['Avg profit'].apply(
-            lambda x: f'{x * perc_multi:,.2f}%'.rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
+            lambda x: f'{x:,.2%}'.rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
         )
         trials['Avg duration'] = trials['Avg duration'].apply(
             lambda x: f'{x:,.1f} m'.rjust(7, ' ') if isinstance(x, float) else f"{x}"
@@ -379,26 +371,27 @@ class HyperoptTools():
 
         stake_currency = config['stake_currency']
 
-        if has_drawdown:
-            trials['Max Drawdown'] = trials.apply(
-                lambda x: '{} {}'.format(
-                    round_coin_value(x['max_drawdown_abs'], stake_currency),
-                    '({:,.2f}%)'.format(x['Max Drawdown'] * perc_multi).rjust(10, ' ')
-                ).rjust(25 + len(stake_currency))
-                if x['Max Drawdown'] != 0.0 else '--'.rjust(25 + len(stake_currency)),
-                axis=1
-            )
-        else:
-            trials = trials.drop(columns=['Max Drawdown'])
+        trials[f"Max Drawdown{' (Acct)' if has_account_drawdown else ''}"] = trials.apply(
+            lambda x: "{} {}".format(
+                round_coin_value(x['max_drawdown_abs'], stake_currency, keep_trailing_zeros=True),
+                (f"({x['max_drawdown_account']:,.2%})"
+                    if has_account_drawdown
+                    else f"({x['max_drawdown']:,.2%})"
+                 ).rjust(10, ' ')
+            ).rjust(25 + len(stake_currency))
+            if x['max_drawdown'] != 0.0 or x['max_drawdown_account'] != 0.0
+            else '--'.rjust(25 + len(stake_currency)),
+            axis=1
+        )
 
-        trials = trials.drop(columns=['max_drawdown_abs'])
+        trials = trials.drop(columns=['max_drawdown_abs', 'max_drawdown', 'max_drawdown_account'])
 
         trials['Profit'] = trials.apply(
             lambda x: '{} {}'.format(
-                round_coin_value(x['Total profit'], stake_currency),
-                '({:,.2f}%)'.format(x['Profit'] * perc_multi).rjust(10, ' ')
-            ).rjust(25+len(stake_currency))
-            if x['Total profit'] != 0.0 else '--'.rjust(25+len(stake_currency)),
+                round_coin_value(x['Total profit'], stake_currency, keep_trailing_zeros=True),
+                f"({x['Profit']:,.2%})".rjust(10, ' ')
+            ).rjust(25 + len(stake_currency))
+            if x['Total profit'] != 0.0 else '--'.rjust(25 + len(stake_currency)),
             axis=1
         )
         trials = trials.drop(columns=['Total profit'])
@@ -406,11 +399,11 @@ class HyperoptTools():
         if print_colorized:
             for i in range(len(trials)):
                 if trials.loc[i]['is_profit']:
-                    for j in range(len(trials.loc[i])-3):
+                    for j in range(len(trials.loc[i]) - 3):
                         trials.iat[i, j] = "{}{}{}".format(Fore.GREEN,
                                                            str(trials.loc[i][j]), Fore.RESET)
                 if trials.loc[i]['is_best'] and highlight_best:
-                    for j in range(len(trials.loc[i])-3):
+                    for j in range(len(trials.loc[i]) - 3):
                         trials.iat[i, j] = "{}{}{}".format(Style.BRIGHT,
                                                            str(trials.loc[i][j]), Style.RESET_ALL)
 
@@ -466,7 +459,7 @@ class HyperoptTools():
                         'loss', 'is_initial_point', 'is_best']
         perc_multi = 100
 
-        param_metrics = [("params_dict."+param) for param in results[0]['params_dict'].keys()]
+        param_metrics = [("params_dict." + param) for param in results[0]['params_dict'].keys()]
         trials = trials[base_metrics + param_metrics]
 
         base_columns = ['Best', 'Epoch', 'Trades', 'Avg profit', 'Median profit', 'Total profit',
diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py
index 8bde48670..c08fa07a1 100644
--- a/freqtrade/optimize/optimize_reports.py
+++ b/freqtrade/optimize/optimize_reports.py
@@ -1,16 +1,18 @@
 import logging
+from copy import deepcopy
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from typing import Any, Dict, List, Union
 
 from numpy import int64
-from pandas import DataFrame
+from pandas import DataFrame, to_datetime
 from tabulate import tabulate
 
 from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT
 from freqtrade.data.btanalysis import (calculate_csum, calculate_market_change,
                                        calculate_max_drawdown)
-from freqtrade.misc import decimals_per_coin, file_dump_json, round_coin_value
+from freqtrade.misc import (decimals_per_coin, file_dump_json, get_backtest_metadata_filename,
+                            round_coin_value)
 
 
 logger = logging.getLogger(__name__)
@@ -32,6 +34,11 @@ def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> N
             recordfilename.parent,
             f'{recordfilename.stem}-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}'
         ).with_suffix(recordfilename.suffix)
+
+    # Store metadata separately.
+    file_dump_json(get_backtest_metadata_filename(filename), stats['metadata'])
+    del stats['metadata']
+
     file_dump_json(filename, stats)
 
     latest_filename = Path.joinpath(filename.parent, LAST_BT_RESULT_FN)
@@ -46,11 +53,11 @@ def _get_line_floatfmt(stake_currency: str) -> List[str]:
             '.2f', 'd', 's', 's']
 
 
-def _get_line_header(first_column: str, stake_currency: str) -> List[str]:
+def _get_line_header(first_column: str, stake_currency: str, direction: str = 'Buys') -> List[str]:
     """
     Generate header lines (goes in line with _generate_result_line())
     """
-    return [first_column, 'Buys', 'Avg Profit %', 'Cum Profit %',
+    return [first_column, direction, 'Avg Profit %', 'Cum Profit %',
             f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
             'Win  Draw  Loss  Win%']
 
@@ -98,11 +105,11 @@ def _generate_result_line(result: DataFrame, starting_balance: int, first_column
     }
 
 
-def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_balance: int,
+def generate_pair_metrics(pairlist: List[str], stake_currency: str, starting_balance: int,
                           results: DataFrame, skip_nan: bool = False) -> List[Dict]:
     """
     Generates and returns a list  for the given backtest data and the results dataframe
-    :param data: Dict of <pair: dataframe> containing data that was used during backtesting.
+    :param pairlist: Pairlist used
     :param stake_currency: stake-currency - used to correctly name headers
     :param starting_balance: Starting balance
     :param results: Dataframe containing the backtest results
@@ -112,7 +119,7 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_b
 
     tabular_data = []
 
-    for pair in data:
+    for pair in pairlist:
         result = results[results['pair'] == pair]
         if skip_nan and result['profit_abs'].isnull().all():
             continue
@@ -127,7 +134,39 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_b
     return tabular_data
 
 
-def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]:
+def generate_tag_metrics(tag_type: str,
+                         starting_balance: int,
+                         results: DataFrame,
+                         skip_nan: bool = False) -> List[Dict]:
+    """
+    Generates and returns a list of metrics for the given tag trades and the results dataframe
+    :param starting_balance: Starting balance
+    :param results: Dataframe containing the backtest results
+    :param skip_nan: Print "left open" open trades
+    :return: List of Dicts containing the metrics per pair
+    """
+
+    tabular_data = []
+
+    if tag_type in results.columns:
+        for tag, count in results[tag_type].value_counts().iteritems():
+            result = results[results[tag_type] == tag]
+            if skip_nan and result['profit_abs'].isnull().all():
+                continue
+
+            tabular_data.append(_generate_result_line(result, starting_balance, tag))
+
+        # Sort by total profit %:
+        tabular_data = sorted(tabular_data, key=lambda k: k['profit_total_abs'], reverse=True)
+
+        # Append Total
+        tabular_data.append(_generate_result_line(results, starting_balance, 'TOTAL'))
+        return tabular_data
+    else:
+        return []
+
+
+def generate_exit_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]:
     """
     Generate small table outlining Backtest results
     :param max_open_trades: Max_open_trades parameter
@@ -136,8 +175,8 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List
     """
     tabular_data = []
 
-    for reason, count in results['sell_reason'].value_counts().iteritems():
-        result = results.loc[results['sell_reason'] == reason]
+    for reason, count in results['exit_reason'].value_counts().iteritems():
+        result = results.loc[results['exit_reason'] == reason]
 
         profit_mean = result['profit_ratio'].mean()
         profit_sum = result['profit_ratio'].sum()
@@ -145,7 +184,7 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List
 
         tabular_data.append(
             {
-                'sell_reason': reason,
+                'exit_reason': reason,
                 'trades': count,
                 'wins': len(result[result['profit_abs'] > 0]),
                 'draws': len(result[result['profit_abs'] == 0]),
@@ -162,34 +201,25 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List
     return tabular_data
 
 
-def generate_strategy_comparison(all_results: Dict) -> List[Dict]:
+def generate_strategy_comparison(bt_stats: Dict) -> List[Dict]:
     """
     Generate summary per strategy
-    :param all_results: Dict of <Strategyname: DataFrame> containing results for all strategies
+    :param bt_stats: Dict of <Strategyname: DataFrame> containing results for all strategies
     :return: List of Dicts containing the metrics per Strategy
     """
 
     tabular_data = []
-    for strategy, results in all_results.items():
-        tabular_data.append(_generate_result_line(
-            results['results'], results['config']['dry_run_wallet'], strategy)
-        )
-        try:
-            max_drawdown_per, _, _, _, _ = calculate_max_drawdown(results['results'],
-                                                                  value_col='profit_ratio')
-            max_drawdown_abs, _, _, _, _ = calculate_max_drawdown(results['results'],
-                                                                  value_col='profit_abs')
-        except ValueError:
-            max_drawdown_per = 0
-            max_drawdown_abs = 0
-        tabular_data[-1]['max_drawdown_per'] = round(max_drawdown_per * 100, 2)
-        tabular_data[-1]['max_drawdown_abs'] = \
-            round_coin_value(max_drawdown_abs, results['config']['stake_currency'], False)
+    for strategy, result in bt_stats.items():
+        tabular_data.append(deepcopy(result['results_per_pair'][-1]))
+        # Update "key" to strategy (results_per_pair has it as "Total").
+        tabular_data[-1]['key'] = strategy
+        tabular_data[-1]['max_drawdown_account'] = result['max_drawdown_account']
+        tabular_data[-1]['max_drawdown_abs'] = round_coin_value(
+            result['max_drawdown_abs'], result['stake_currency'], False)
     return tabular_data
 
 
 def generate_edge_table(results: dict) -> str:
-
     floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', 'd', 'd')
     tabular_data = []
     headers = ['Pair', 'Stoploss', 'Win Rate', 'Risk Reward Ratio',
@@ -214,6 +244,41 @@ def generate_edge_table(results: dict) -> str:
                     floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")  # type: ignore
 
 
+def _get_resample_from_period(period: str) -> str:
+    if period == 'day':
+        return '1d'
+    if period == 'week':
+        return '1w'
+    if period == 'month':
+        return '1M'
+    raise ValueError(f"Period {period} is not supported.")
+
+
+def generate_periodic_breakdown_stats(trade_list: List, period: str) -> List[Dict[str, Any]]:
+    results = DataFrame.from_records(trade_list)
+    if len(results) == 0:
+        return []
+    results['close_date'] = to_datetime(results['close_date'], utc=True)
+    resample_period = _get_resample_from_period(period)
+    resampled = results.resample(resample_period, on='close_date')
+    stats = []
+    for name, day in resampled:
+        profit_abs = day['profit_abs'].sum().round(10)
+        wins = sum(day['profit_abs'] > 0)
+        draws = sum(day['profit_abs'] == 0)
+        loses = sum(day['profit_abs'] < 0)
+        stats.append(
+            {
+                'date': name.strftime('%d/%m/%Y'),
+                'profit_abs': profit_abs,
+                'wins': wins,
+                'draws': draws,
+                'loses': loses
+            }
+        )
+    return stats
+
+
 def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
     """ Generate overall trade statistics """
     if len(results) == 0:
@@ -286,14 +351,14 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
     }
 
 
-def generate_strategy_stats(btdata: Dict[str, DataFrame],
+def generate_strategy_stats(pairlist: List[str],
                             strategy: str,
                             content: Dict[str, Any],
                             min_date: datetime, max_date: datetime,
                             market_change: float
                             ) -> Dict[str, Any]:
     """
-    :param btdata: Backtest data
+    :param pairlist: List of pairs to backtest
     :param strategy: Strategy name
     :param content: Backtest result data in the format:
                     {'results: results, 'config: config}}.
@@ -306,17 +371,21 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
     if not isinstance(results, DataFrame):
         return {}
     config = content['config']
-    max_open_trades = min(config['max_open_trades'], len(btdata.keys()))
-    starting_balance = config['dry_run_wallet']
+    max_open_trades = min(config['max_open_trades'], len(pairlist))
+    start_balance = config['dry_run_wallet']
     stake_currency = config['stake_currency']
 
-    pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
-                                         starting_balance=starting_balance,
+    pair_results = generate_pair_metrics(pairlist, stake_currency=stake_currency,
+                                         starting_balance=start_balance,
                                          results=results, skip_nan=False)
-    sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
+
+    enter_tag_results = generate_tag_metrics("enter_tag", starting_balance=start_balance,
+                                             results=results, skip_nan=False)
+
+    exit_reason_stats = generate_exit_reason_stats(max_open_trades=max_open_trades,
                                                    results=results)
-    left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
-                                              starting_balance=starting_balance,
+    left_open_results = generate_pair_metrics(pairlist, stake_currency=stake_currency,
+                                              starting_balance=start_balance,
                                               results=results.loc[results['is_open']],
                                               skip_nan=True)
     daily_stats = generate_daily_stats(results)
@@ -329,22 +398,31 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
         results['open_timestamp'] = results['open_date'].view(int64) // 1e6
         results['close_timestamp'] = results['close_date'].view(int64) // 1e6
 
-    backtest_days = (max_date - min_date).days
+    backtest_days = (max_date - min_date).days or 1
     strat_stats = {
         'trades': results.to_dict(orient='records'),
         'locks': [lock.to_json() for lock in content['locks']],
         'best_pair': best_pair,
         'worst_pair': worst_pair,
         'results_per_pair': pair_results,
-        'sell_reason_summary': sell_reason_stats,
+        'results_per_enter_tag': enter_tag_results,
+        'exit_reason_summary': exit_reason_stats,
         'left_open_trades': left_open_results,
+        # 'days_breakdown_stats': days_breakdown_stats,
+
         'total_trades': len(results),
+        'trade_count_long': len(results.loc[~results['is_short']]),
+        'trade_count_short': len(results.loc[results['is_short']]),
         'total_volume': float(results['stake_amount'].sum()),
         'avg_stake_amount': results['stake_amount'].mean() if len(results) > 0 else 0,
         'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0,
         'profit_median': results['profit_ratio'].median() if len(results) > 0 else 0,
-        'profit_total': results['profit_abs'].sum() / starting_balance,
+        'profit_total': results['profit_abs'].sum() / start_balance,
+        'profit_total_long': results.loc[~results['is_short'], 'profit_abs'].sum() / start_balance,
+        'profit_total_short': results.loc[results['is_short'], 'profit_abs'].sum() / start_balance,
         'profit_total_abs': results['profit_abs'].sum(),
+        'profit_total_long_abs': results.loc[~results['is_short'], 'profit_abs'].sum(),
+        'profit_total_short_abs': results.loc[results['is_short'], 'profit_abs'].sum(),
         'backtest_start': min_date.strftime(DATETIME_PRINT_FORMAT),
         'backtest_start_ts': int(min_date.timestamp() * 1000),
         'backtest_end': max_date.strftime(DATETIME_PRINT_FORMAT),
@@ -354,16 +432,18 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
         'backtest_run_start_ts': content['backtest_start_time'],
         'backtest_run_end_ts': content['backtest_end_time'],
 
-        'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else 0,
+        'trades_per_day': round(len(results) / backtest_days, 2),
         'market_change': market_change,
-        'pairlist': list(btdata.keys()),
+        'pairlist': pairlist,
         'stake_amount': config['stake_amount'],
         'stake_currency': config['stake_currency'],
         'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
-        'starting_balance': starting_balance,
-        'dry_run_wallet': starting_balance,
+        'starting_balance': start_balance,
+        'dry_run_wallet': start_balance,
         'final_balance': content['final_balance'],
         'rejected_signals': content['rejected_signals'],
+        'timedout_entry_orders': content['timedout_entry_orders'],
+        'timedout_exit_orders': content['timedout_exit_orders'],
         'max_open_trades': max_open_trades,
         'max_open_trades_setting': (config['max_open_trades']
                                     if config['max_open_trades'] != float('inf') else -1),
@@ -380,21 +460,23 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
         'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached', False),
         'use_custom_stoploss': config.get('use_custom_stoploss', False),
         'minimal_roi': config['minimal_roi'],
-        'use_sell_signal': config['use_sell_signal'],
-        'sell_profit_only': config['sell_profit_only'],
-        'sell_profit_offset': config['sell_profit_offset'],
-        'ignore_roi_if_buy_signal': config['ignore_roi_if_buy_signal'],
+        'use_exit_signal': config['use_exit_signal'],
+        'exit_profit_only': config['exit_profit_only'],
+        'exit_profit_offset': config['exit_profit_offset'],
+        'ignore_roi_if_entry_signal': config['ignore_roi_if_entry_signal'],
         **daily_stats,
         **trade_stats
     }
 
     try:
-        max_drawdown, _, _, _, _ = calculate_max_drawdown(
+        max_drawdown_legacy, _, _, _, _, _ = calculate_max_drawdown(
             results, value_col='profit_ratio')
-        drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown(
-            results, value_col='profit_abs')
+        (drawdown_abs, drawdown_start, drawdown_end, high_val, low_val,
+         max_drawdown) = calculate_max_drawdown(
+             results, value_col='profit_abs', starting_balance=start_balance)
         strat_stats.update({
-            'max_drawdown': max_drawdown,
+            'max_drawdown': max_drawdown_legacy,  # Deprecated - do not use
+            'max_drawdown_account': max_drawdown,
             'max_drawdown_abs': drawdown_abs,
             'drawdown_start': drawdown_start.strftime(DATETIME_PRINT_FORMAT),
             'drawdown_start_ts': drawdown_start.timestamp() * 1000,
@@ -405,7 +487,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
             'max_drawdown_high': high_val,
         })
 
-        csum_min, csum_max = calculate_csum(results, starting_balance)
+        csum_min, csum_max = calculate_csum(results, start_balance)
         strat_stats.update({
             'csum_min': csum_min,
             'csum_max': csum_max
@@ -414,6 +496,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
     except ValueError:
         strat_stats.update({
             'max_drawdown': 0.0,
+            'max_drawdown_account': 0.0,
             'max_drawdown_abs': 0.0,
             'max_drawdown_low': 0.0,
             'max_drawdown_high': 0.0,
@@ -440,16 +523,26 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
     :param max_date: Backtest end date
     :return: Dictionary containing results per strategy and a strategy summary.
     """
-    result: Dict[str, Any] = {'strategy': {}}
+    result: Dict[str, Any] = {
+        'metadata': {},
+        'strategy': {},
+        'strategy_comparison': [],
+    }
     market_change = calculate_market_change(btdata, 'close')
-
+    metadata = {}
+    pairlist = list(btdata.keys())
     for strategy, content in all_results.items():
-        strat_stats = generate_strategy_stats(btdata, strategy, content,
+        strat_stats = generate_strategy_stats(pairlist, strategy, content,
                                               min_date, max_date, market_change=market_change)
+        metadata[strategy] = {
+            'run_id': content['run_id'],
+            'backtest_start_time': content['backtest_start_time'],
+        }
         result['strategy'][strategy] = strat_stats
 
-    strategy_results = generate_strategy_comparison(all_results=all_results)
+    strategy_results = generate_strategy_comparison(bt_stats=result['strategy'])
 
+    result['metadata'] = metadata
     result['strategy_comparison'] = strategy_results
 
     return result
@@ -479,16 +572,16 @@ def text_table_bt_results(pair_results: List[Dict[str, Any]], stake_currency: st
                     floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
 
 
-def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_currency: str) -> str:
+def text_table_exit_reason(exit_reason_stats: List[Dict[str, Any]], stake_currency: str) -> str:
     """
     Generate small table outlining Backtest results
-    :param sell_reason_stats: Sell reason metrics
+    :param sell_reason_stats: Exit reason metrics
     :param stake_currency: Stakecurrency used
     :return: pretty printed table with tabulate as string
     """
     headers = [
-        'Sell Reason',
-        'Sells',
+        'Exit Reason',
+        'Exits',
         'Win  Draws  Loss  Win%',
         'Avg Profit %',
         'Cum Profit %',
@@ -497,12 +590,65 @@ def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_curren
     ]
 
     output = [[
-        t['sell_reason'], t['trades'],
+        t.get('exit_reason', t.get('sell_reason')), t['trades'],
         _generate_wins_draws_losses(t['wins'], t['draws'], t['losses']),
         t['profit_mean_pct'], t['profit_sum_pct'],
         round_coin_value(t['profit_total_abs'], stake_currency, False),
         t['profit_total_pct'],
-    ] for t in sell_reason_stats]
+    ] for t in exit_reason_stats]
+    return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
+
+
+def text_table_tags(tag_type: str, tag_results: List[Dict[str, Any]], stake_currency: str) -> str:
+    """
+    Generates and returns a text table for the given backtest data and the results dataframe
+    :param pair_results: List of Dictionaries - one entry per pair + final TOTAL row
+    :param stake_currency: stake-currency - used to correctly name headers
+    :return: pretty printed table with tabulate as string
+    """
+    if(tag_type == "enter_tag"):
+        headers = _get_line_header("TAG", stake_currency)
+    else:
+        headers = _get_line_header("TAG", stake_currency, 'Sells')
+    floatfmt = _get_line_floatfmt(stake_currency)
+    output = [
+        [
+            t['key'] if t['key'] is not None and len(
+                t['key']) > 0 else "OTHER",
+            t['trades'],
+            t['profit_mean_pct'],
+            t['profit_sum_pct'],
+            t['profit_total_abs'],
+            t['profit_total_pct'],
+            t['duration_avg'],
+            _generate_wins_draws_losses(
+                t['wins'],
+                t['draws'],
+                t['losses'])] for t in tag_results]
+    # Ignore type as floatfmt does allow tuples but mypy does not know that
+    return tabulate(output, headers=headers,
+                    floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
+
+
+def text_table_periodic_breakdown(days_breakdown_stats: List[Dict[str, Any]],
+                                  stake_currency: str, period: str) -> str:
+    """
+    Generate small table with Backtest results by days
+    :param days_breakdown_stats: Days breakdown metrics
+    :param stake_currency: Stakecurrency used
+    :return: pretty printed table with tabulate as string
+    """
+    headers = [
+        period.capitalize(),
+        f'Tot Profit {stake_currency}',
+        'Wins',
+        'Draws',
+        'Losses',
+    ]
+    output = [[
+        d['date'], round_coin_value(d['profit_abs'], stake_currency, False),
+        d['wins'], d['draws'], d['loses'],
+    ] for d in days_breakdown_stats]
     return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
 
 
@@ -520,7 +666,12 @@ def text_table_strategy(strategy_results, stake_currency: str) -> str:
     headers.append('Drawdown')
 
     # Align drawdown string on the center two space separator.
-    drawdown = [f'{t["max_drawdown_per"]:.2f}' for t in strategy_results]
+    if 'max_drawdown_account' in strategy_results[0]:
+        drawdown = [f'{t["max_drawdown_account"] * 100:.2f}' for t in strategy_results]
+    else:
+        # Support for prior backtest results
+        drawdown = [f'{t["max_drawdown_per"]:.2f}' for t in strategy_results]
+
     dd_pad_abs = max([len(t['max_drawdown_abs']) for t in strategy_results])
     dd_pad_per = max([len(dd) for dd in drawdown])
     drawdown = [f'{t["max_drawdown_abs"]:>{dd_pad_abs}} {stake_currency}  {dd:>{dd_pad_per}}%'
@@ -541,6 +692,19 @@ def text_table_add_metrics(strat_results: Dict) -> str:
         best_trade = max(strat_results['trades'], key=lambda x: x['profit_ratio'])
         worst_trade = min(strat_results['trades'], key=lambda x: x['profit_ratio'])
 
+        short_metrics = [
+            ('', ''),  # Empty line to improve readability
+            ('Long / Short',
+             f"{strat_results.get('trade_count_long', 'total_trades')} / "
+             f"{strat_results.get('trade_count_short', 0)}"),
+            ('Total profit Long %', f"{strat_results['profit_total_long']:.2%}"),
+            ('Total profit Short %', f"{strat_results['profit_total_short']:.2%}"),
+            ('Absolute profit Long', round_coin_value(strat_results['profit_total_long_abs'],
+                                                      strat_results['stake_currency'])),
+            ('Absolute profit Short', round_coin_value(strat_results['profit_total_short_abs'],
+                                                       strat_results['stake_currency'])),
+        ] if strat_results.get('trade_count_short', 0) > 0 else []
+
         # Newly added fields should be ignored if they are missing in strat_results. hyperopt-show
         # command stores these results and newer version of freqtrade must be able to handle old
         # results with missing new fields.
@@ -551,25 +715,30 @@ def text_table_add_metrics(strat_results: Dict) -> str:
             ('', ''),  # Empty line to improve readability
             ('Total/Daily Avg Trades',
                 f"{strat_results['total_trades']} / {strat_results['trades_per_day']}"),
+
             ('Starting balance', round_coin_value(strat_results['starting_balance'],
                                                   strat_results['stake_currency'])),
             ('Final balance', round_coin_value(strat_results['final_balance'],
                                                strat_results['stake_currency'])),
             ('Absolute profit ', round_coin_value(strat_results['profit_total_abs'],
                                                   strat_results['stake_currency'])),
-            ('Total profit %', f"{round(strat_results['profit_total'] * 100, 2):}%"),
+            ('Total profit %', f"{strat_results['profit_total']:.2%}"),
+            ('Trades per day', strat_results['trades_per_day']),
+            ('Avg. daily profit %',
+             f"{(strat_results['profit_total'] / strat_results['backtest_days']):.2%}"),
             ('Avg. stake amount', round_coin_value(strat_results['avg_stake_amount'],
                                                    strat_results['stake_currency'])),
             ('Total trade volume', round_coin_value(strat_results['total_volume'],
                                                     strat_results['stake_currency'])),
+            *short_metrics,
             ('', ''),  # Empty line to improve readability
             ('Best Pair', f"{strat_results['best_pair']['key']} "
-                          f"{round(strat_results['best_pair']['profit_sum_pct'], 2)}%"),
+                          f"{strat_results['best_pair']['profit_sum']:.2%}"),
             ('Worst Pair', f"{strat_results['worst_pair']['key']} "
-                           f"{round(strat_results['worst_pair']['profit_sum_pct'], 2)}%"),
-            ('Best trade', f"{best_trade['pair']} {round(best_trade['profit_ratio'] * 100, 2)}%"),
+                           f"{strat_results['worst_pair']['profit_sum']:.2%}"),
+            ('Best trade', f"{best_trade['pair']} {best_trade['profit_ratio']:.2%}"),
             ('Worst trade', f"{worst_trade['pair']} "
-                            f"{round(worst_trade['profit_ratio'] * 100, 2)}%"),
+                            f"{worst_trade['profit_ratio']:.2%}"),
 
             ('Best day', round_coin_value(strat_results['backtest_best_day_abs'],
                                           strat_results['stake_currency'])),
@@ -579,7 +748,10 @@ def text_table_add_metrics(strat_results: Dict) -> str:
                 f"{strat_results['draw_days']} / {strat_results['losing_days']}"),
             ('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
             ('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
-            ('Rejected Buy signals', strat_results.get('rejected_signals', 'N/A')),
+            ('Rejected Entry signals', strat_results.get('rejected_signals', 'N/A')),
+            ('Entry/Exit Timeouts',
+             f"{strat_results.get('timedout_entry_orders', 'N/A')} / "
+             f"{strat_results.get('timedout_exit_orders', 'N/A')}"),
             ('', ''),  # Empty line to improve readability
 
             ('Min balance', round_coin_value(strat_results['csum_min'],
@@ -587,7 +759,10 @@ def text_table_add_metrics(strat_results: Dict) -> str:
             ('Max balance', round_coin_value(strat_results['csum_max'],
                                              strat_results['stake_currency'])),
 
-            ('Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"),
+            # Compatibility to show old hyperopt results
+            ('Drawdown (Account)', f"{strat_results['max_drawdown_account']:.2%}")
+            if 'max_drawdown_account' in strat_results else (
+                'Drawdown', f"{strat_results['max_drawdown']:.2%}"),
             ('Drawdown', round_coin_value(strat_results['max_drawdown_abs'],
                                           strat_results['stake_currency'])),
             ('Drawdown high', round_coin_value(strat_results['max_drawdown_high'],
@@ -596,7 +771,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
                                               strat_results['stake_currency'])),
             ('Drawdown Start', strat_results['drawdown_start']),
             ('Drawdown End', strat_results['drawdown_end']),
-            ('Market change', f"{round(strat_results['market_change'] * 100, 2)}%"),
+            ('Market change', f"{strat_results['market_change']:.2%}"),
         ]
 
         return tabulate(metrics, headers=["Metric", "Value"], tablefmt="orgtbl")
@@ -614,7 +789,8 @@ def text_table_add_metrics(strat_results: Dict) -> str:
         return message
 
 
-def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency: str):
+def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency: str,
+                         backtest_breakdown=[]):
     """
     Print results for one strategy
     """
@@ -625,10 +801,23 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
         print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
     print(table)
 
-    table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'],
+    if (results.get('results_per_enter_tag') is not None
+            or results.get('results_per_buy_tag') is not None):
+        # results_per_buy_tag is deprecated and should be removed 2 versions after short golive.
+        table = text_table_tags(
+            "enter_tag",
+            results.get('results_per_enter_tag', results.get('results_per_buy_tag')),
+            stake_currency=stake_currency)
+
+        if isinstance(table, str) and len(table) > 0:
+            print(' ENTER TAG STATS '.center(len(table.splitlines()[0]), '='))
+        print(table)
+
+    exit_reasons = results.get('exit_reason_summary', results.get('sell_reason_summary'))
+    table = text_table_exit_reason(exit_reason_stats=exit_reasons,
                                    stake_currency=stake_currency)
     if isinstance(table, str) and len(table) > 0:
-        print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '='))
+        print(' EXIT REASON STATS '.center(len(table.splitlines()[0]), '='))
     print(table)
 
     table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
@@ -636,6 +825,15 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
         print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
     print(table)
 
+    for period in backtest_breakdown:
+        days_breakdown_stats = generate_periodic_breakdown_stats(
+            trade_list=results['trades'], period=period)
+        table = text_table_periodic_breakdown(days_breakdown_stats=days_breakdown_stats,
+                                              stake_currency=stake_currency, period=period)
+        if isinstance(table, str) and len(table) > 0:
+            print(f' {period.upper()} BREAKDOWN '.center(len(table.splitlines()[0]), '='))
+        print(table)
+
     table = text_table_add_metrics(results)
     if isinstance(table, str) and len(table) > 0:
         print(' SUMMARY METRICS '.center(len(table.splitlines()[0]), '='))
@@ -643,6 +841,7 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
 
     if isinstance(table, str) and len(table) > 0:
         print('=' * len(table.splitlines()[0]))
+
     print()
 
 
@@ -650,7 +849,9 @@ def show_backtest_results(config: Dict, backtest_stats: Dict):
     stake_currency = config['stake_currency']
 
     for strategy, results in backtest_stats['strategy'].items():
-        show_backtest_result(strategy, results, stake_currency)
+        show_backtest_result(
+            strategy, results, stake_currency,
+            config.get('backtest_breakdown', []))
 
     if len(backtest_stats['strategy']) > 1:
         # Print Strategy summary table
@@ -662,3 +863,13 @@ def show_backtest_results(config: Dict, backtest_stats: Dict):
         print(table)
         print('=' * len(table.splitlines()[0]))
         print('\nFor more details, please look at the detail tables above')
+
+
+def show_sorted_pairlist(config: Dict, backtest_stats: Dict):
+    if config.get('backtest_show_pair_list', False):
+        for strategy, results in backtest_stats['strategy'].items():
+            print(f"Pairs for Strategy {strategy}: \n[")
+            for result in results['results_per_pair']:
+                if result["key"] != 'TOTAL':
+                    print(f'"{result["key"]}",  // {result["profit_mean"]:.2%}')
+            print("]")
diff --git a/freqtrade/optimize/space/decimalspace.py b/freqtrade/optimize/space/decimalspace.py
index 643999cc1..220502e69 100644
--- a/freqtrade/optimize/space/decimalspace.py
+++ b/freqtrade/optimize/space/decimalspace.py
@@ -7,11 +7,15 @@ class SKDecimal(Integer):
     def __init__(self, low, high, decimals=3, prior="uniform", base=10, transform=None,
                  name=None, dtype=np.int64):
         self.decimals = decimals
-        _low = int(low * pow(10, self.decimals))
-        _high = int(high * pow(10, self.decimals))
+
+        self.pow_dot_one = pow(0.1, self.decimals)
+        self.pow_ten = pow(10, self.decimals)
+
+        _low = int(low * self.pow_ten)
+        _high = int(high * self.pow_ten)
         # trunc to precision to avoid points out of space
-        self.low_orig = round(_low * pow(0.1, self.decimals), self.decimals)
-        self.high_orig = round(_high * pow(0.1, self.decimals), self.decimals)
+        self.low_orig = round(_low * self.pow_dot_one, self.decimals)
+        self.high_orig = round(_high * self.pow_dot_one, self.decimals)
 
         super().__init__(_low, _high, prior, base, transform, name, dtype)
 
@@ -25,9 +29,9 @@ class SKDecimal(Integer):
         return self.low_orig <= point <= self.high_orig
 
     def transform(self, Xt):
-        aa = [int(x * pow(10, self.decimals)) for x in Xt]
-        return super().transform(aa)
+        return super().transform([int(v * self.pow_ten) for v in Xt])
 
     def inverse_transform(self, Xt):
         res = super().inverse_transform(Xt)
-        return [round(x * pow(0.1, self.decimals), self.decimals) for x in res]
+        # equivalent to [round(x * pow(0.1, self.decimals), self.decimals) for x in res]
+        return [int(v) / self.pow_ten for v in res]
diff --git a/freqtrade/persistence/migrations.py b/freqtrade/persistence/migrations.py
index 1839c4130..f020f990c 100644
--- a/freqtrade/persistence/migrations.py
+++ b/freqtrade/persistence/migrations.py
@@ -3,6 +3,8 @@ from typing import List
 
 from sqlalchemy import inspect, text
 
+from freqtrade.exceptions import OperationalException
+
 
 logger = logging.getLogger(__name__)
 
@@ -28,7 +30,38 @@ def get_backup_name(tabs, backup_prefix: str):
     return table_back_name
 
 
-def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, cols: List):
+def get_last_sequence_ids(engine, trade_back_name, order_back_name):
+    order_id: int = None
+    trade_id: int = None
+
+    if engine.name == 'postgresql':
+        with engine.begin() as connection:
+            trade_id = connection.execute(text("select nextval('trades_id_seq')")).fetchone()[0]
+            order_id = connection.execute(text("select nextval('orders_id_seq')")).fetchone()[0]
+        with engine.begin() as connection:
+            connection.execute(text(
+                f"ALTER SEQUENCE orders_id_seq rename to {order_back_name}_id_seq_bak"))
+            connection.execute(text(
+                f"ALTER SEQUENCE trades_id_seq rename to {trade_back_name}_id_seq_bak"))
+    return order_id, trade_id
+
+
+def set_sequence_ids(engine, order_id, trade_id):
+
+    if engine.name == 'postgresql':
+        with engine.begin() as connection:
+            if order_id:
+                connection.execute(text(f"ALTER SEQUENCE orders_id_seq RESTART WITH {order_id}"))
+            if trade_id:
+                connection.execute(text(f"ALTER SEQUENCE trades_id_seq RESTART WITH {trade_id}"))
+
+
+def migrate_trades_and_orders_table(
+        decl_base, inspector, engine,
+        trade_back_name: str, cols: List,
+        order_back_name: str, cols_order: List):
+    base_currency = get_column_def(cols, 'base_currency', 'null')
+    stake_currency = get_column_def(cols, 'stake_currency', 'null')
     fee_open = get_column_def(cols, 'fee_open', 'fee')
     fee_open_cost = get_column_def(cols, 'fee_open_cost', 'null')
     fee_open_currency = get_column_def(cols, 'fee_open_currency', 'null')
@@ -45,9 +78,25 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
     stoploss_last_update = get_column_def(cols, 'stoploss_last_update', 'null')
     max_rate = get_column_def(cols, 'max_rate', '0.0')
     min_rate = get_column_def(cols, 'min_rate', 'null')
-    sell_reason = get_column_def(cols, 'sell_reason', 'null')
+    exit_reason = get_column_def(cols, 'sell_reason', get_column_def(cols, 'exit_reason', 'null'))
     strategy = get_column_def(cols, 'strategy', 'null')
-    buy_tag = get_column_def(cols, 'buy_tag', 'null')
+    enter_tag = get_column_def(cols, 'buy_tag', get_column_def(cols, 'enter_tag', 'null'))
+
+    trading_mode = get_column_def(cols, 'trading_mode', 'null')
+
+    # Leverage Properties
+    leverage = get_column_def(cols, 'leverage', '1.0')
+    liquidation_price = get_column_def(cols, 'liquidation_price',
+                                       get_column_def(cols, 'isolated_liq', 'null'))
+    # sqlite does not support literals for booleans
+    is_short = get_column_def(cols, 'is_short', '0')
+
+    # Margin Properties
+    interest_rate = get_column_def(cols, 'interest_rate', '0.0')
+
+    # Futures properties
+    funding_fees = get_column_def(cols, 'funding_fees', '0.0')
+
     # If ticker-interval existed use that, else null.
     if has_column(cols, 'ticker_interval'):
         timeframe = get_column_def(cols, 'timeframe', 'ticker_interval')
@@ -59,33 +108,46 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
     close_profit_abs = get_column_def(
         cols, 'close_profit_abs',
         f"(amount * close_rate * (1 - {fee_close})) - {open_trade_value}")
-    sell_order_status = get_column_def(cols, 'sell_order_status', 'null')
+    exit_order_status = get_column_def(cols, 'exit_order_status',
+                                       get_column_def(cols, 'sell_order_status', 'null'))
     amount_requested = get_column_def(cols, 'amount_requested', 'amount')
 
     # Schema migration necessary
     with engine.begin() as connection:
-        connection.execute(text(f"alter table trades rename to {table_back_name}"))
+        connection.execute(text(f"alter table trades rename to {trade_back_name}"))
+
     with engine.begin() as connection:
         # drop indexes on backup table in new session
-        for index in inspector.get_indexes(table_back_name):
-            connection.execute(text(f"drop index {index['name']}"))
+        for index in inspector.get_indexes(trade_back_name):
+            if engine.name == 'mysql':
+                connection.execute(text(f"drop index {index['name']} on {trade_back_name}"))
+            else:
+                connection.execute(text(f"drop index {index['name']}"))
+
+    order_id, trade_id = get_last_sequence_ids(engine, trade_back_name, order_back_name)
+
+    drop_orders_table(engine, order_back_name)
+
     # let SQLAlchemy create the schema as required
     decl_base.metadata.create_all(engine)
 
     # Copy data back - following the correct schema
     with engine.begin() as connection:
         connection.execute(text(f"""insert into trades
-            (id, exchange, pair, is_open,
+            (id, exchange, pair, base_currency, stake_currency, is_open,
             fee_open, fee_open_cost, fee_open_currency,
             fee_close, fee_close_cost, fee_close_currency, open_rate,
             open_rate_requested, close_rate, close_rate_requested, close_profit,
             stake_amount, amount, amount_requested, open_date, close_date, open_order_id,
             stop_loss, stop_loss_pct, initial_stop_loss, initial_stop_loss_pct,
             stoploss_order_id, stoploss_last_update,
-            max_rate, min_rate, sell_reason, sell_order_status, strategy, buy_tag,
-            timeframe, open_trade_value, close_profit_abs
+            max_rate, min_rate, exit_reason, exit_order_status, strategy, enter_tag,
+            timeframe, open_trade_value, close_profit_abs,
+            trading_mode, leverage, liquidation_price, is_short,
+            interest_rate, funding_fees
             )
-        select id, lower(exchange), pair,
+        select id, lower(exchange), pair, {base_currency} base_currency,
+            {stake_currency} stake_currency,
             is_open, {fee_open} fee_open, {fee_open_cost} fee_open_cost,
             {fee_open_currency} fee_open_currency, {fee_close} fee_close,
             {fee_close_cost} fee_close_cost, {fee_close_currency} fee_close_currency,
@@ -96,83 +158,88 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
             {initial_stop_loss} initial_stop_loss,
             {initial_stop_loss_pct} initial_stop_loss_pct,
             {stoploss_order_id} stoploss_order_id, {stoploss_last_update} stoploss_last_update,
-            {max_rate} max_rate, {min_rate} min_rate, {sell_reason} sell_reason,
-            {sell_order_status} sell_order_status,
-            {strategy} strategy, {buy_tag} buy_tag, {timeframe} timeframe,
-            {open_trade_value} open_trade_value, {close_profit_abs} close_profit_abs
-            from {table_back_name}
+            {max_rate} max_rate, {min_rate} min_rate,
+            case when {exit_reason} = 'sell_signal' then 'exit_signal'
+                 when {exit_reason} = 'custom_sell' then 'custom_exit'
+                 when {exit_reason} = 'force_sell' then 'force_exit'
+                 when {exit_reason} = 'emergency_sell' then 'emergency_exit'
+                 else {exit_reason}
+            end exit_reason,
+            {exit_order_status} exit_order_status,
+            {strategy} strategy, {enter_tag} enter_tag, {timeframe} timeframe,
+            {open_trade_value} open_trade_value, {close_profit_abs} close_profit_abs,
+            {trading_mode} trading_mode, {leverage} leverage, {liquidation_price} liquidation_price,
+            {is_short} is_short, {interest_rate} interest_rate,
+            {funding_fees} funding_fees
+            from {trade_back_name}
             """))
 
-
-def migrate_open_orders_to_trades(engine):
-    with engine.begin() as connection:
-        connection.execute(text("""
-        insert into orders (ft_trade_id, ft_pair, order_id, ft_order_side, ft_is_open)
-        select id ft_trade_id, pair ft_pair, open_order_id,
-            case when close_rate_requested is null then 'buy'
-            else 'sell' end ft_order_side, 1 ft_is_open
-        from trades
-        where open_order_id is not null
-        union all
-        select id ft_trade_id, pair ft_pair, stoploss_order_id order_id,
-            'stoploss' ft_order_side, 1 ft_is_open
-        from trades
-        where stoploss_order_id is not null
-        """))
+    migrate_orders_table(engine, order_back_name, cols_order)
+    set_sequence_ids(engine, order_id, trade_id)
 
 
-def migrate_orders_table(decl_base, inspector, engine, table_back_name: str, cols: List):
-    # Schema migration necessary
+def drop_orders_table(engine, table_back_name: str):
+    # Drop and recreate orders table as backup
+    # This drops foreign keys, too.
 
     with engine.begin() as connection:
-        connection.execute(text(f"alter table orders rename to {table_back_name}"))
+        connection.execute(text(f"create table {table_back_name} as select * from orders"))
+        connection.execute(text("drop table orders"))
 
-    with engine.begin() as connection:
-        # drop indexes on backup table in new session
-        for index in inspector.get_indexes(table_back_name):
-            connection.execute(text(f"drop index {index['name']}"))
 
-    # let SQLAlchemy create the schema as required
-    decl_base.metadata.create_all(engine)
+def migrate_orders_table(engine, table_back_name: str, cols_order: List):
+
+    ft_fee_base = get_column_def(cols_order, 'ft_fee_base', 'null')
+    average = get_column_def(cols_order, 'average', 'null')
+
+    # sqlite does not support literals for booleans
     with engine.begin() as connection:
         connection.execute(text(f"""
-            insert into orders ( id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id,
+            insert into orders (id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id,
             status, symbol, order_type, side, price, amount, filled, average, remaining, cost,
-            order_date, order_filled_date, order_update_date)
+            order_date, order_filled_date, order_update_date, ft_fee_base)
             select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id,
-            status, symbol, order_type, side, price, amount, filled, null average, remaining, cost,
-            order_date, order_filled_date, order_update_date
+            status, symbol, order_type, side, price, amount, filled, {average} average, remaining,
+            cost, order_date, order_filled_date, order_update_date, {ft_fee_base} ft_fee_base
             from {table_back_name}
             """))
 
 
+def set_sqlite_to_wal(engine):
+    if engine.name == 'sqlite' and str(engine.url) != 'sqlite://':
+        # Set Mode to
+        with engine.begin() as connection:
+            connection.execute(text("PRAGMA journal_mode=wal"))
+
+
 def check_migrate(engine, decl_base, previous_tables) -> None:
     """
     Checks if migration is necessary and migrates if necessary
     """
     inspector = inspect(engine)
 
-    cols = inspector.get_columns('trades')
+    cols_trades = inspector.get_columns('trades')
+    cols_orders = inspector.get_columns('orders')
     tabs = get_table_names_for_table(inspector, 'trades')
     table_back_name = get_backup_name(tabs, 'trades_bak')
+    order_tabs = get_table_names_for_table(inspector, 'orders')
+    order_table_bak_name = get_backup_name(order_tabs, 'orders_bak')
 
-    # Check for latest column
-    if not has_column(cols, 'buy_tag'):
-        logger.info(f'Running database migration for trades - backup: {table_back_name}')
-        migrate_trades_table(decl_base, inspector, engine, table_back_name, cols)
-        # Reread columns - the above recreated the table!
-        inspector = inspect(engine)
-        cols = inspector.get_columns('trades')
+    # Check if migration necessary
+    # Migrates both trades and orders table!
+    # if ('orders' not in previous_tables
+    # or not has_column(cols_orders, 'leverage')):
+    if not has_column(cols_trades, 'base_currency'):
+        logger.info(f"Running database migration for trades - "
+                    f"backup: {table_back_name}, {order_table_bak_name}")
+        migrate_trades_and_orders_table(
+            decl_base, inspector, engine, table_back_name, cols_trades,
+            order_table_bak_name, cols_orders)
 
     if 'orders' not in previous_tables and 'trades' in previous_tables:
-        logger.info('Moving open orders to Orders table.')
-        migrate_open_orders_to_trades(engine)
-    else:
-        cols_order = inspector.get_columns('orders')
+        raise OperationalException(
+            "Your database seems to be very old. "
+            "Please update to freqtrade 2022.3 to migrate this database or "
+            "start with a fresh database.")
 
-        if not has_column(cols_order, 'average'):
-            tabs = get_table_names_for_table(inspector, 'orders')
-            # Empty for now - as there is only one iteration of the orders table so far.
-            table_back_name = get_backup_name(tabs, 'orders_bak')
-
-            migrate_orders_table(decl_base, inspector, engine, table_back_name, cols)
+    set_sqlite_to_wal(engine)
diff --git a/freqtrade/persistence/models.py b/freqtrade/persistence/models.py
index bc5ef961a..a9c07f12c 100644
--- a/freqtrade/persistence/models.py
+++ b/freqtrade/persistence/models.py
@@ -6,7 +6,7 @@ from datetime import datetime, timedelta, timezone
 from decimal import Decimal
 from typing import Any, Dict, List, Optional
 
-from sqlalchemy import (Boolean, Column, DateTime, Float, ForeignKey, Integer, String,
+from sqlalchemy import (Boolean, Column, DateTime, Enum, Float, ForeignKey, Integer, String,
                         create_engine, desc, func, inspect)
 from sqlalchemy.exc import NoSuchModuleError
 from sqlalchemy.orm import Query, declarative_base, relationship, scoped_session, sessionmaker
@@ -14,9 +14,9 @@ from sqlalchemy.pool import StaticPool
 from sqlalchemy.sql.schema import UniqueConstraint
 
 from freqtrade.constants import DATETIME_PRINT_FORMAT, NON_OPEN_EXCHANGE_STATES
-from freqtrade.enums import SellType
+from freqtrade.enums import ExitType, TradingMode
 from freqtrade.exceptions import DependencyException, OperationalException
-from freqtrade.misc import safe_value_fallback
+from freqtrade.leverage import interest
 from freqtrade.persistence.migrations import check_migrate
 
 
@@ -39,6 +39,9 @@ def init_db(db_url: str, clean_open_orders: bool = False) -> None:
     """
     kwargs = {}
 
+    if db_url == 'sqlite:///':
+        raise OperationalException(
+            f'Bad db-url {db_url}. For in-memory database, please use `sqlite://`.')
     if db_url == 'sqlite://':
         kwargs.update({
             'poolclass': StaticPool,
@@ -113,14 +116,15 @@ class Order(_DECL_BASE):
 
     trade = relationship("Trade", back_populates="orders")
 
-    ft_order_side = Column(String(25), nullable=False)
-    ft_pair = Column(String(25), nullable=False)
+    # order_side can only be 'buy', 'sell' or 'stoploss'
+    ft_order_side: str = Column(String(25), nullable=False)
+    ft_pair: str = Column(String(25), nullable=False)
     ft_is_open = Column(Boolean, nullable=False, default=True, index=True)
 
-    order_id = Column(String(255), nullable=False, index=True)
+    order_id: str = Column(String(255), nullable=False, index=True)
     status = Column(String(255), nullable=True)
     symbol = Column(String(25), nullable=True)
-    order_type = Column(String(50), nullable=True)
+    order_type: str = Column(String(50), nullable=True)
     side = Column(String(25), nullable=True)
     price = Column(Float, nullable=True)
     average = Column(Float, nullable=True)
@@ -132,6 +136,29 @@ class Order(_DECL_BASE):
     order_filled_date = Column(DateTime, nullable=True)
     order_update_date = Column(DateTime, nullable=True)
 
+    ft_fee_base = Column(Float, nullable=True)
+
+    @property
+    def order_date_utc(self) -> datetime:
+        """ Order-date with UTC timezoneinfo"""
+        return self.order_date.replace(tzinfo=timezone.utc)
+
+    @property
+    def safe_price(self) -> float:
+        return self.average or self.price
+
+    @property
+    def safe_filled(self) -> float:
+        return self.filled or self.amount or 0.0
+
+    @property
+    def safe_fee_base(self) -> float:
+        return self.ft_fee_base or 0.0
+
+    @property
+    def safe_amount_after_fee(self) -> float:
+        return self.safe_filled - self.safe_fee_base
+
     def __repr__(self):
 
         return (f'Order(id={self.id}, order_id={self.order_id}, trade_id={self.ft_trade_id}, '
@@ -155,6 +182,7 @@ class Order(_DECL_BASE):
         self.average = order.get('average', self.average)
         self.remaining = order.get('remaining', self.remaining)
         self.cost = order.get('cost', self.cost)
+
         if 'timestamp' in order and order['timestamp'] is not None:
             self.order_date = datetime.fromtimestamp(order['timestamp'] / 1000, tz=timezone.utc)
 
@@ -165,6 +193,38 @@ class Order(_DECL_BASE):
                 self.order_filled_date = datetime.now(timezone.utc)
         self.order_update_date = datetime.now(timezone.utc)
 
+    def to_json(self, entry_side: str) -> Dict[str, Any]:
+        return {
+            'pair': self.ft_pair,
+            'order_id': self.order_id,
+            'status': self.status,
+            'amount': self.amount,
+            'average': round(self.average, 8) if self.average else 0,
+            'safe_price': self.safe_price,
+            'cost': self.cost if self.cost else 0,
+            'filled': self.filled,
+            'ft_order_side': self.ft_order_side,
+            'is_open': self.ft_is_open,
+            'order_date': self.order_date.strftime(DATETIME_PRINT_FORMAT)
+            if self.order_date else None,
+            'order_timestamp': int(self.order_date.replace(
+                tzinfo=timezone.utc).timestamp() * 1000) if self.order_date else None,
+            'order_filled_date': self.order_filled_date.strftime(DATETIME_PRINT_FORMAT)
+            if self.order_filled_date else None,
+            'order_filled_timestamp': int(self.order_filled_date.replace(
+                tzinfo=timezone.utc).timestamp() * 1000) if self.order_filled_date else None,
+            'order_type': self.order_type,
+            'price': self.price,
+            'ft_is_entry': self.ft_order_side == entry_side,
+            'remaining': self.remaining,
+        }
+
+    def close_bt_order(self, close_date: datetime):
+        self.order_filled_date = close_date
+        self.filled = self.amount
+        self.status = 'closed'
+        self.ft_is_open = False
+
     @staticmethod
     def update_orders(orders: List['Order'], order: Dict[str, Any]):
         """
@@ -195,6 +255,8 @@ class Order(_DECL_BASE):
     @staticmethod
     def get_open_orders() -> List['Order']:
         """
+        Retrieve open orders from the database
+        :return: List of open orders
         """
         return Order.query.filter(Order.ft_is_open.is_(True)).all()
 
@@ -217,6 +279,8 @@ class LocalTrade():
 
     exchange: str = ''
     pair: str = ''
+    base_currency: str = ''
+    stake_currency: str = ''
     is_open: bool = True
     fee_open: float = 0.0
     fee_open_cost: Optional[float] = None
@@ -245,7 +309,7 @@ class LocalTrade():
     # absolute value of the initial stop loss
     initial_stop_loss: float = 0.0
     # percentage value of the initial stop loss
-    initial_stop_loss_pct: float = 0.0
+    initial_stop_loss_pct: Optional[float] = None
     # stoploss order id which is on exchange
     stoploss_order_id: Optional[str] = None
     # last update time of the stoploss order on exchange
@@ -254,22 +318,51 @@ class LocalTrade():
     max_rate: float = 0.0
     # Lowest price reached
     min_rate: float = 0.0
-    sell_reason: str = ''
-    sell_order_status: str = ''
+    exit_reason: str = ''
+    exit_order_status: str = ''
     strategy: str = ''
-    buy_tag: Optional[str] = None
+    enter_tag: Optional[str] = None
     timeframe: Optional[int] = None
 
-    def __init__(self, **kwargs):
-        for key in kwargs:
-            setattr(self, key, kwargs[key])
-        self.recalc_open_trade_value()
+    trading_mode: TradingMode = TradingMode.SPOT
 
-    def __repr__(self):
-        open_since = self.open_date.strftime(DATETIME_PRINT_FORMAT) if self.is_open else 'closed'
+    # Leverage trading properties
+    liquidation_price: Optional[float] = None
+    is_short: bool = False
+    leverage: float = 1.0
 
-        return (f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
-                f'open_rate={self.open_rate:.8f}, open_since={open_since})')
+    # Margin trading properties
+    interest_rate: float = 0.0
+
+    # Futures properties
+    funding_fees: Optional[float] = None
+
+    @property
+    def buy_tag(self) -> Optional[str]:
+        """
+        Compatibility between buy_tag (old) and enter_tag (new)
+        Consider buy_tag deprecated
+        """
+        return self.enter_tag
+
+    @property
+    def has_no_leverage(self) -> bool:
+        """Returns true if this is a non-leverage, non-short trade"""
+        return ((self.leverage == 1.0 or self.leverage is None) and not self.is_short)
+
+    @property
+    def borrowed(self) -> float:
+        """
+            The amount of currency borrowed from the exchange for leverage trades
+            If a long trade, the amount is in base currency
+            If a short trade, the amount is in the other currency being traded
+        """
+        if self.has_no_leverage:
+            return 0.0
+        elif not self.is_short:
+            return (self.amount * self.open_rate) * ((self.leverage - 1) / self.leverage)
+        else:
+            return self.amount
 
     @property
     def open_date_utc(self):
@@ -279,17 +372,89 @@ class LocalTrade():
     def close_date_utc(self):
         return self.close_date.replace(tzinfo=timezone.utc)
 
+    @property
+    def enter_side(self) -> str:
+        """ DEPRECATED, please use entry_side instead"""
+        # TODO: Please remove me after 2022.5
+        return self.entry_side
+
+    @property
+    def entry_side(self) -> str:
+        if self.is_short:
+            return "sell"
+        else:
+            return "buy"
+
+    @property
+    def exit_side(self) -> str:
+        if self.is_short:
+            return "buy"
+        else:
+            return "sell"
+
+    @property
+    def trade_direction(self) -> str:
+        if self.is_short:
+            return "short"
+        else:
+            return "long"
+
+    @property
+    def safe_base_currency(self) -> str:
+        """
+        Compatibility layer for asset - which can be empty for old trades.
+        """
+        try:
+            return self.base_currency or self.pair.split('/')[0]
+        except IndexError:
+            return ''
+
+    @property
+    def safe_quote_currency(self) -> str:
+        """
+        Compatibility layer for asset - which can be empty for old trades.
+        """
+        try:
+            return self.stake_currency or self.pair.split('/')[1].split(':')[0]
+        except IndexError:
+            return ''
+
+    def __init__(self, **kwargs):
+        for key in kwargs:
+            setattr(self, key, kwargs[key])
+        self.recalc_open_trade_value()
+        if self.trading_mode == TradingMode.MARGIN and self.interest_rate is None:
+            raise OperationalException(
+                f"{self.trading_mode.value} trading requires param interest_rate on trades")
+
+    def __repr__(self):
+        open_since = self.open_date.strftime(DATETIME_PRINT_FORMAT) if self.is_open else 'closed'
+        leverage = self.leverage or 1.0
+        is_short = self.is_short or False
+
+        return (
+            f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
+            f'is_short={is_short}, leverage={leverage}, '
+            f'open_rate={self.open_rate:.8f}, open_since={open_since})'
+        )
+
     def to_json(self) -> Dict[str, Any]:
+        filled_orders = self.select_filled_orders()
+        orders = [order.to_json(self.entry_side) for order in filled_orders]
+
         return {
             'trade_id': self.id,
             'pair': self.pair,
+            'base_currency': self.safe_base_currency,
+            'quote_currency': self.safe_quote_currency,
             'is_open': self.is_open,
             'exchange': self.exchange,
             'amount': round(self.amount, 8),
             'amount_requested': round(self.amount_requested, 8) if self.amount_requested else None,
             'stake_amount': round(self.stake_amount, 8),
             'strategy': self.strategy,
-            'buy_tag': self.buy_tag,
+            'buy_tag': self.enter_tag,
+            'enter_tag': self.enter_tag,
             'timeframe': self.timeframe,
 
             'fee_open': self.fee_open,
@@ -324,8 +489,9 @@ class LocalTrade():
             'profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None,
             'profit_abs': self.close_profit_abs,
 
-            'sell_reason': self.sell_reason,
-            'sell_order_status': self.sell_order_status,
+            'sell_reason': self.exit_reason,  # Deprecated
+            'exit_reason': self.exit_reason,
+            'exit_order_status': self.exit_order_status,
             'stop_loss_abs': self.stop_loss,
             'stop_loss_ratio': self.stop_loss_pct if self.stop_loss_pct else None,
             'stop_loss_pct': (self.stop_loss_pct * 100) if self.stop_loss_pct else None,
@@ -342,7 +508,14 @@ class LocalTrade():
             'min_rate': self.min_rate,
             'max_rate': self.max_rate,
 
+            'leverage': self.leverage,
+            'interest_rate': self.interest_rate,
+            'liquidation_price': self.liquidation_price,
+            'is_short': self.is_short,
+            'trading_mode': self.trading_mode,
+            'funding_fees': self.funding_fees,
             'open_order_id': self.open_order_id,
+            'orders': orders,
         }
 
     @staticmethod
@@ -361,10 +534,33 @@ class LocalTrade():
         self.max_rate = max(current_price, self.max_rate or self.open_rate)
         self.min_rate = min(current_price_low, self.min_rate or self.open_rate)
 
-    def _set_new_stoploss(self, new_loss: float, stoploss: float):
-        """Assign new stop value"""
-        self.stop_loss = new_loss
-        self.stop_loss_pct = -1 * abs(stoploss)
+    def set_isolated_liq(self, liquidation_price: Optional[float]):
+        """
+        Method you should use to set self.liquidation price.
+        Assures stop_loss is not passed the liquidation price
+        """
+        if not liquidation_price:
+            return
+        self.liquidation_price = liquidation_price
+
+    def _set_stop_loss(self, stop_loss: float, percent: float):
+        """
+        Method you should use to set self.stop_loss.
+        Assures stop_loss is not passed the liquidation price
+        """
+        if self.liquidation_price is not None:
+            if self.is_short:
+                sl = min(stop_loss, self.liquidation_price)
+            else:
+                sl = max(stop_loss, self.liquidation_price)
+        else:
+            sl = stop_loss
+
+        if not self.stop_loss:
+            self.initial_stop_loss = sl
+        self.stop_loss = sl
+
+        self.stop_loss_pct = -1 * abs(percent)
         self.stoploss_last_update = datetime.utcnow()
 
     def adjust_stop_loss(self, current_price: float, stoploss: float,
@@ -380,65 +576,85 @@ class LocalTrade():
             # Don't modify if called with initial and nothing to do
             return
 
-        new_loss = float(current_price * (1 - abs(stoploss)))
+        leverage = self.leverage or 1.0
+        if self.is_short:
+            new_loss = float(current_price * (1 + abs(stoploss / leverage)))
+            # If trading with leverage, don't set the stoploss below the liquidation price
+            if self.liquidation_price:
+                new_loss = min(self.liquidation_price, new_loss)
+        else:
+            new_loss = float(current_price * (1 - abs(stoploss / leverage)))
+            # If trading with leverage, don't set the stoploss below the liquidation price
+            if self.liquidation_price:
+                new_loss = max(self.liquidation_price, new_loss)
 
         # no stop loss assigned yet
-        if not self.stop_loss:
+        if self.initial_stop_loss_pct is None:
             logger.debug(f"{self.pair} - Assigning new stoploss...")
-            self._set_new_stoploss(new_loss, stoploss)
+            self._set_stop_loss(new_loss, stoploss)
             self.initial_stop_loss = new_loss
             self.initial_stop_loss_pct = -1 * abs(stoploss)
 
         # evaluate if the stop loss needs to be updated
         else:
-            if new_loss > self.stop_loss:  # stop losses only walk up, never down!
+
+            higher_stop = new_loss > self.stop_loss
+            lower_stop = new_loss < self.stop_loss
+
+            # stop losses only walk up, never down!,
+            #   ? But adding more to a leveraged trade would create a lower liquidation price,
+            #   ? decreasing the minimum stoploss
+            if (higher_stop and not self.is_short) or (lower_stop and self.is_short):
                 logger.debug(f"{self.pair} - Adjusting stoploss...")
-                self._set_new_stoploss(new_loss, stoploss)
+                self._set_stop_loss(new_loss, stoploss)
             else:
                 logger.debug(f"{self.pair} - Keeping current stoploss...")
 
         logger.debug(
             f"{self.pair} - Stoploss adjusted. current_price={current_price:.8f}, "
-            f"open_rate={self.open_rate:.8f}, max_rate={self.max_rate:.8f}, "
+            f"open_rate={self.open_rate:.8f}, max_rate={self.max_rate or self.open_rate:.8f}, "
             f"initial_stop_loss={self.initial_stop_loss:.8f}, "
             f"stop_loss={self.stop_loss:.8f}. "
             f"Trailing stoploss saved us: "
             f"{float(self.stop_loss) - float(self.initial_stop_loss):.8f}.")
 
-    def update(self, order: Dict) -> None:
+    def update_trade(self, order: Order) -> None:
         """
         Updates this entity with amount and actual open/close rates.
         :param order: order retrieved by exchange.fetch_order()
         :return: None
         """
-        order_type = order['type']
+
         # Ignore open and cancelled orders
-        if order['status'] == 'open' or safe_value_fallback(order, 'average', 'price') is None:
+        if order.status == 'open' or order.safe_price is None:
             return
 
-        logger.info('Updating trade (id=%s) ...', self.id)
+        logger.info(f'Updating trade (id={self.id}) ...')
 
-        if order_type in ('market', 'limit') and order['side'] == 'buy':
+        if order.ft_order_side == self.entry_side:
             # Update open rate and actual amount
-            self.open_rate = float(safe_value_fallback(order, 'average', 'price'))
-            self.amount = float(safe_value_fallback(order, 'filled', 'amount'))
-            self.recalc_open_trade_value()
+            self.open_rate = order.safe_price
+            self.amount = order.safe_amount_after_fee
             if self.is_open:
-                logger.info(f'{order_type.upper()}_BUY has been fulfilled for {self}.')
+                payment = "SELL" if self.is_short else "BUY"
+                logger.info(f'{order.order_type.upper()}_{payment} has been fulfilled for {self}.')
             self.open_order_id = None
-        elif order_type in ('market', 'limit') and order['side'] == 'sell':
+            self.recalc_trade_from_orders()
+        elif order.ft_order_side == self.exit_side:
             if self.is_open:
-                logger.info(f'{order_type.upper()}_SELL has been fulfilled for {self}.')
-            self.close(safe_value_fallback(order, 'average', 'price'))
-        elif order_type in ('stop_loss_limit', 'stop-loss', 'stop-loss-limit', 'stop'):
+                payment = "BUY" if self.is_short else "SELL"
+                # * On margin shorts, you buy a little bit more than the amount (amount + interest)
+                logger.info(f'{order.order_type.upper()}_{payment} has been fulfilled for {self}.')
+            self.close(order.safe_price)
+        elif order.ft_order_side == 'stoploss':
             self.stoploss_order_id = None
             self.close_rate_requested = self.stop_loss
-            self.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
+            self.exit_reason = ExitType.STOPLOSS_ON_EXCHANGE.value
             if self.is_open:
-                logger.info(f'{order_type.upper()} is hit for {self}.')
-            self.close(safe_value_fallback(order, 'average', 'price'))
+                logger.info(f'{order.order_type.upper()} is hit for {self}.')
+            self.close(order.safe_price)
         else:
-            raise ValueError(f'Unknown order type: {order_type}')
+            raise ValueError(f'Unknown order type: {order.order_type}')
         Trade.commit()
 
     def close(self, rate: float, *, show_msg: bool = True) -> None:
@@ -447,11 +663,11 @@ class LocalTrade():
         and marks trade as closed
         """
         self.close_rate = rate
+        self.close_date = self.close_date or datetime.utcnow()
         self.close_profit = self.calc_profit_ratio()
         self.close_profit_abs = self.calc_profit()
-        self.close_date = self.close_date or datetime.utcnow()
         self.is_open = False
-        self.sell_order_status = 'closed'
+        self.exit_order_status = 'closed'
         self.open_order_id = None
         if show_msg:
             logger.info(
@@ -464,14 +680,14 @@ class LocalTrade():
         """
         Update Fee parameters. Only acts once per side
         """
-        if side == 'buy' and self.fee_open_currency is None:
+        if self.entry_side == side and self.fee_open_currency is None:
             self.fee_open_cost = fee_cost
             self.fee_open_currency = fee_currency
             if fee_rate is not None:
                 self.fee_open = fee_rate
                 # Assume close-fee will fall into the same fee category and take an educated guess
                 self.fee_close = fee_rate
-        elif side == 'sell' and self.fee_close_currency is None:
+        elif self.exit_side == side and self.fee_close_currency is None:
             self.fee_close_cost = fee_cost
             self.fee_close_currency = fee_currency
             if fee_rate is not None:
@@ -481,9 +697,9 @@ class LocalTrade():
         """
         Verify if this side (buy / sell) has already been updated
         """
-        if side == 'buy':
+        if self.entry_side == side:
             return self.fee_open_currency is not None
-        elif side == 'sell':
+        elif self.exit_side == side:
             return self.fee_close_currency is not None
         else:
             return False
@@ -491,82 +707,223 @@ class LocalTrade():
     def update_order(self, order: Dict) -> None:
         Order.update_orders(self.orders, order)
 
+    def get_exit_order_count(self) -> int:
+        """
+        Get amount of failed exiting orders
+        assumes full exits.
+        """
+        return len([o for o in self.orders if o.ft_order_side == self.exit_side])
+
     def _calc_open_trade_value(self) -> float:
         """
         Calculate the open_rate including open_fee.
         :return: Price in of the open trade incl. Fees
         """
-        buy_trade = Decimal(self.amount) * Decimal(self.open_rate)
-        fees = buy_trade * Decimal(self.fee_open)
-        return float(buy_trade + fees)
+        open_trade = Decimal(self.amount) * Decimal(self.open_rate)
+        fees = open_trade * Decimal(self.fee_open)
+        if self.is_short:
+            return float(open_trade - fees)
+        else:
+            return float(open_trade + fees)
 
     def recalc_open_trade_value(self) -> None:
         """
         Recalculate open_trade_value.
-        Must be called whenever open_rate or fee_open is changed.
+        Must be called whenever open_rate, fee_open or is_short is changed.
         """
         self.open_trade_value = self._calc_open_trade_value()
 
+    def calculate_interest(self, interest_rate: Optional[float] = None) -> Decimal:
+        """
+        :param interest_rate: interest_charge for borrowing this coin(optional).
+        If interest_rate is not set self.interest_rate will be used
+        """
+        zero = Decimal(0.0)
+        # If nothing was borrowed
+        if self.trading_mode != TradingMode.MARGIN or self.has_no_leverage:
+            return zero
+
+        open_date = self.open_date.replace(tzinfo=None)
+        now = (self.close_date or datetime.now(timezone.utc)).replace(tzinfo=None)
+        sec_per_hour = Decimal(3600)
+        total_seconds = Decimal((now - open_date).total_seconds())
+        hours = total_seconds / sec_per_hour or zero
+
+        rate = Decimal(interest_rate or self.interest_rate)
+        borrowed = Decimal(self.borrowed)
+
+        return interest(exchange_name=self.exchange, borrowed=borrowed, rate=rate, hours=hours)
+
+    def _calc_base_close(self, amount: Decimal, rate: Optional[float] = None,
+                         fee: Optional[float] = None) -> Decimal:
+
+        close_trade = Decimal(amount) * Decimal(rate or self.close_rate)  # type: ignore
+        fees = close_trade * Decimal(fee or self.fee_close)
+
+        if self.is_short:
+            return close_trade + fees
+        else:
+            return close_trade - fees
+
     def calc_close_trade_value(self, rate: Optional[float] = None,
-                               fee: Optional[float] = None) -> float:
+                               fee: Optional[float] = None,
+                               interest_rate: Optional[float] = None) -> float:
         """
         Calculate the close_rate including fee
         :param fee: fee to use on the close rate (optional).
             If rate is not set self.fee will be used
         :param rate: rate to compare with (optional).
             If rate is not set self.close_rate will be used
+        :param interest_rate: interest_charge for borrowing this coin (optional).
+            If interest_rate is not set self.interest_rate will be used
         :return: Price in BTC of the open trade
         """
         if rate is None and not self.close_rate:
             return 0.0
 
-        sell_trade = Decimal(self.amount) * Decimal(rate or self.close_rate)  # type: ignore
-        fees = sell_trade * Decimal(fee or self.fee_close)
-        return float(sell_trade - fees)
+        amount = Decimal(self.amount)
+        trading_mode = self.trading_mode or TradingMode.SPOT
+
+        if trading_mode == TradingMode.SPOT:
+            return float(self._calc_base_close(amount, rate, fee))
+
+        elif (trading_mode == TradingMode.MARGIN):
+
+            total_interest = self.calculate_interest(interest_rate)
+
+            if self.is_short:
+                amount = amount + total_interest
+                return float(self._calc_base_close(amount, rate, fee))
+            else:
+                # Currency already owned for longs, no need to purchase
+                return float(self._calc_base_close(amount, rate, fee) - total_interest)
+
+        elif (trading_mode == TradingMode.FUTURES):
+            funding_fees = self.funding_fees or 0.0
+            # Positive funding_fees -> Trade has gained from fees.
+            # Negative funding_fees -> Trade had to pay the fees.
+            if self.is_short:
+                return float(self._calc_base_close(amount, rate, fee)) - funding_fees
+            else:
+                return float(self._calc_base_close(amount, rate, fee)) + funding_fees
+        else:
+            raise OperationalException(
+                f"{self.trading_mode.value} trading is not yet available using freqtrade")
 
     def calc_profit(self, rate: Optional[float] = None,
-                    fee: Optional[float] = None) -> float:
+                    fee: Optional[float] = None,
+                    interest_rate: Optional[float] = None) -> float:
         """
         Calculate the absolute profit in stake currency between Close and Open trade
         :param fee: fee to use on the close rate (optional).
-            If rate is not set self.fee will be used
+            If fee is not set self.fee will be used
         :param rate: close rate to compare with (optional).
             If rate is not set self.close_rate will be used
+        :param interest_rate: interest_charge for borrowing this coin (optional).
+            If interest_rate is not set self.interest_rate will be used
         :return:  profit in stake currency as float
         """
         close_trade_value = self.calc_close_trade_value(
             rate=(rate or self.close_rate),
-            fee=(fee or self.fee_close)
+            fee=(fee or self.fee_close),
+            interest_rate=(interest_rate or self.interest_rate)
         )
-        profit = close_trade_value - self.open_trade_value
+
+        if self.is_short:
+            profit = self.open_trade_value - close_trade_value
+        else:
+            profit = close_trade_value - self.open_trade_value
         return float(f"{profit:.8f}")
 
     def calc_profit_ratio(self, rate: Optional[float] = None,
-                          fee: Optional[float] = None) -> float:
+                          fee: Optional[float] = None,
+                          interest_rate: Optional[float] = None) -> float:
         """
         Calculates the profit as ratio (including fee).
         :param rate: rate to compare with (optional).
             If rate is not set self.close_rate will be used
         :param fee: fee to use on the close rate (optional).
+        :param interest_rate: interest_charge for borrowing this coin (optional).
+            If interest_rate is not set self.interest_rate will be used
         :return: profit ratio as float
         """
         close_trade_value = self.calc_close_trade_value(
             rate=(rate or self.close_rate),
-            fee=(fee or self.fee_close)
+            fee=(fee or self.fee_close),
+            interest_rate=(interest_rate or self.interest_rate)
         )
-        if self.open_trade_value == 0.0:
+
+        short_close_zero = (self.is_short and close_trade_value == 0.0)
+        long_close_zero = (not self.is_short and self.open_trade_value == 0.0)
+        leverage = self.leverage or 1.0
+
+        if (short_close_zero or long_close_zero):
             return 0.0
-        profit_ratio = (close_trade_value / self.open_trade_value) - 1
+        else:
+            if self.is_short:
+                profit_ratio = (1 - (close_trade_value / self.open_trade_value)) * leverage
+            else:
+                profit_ratio = ((close_trade_value / self.open_trade_value) - 1) * leverage
+
         return float(f"{profit_ratio:.8f}")
 
-    def select_order(self, order_side: str, is_open: Optional[bool]) -> Optional[Order]:
+    def recalc_trade_from_orders(self):
+        # We need at least 2 entry orders for averaging amounts and rates.
+        # TODO: this condition could probably be removed
+        if len(self.select_filled_orders(self.entry_side)) < 2:
+            self.stake_amount = self.amount * self.open_rate / self.leverage
+
+            # Just in case, still recalc open trade value
+            self.recalc_open_trade_value()
+            return
+
+        total_amount = 0.0
+        total_stake = 0.0
+        for o in self.orders:
+            if (o.ft_is_open or
+                    (o.ft_order_side != self.entry_side) or
+                    (o.status not in NON_OPEN_EXCHANGE_STATES)):
+                continue
+
+            tmp_amount = o.safe_amount_after_fee
+            tmp_price = o.average or o.price
+            if o.filled is not None:
+                tmp_amount = o.filled
+            if tmp_amount > 0.0 and tmp_price is not None:
+                total_amount += tmp_amount
+                total_stake += tmp_price * tmp_amount
+
+        if total_amount > 0:
+            # Leverage not updated, as we don't allow changing leverage through DCA at the moment.
+            self.open_rate = total_stake / total_amount
+            self.stake_amount = total_stake / (self.leverage or 1.0)
+            self.amount = total_amount
+            self.fee_open_cost = self.fee_open * self.stake_amount
+            self.recalc_open_trade_value()
+            if self.stop_loss_pct is not None and self.open_rate is not None:
+                self.adjust_stop_loss(self.open_rate, self.stop_loss_pct)
+
+    def select_order_by_order_id(self, order_id: str) -> Optional[Order]:
+        """
+        Finds order object by Order id.
+        :param order_id: Exchange order id
+        """
+        for o in self.orders:
+            if o.order_id == order_id:
+                return o
+        return None
+
+    def select_order(
+            self, order_side: str = None, is_open: Optional[bool] = None) -> Optional[Order]:
         """
         Finds latest order for this orderside and status
-        :param order_side: Side of the order (either 'buy' or 'sell')
+        :param order_side: ft_order_side of the order (either 'buy', 'sell' or 'stoploss')
         :param is_open: Only search for open orders?
         :return: latest Order object if it exists, else None
         """
-        orders = [o for o in self.orders if o.side == order_side]
+        orders = self.orders
+        if order_side:
+            orders = [o for o in self.orders if o.ft_order_side == order_side]
         if is_open is not None:
             orders = [o for o in orders if o.ft_is_open == is_open]
         if len(orders) > 0:
@@ -574,6 +931,58 @@ class LocalTrade():
         else:
             return None
 
+    def select_filled_orders(self, order_side: Optional[str] = None) -> List['Order']:
+        """
+        Finds filled orders for this orderside.
+        :param order_side: Side of the order (either 'buy', 'sell', or None)
+        :return: array of Order objects
+        """
+        return [o for o in self.orders if ((o.ft_order_side == order_side) or (order_side is None))
+                and o.ft_is_open is False and
+                (o.filled or 0) > 0 and
+                o.status in NON_OPEN_EXCHANGE_STATES]
+
+    @property
+    def nr_of_successful_entries(self) -> int:
+        """
+        Helper function to count the number of entry orders that have been filled.
+        :return: int count of entry orders that have been filled for this trade.
+        """
+
+        return len(self.select_filled_orders(self.entry_side))
+
+    @property
+    def nr_of_successful_exits(self) -> int:
+        """
+        Helper function to count the number of exit orders that have been filled.
+        :return: int count of exit orders that have been filled for this trade.
+        """
+        return len(self.select_filled_orders(self.exit_side))
+
+    @property
+    def nr_of_successful_buys(self) -> int:
+        """
+        Helper function to count the number of buy orders that have been filled.
+        WARNING: Please use nr_of_successful_entries for short support.
+        :return: int count of buy orders that have been filled for this trade.
+        """
+
+        return len(self.select_filled_orders('buy'))
+
+    @property
+    def nr_of_successful_sells(self) -> int:
+        """
+        Helper function to count the number of sell orders that have been filled.
+        WARNING: Please use nr_of_successful_exits for short support.
+        :return: int count of sell orders that have been filled for this trade.
+        """
+        return len(self.select_filled_orders('sell'))
+
+    @property
+    def sell_reason(self) -> str:
+        """ DEPRECATED! Please use exit_reason instead."""
+        return self.exit_reason
+
     @staticmethod
     def get_trades_proxy(*, pair: str = None, is_open: bool = None,
                          open_date: datetime = None, close_date: datetime = None,
@@ -644,6 +1053,7 @@ class LocalTrade():
                 logger.info(f"Stoploss for {trade} needs adjustment...")
                 # Force reset of stoploss
                 trade.stop_loss = None
+                trade.initial_stop_loss_pct = None
                 trade.adjust_stop_loss(trade.open_rate, desired_stoploss)
                 logger.info(f"New stoploss: {trade.stop_loss}.")
 
@@ -661,10 +1071,12 @@ class Trade(_DECL_BASE, LocalTrade):
 
     id = Column(Integer, primary_key=True)
 
-    orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan")
+    orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan", lazy="joined")
 
     exchange = Column(String(25), nullable=False)
     pair = Column(String(25), nullable=False, index=True)
+    base_currency = Column(String(25), nullable=True)
+    stake_currency = Column(String(25), nullable=True)
     is_open = Column(Boolean, nullable=False, default=True, index=True)
     fee_open = Column(Float, nullable=False, default=0.0)
     fee_open_cost = Column(Float, nullable=True)
@@ -672,11 +1084,11 @@ class Trade(_DECL_BASE, LocalTrade):
     fee_close = Column(Float, nullable=False, default=0.0)
     fee_close_cost = Column(Float, nullable=True)
     fee_close_currency = Column(String(25), nullable=True)
-    open_rate = Column(Float)
+    open_rate: float = Column(Float)
     open_rate_requested = Column(Float)
     # open_trade_value - calculated via _calc_open_trade_value
     open_trade_value = Column(Float)
-    close_rate = Column(Float)
+    close_rate: Optional[float] = Column(Float)
     close_rate_requested = Column(Float)
     close_profit = Column(Float)
     close_profit_abs = Column(Float)
@@ -702,12 +1114,25 @@ class Trade(_DECL_BASE, LocalTrade):
     max_rate = Column(Float, nullable=True, default=0.0)
     # Lowest price reached
     min_rate = Column(Float, nullable=True)
-    sell_reason = Column(String(100), nullable=True)
-    sell_order_status = Column(String(100), nullable=True)
+    exit_reason = Column(String(100), nullable=True)
+    exit_order_status = Column(String(100), nullable=True)
     strategy = Column(String(100), nullable=True)
-    buy_tag = Column(String(100), nullable=True)
+    enter_tag = Column(String(100), nullable=True)
     timeframe = Column(Integer, nullable=True)
 
+    trading_mode = Column(Enum(TradingMode), nullable=True)
+
+    # Leverage trading properties
+    leverage = Column(Float, nullable=True, default=1.0)
+    is_short = Column(Boolean, nullable=False, default=False)
+    liquidation_price = Column(Float, nullable=True)
+
+    # Margin Trading Properties
+    interest_rate = Column(Float, nullable=False, default=0.0)
+
+    # Futures properties
+    funding_fees = Column(Float, nullable=True, default=None)
+
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
         self.recalc_open_trade_value()
@@ -775,7 +1200,7 @@ class Trade(_DECL_BASE, LocalTrade):
             return Trade.query
 
     @staticmethod
-    def get_open_order_trades():
+    def get_open_order_trades() -> List['Trade']:
         """
         Returns all open trades
         NOTE: Not supported in Backtesting.
@@ -794,7 +1219,7 @@ class Trade(_DECL_BASE, LocalTrade):
                                  ]).all()
 
     @staticmethod
-    def get_sold_trades_without_assigned_fees():
+    def get_closed_trades_without_assigned_fees():
         """
         Returns all closed trades which don't have fees set correctly
         NOTE: Not supported in Backtesting.
@@ -853,13 +1278,132 @@ class Trade(_DECL_BASE, LocalTrade):
         return [
             {
                 'pair': pair,
-                'profit': profit,
+                'profit_ratio': profit,
+                'profit': round(profit * 100, 2),  # Compatibility mode
+                'profit_pct': round(profit * 100, 2),
                 'profit_abs': profit_abs,
                 'count': count
             }
             for pair, profit, profit_abs, count in pair_rates
         ]
 
+    @staticmethod
+    def get_enter_tag_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
+        """
+        Returns List of dicts containing all Trades, based on buy tag performance
+        Can either be average for all pairs or a specific pair provided
+        NOTE: Not supported in Backtesting.
+        """
+
+        filters = [Trade.is_open.is_(False)]
+        if(pair is not None):
+            filters.append(Trade.pair == pair)
+
+        enter_tag_perf = Trade.query.with_entities(
+            Trade.enter_tag,
+            func.sum(Trade.close_profit).label('profit_sum'),
+            func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
+            func.count(Trade.pair).label('count')
+        ).filter(*filters)\
+            .group_by(Trade.enter_tag) \
+            .order_by(desc('profit_sum_abs')) \
+            .all()
+
+        return [
+            {
+                'enter_tag': enter_tag if enter_tag is not None else "Other",
+                'profit_ratio': profit,
+                'profit_pct': round(profit * 100, 2),
+                'profit_abs': profit_abs,
+                'count': count
+            }
+            for enter_tag, profit, profit_abs, count in enter_tag_perf
+        ]
+
+    @staticmethod
+    def get_exit_reason_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
+        """
+        Returns List of dicts containing all Trades, based on exit reason performance
+        Can either be average for all pairs or a specific pair provided
+        NOTE: Not supported in Backtesting.
+        """
+
+        filters = [Trade.is_open.is_(False)]
+        if(pair is not None):
+            filters.append(Trade.pair == pair)
+
+        sell_tag_perf = Trade.query.with_entities(
+            Trade.exit_reason,
+            func.sum(Trade.close_profit).label('profit_sum'),
+            func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
+            func.count(Trade.pair).label('count')
+        ).filter(*filters)\
+            .group_by(Trade.exit_reason) \
+            .order_by(desc('profit_sum_abs')) \
+            .all()
+
+        return [
+            {
+                'exit_reason': exit_reason if exit_reason is not None else "Other",
+                'profit_ratio': profit,
+                'profit_pct': round(profit * 100, 2),
+                'profit_abs': profit_abs,
+                'count': count
+            }
+            for exit_reason, profit, profit_abs, count in sell_tag_perf
+        ]
+
+    @staticmethod
+    def get_mix_tag_performance(pair: Optional[str]) -> List[Dict[str, Any]]:
+        """
+        Returns List of dicts containing all Trades, based on entry_tag + exit_reason performance
+        Can either be average for all pairs or a specific pair provided
+        NOTE: Not supported in Backtesting.
+        """
+
+        filters = [Trade.is_open.is_(False)]
+        if(pair is not None):
+            filters.append(Trade.pair == pair)
+
+        mix_tag_perf = Trade.query.with_entities(
+            Trade.id,
+            Trade.enter_tag,
+            Trade.exit_reason,
+            func.sum(Trade.close_profit).label('profit_sum'),
+            func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
+            func.count(Trade.pair).label('count')
+        ).filter(*filters)\
+            .group_by(Trade.id) \
+            .order_by(desc('profit_sum_abs')) \
+            .all()
+
+        return_list: List[Dict] = []
+        for id, enter_tag, exit_reason, profit, profit_abs, count in mix_tag_perf:
+            enter_tag = enter_tag if enter_tag is not None else "Other"
+            exit_reason = exit_reason if exit_reason is not None else "Other"
+
+            if(exit_reason is not None and enter_tag is not None):
+                mix_tag = enter_tag + " " + exit_reason
+                i = 0
+                if not any(item["mix_tag"] == mix_tag for item in return_list):
+                    return_list.append({'mix_tag': mix_tag,
+                                        'profit': profit,
+                                        'profit_pct': round(profit * 100, 2),
+                                        'profit_abs': profit_abs,
+                                        'count': count})
+                else:
+                    while i < len(return_list):
+                        if return_list[i]["mix_tag"] == mix_tag:
+                            return_list[i] = {
+                                'mix_tag': mix_tag,
+                                'profit': profit + return_list[i]["profit"],
+                                'profit_pct': round(profit + return_list[i]["profit"] * 100, 2),
+                                'profit_abs': profit_abs + return_list[i]["profit_abs"],
+                                'count': 1 + return_list[i]["count"]}
+                        i += 1
+
+        return return_list
+
     @staticmethod
     def get_best_pair(start_date: datetime = datetime.fromtimestamp(0)):
         """
@@ -896,7 +1440,7 @@ class PairLock(_DECL_BASE):
         lock_time = self.lock_time.strftime(DATETIME_PRINT_FORMAT)
         lock_end_time = self.lock_end_time.strftime(DATETIME_PRINT_FORMAT)
         return (f'PairLock(id={self.id}, pair={self.pair}, lock_time={lock_time}, '
-                f'lock_end_time={lock_end_time})')
+                f'lock_end_time={lock_end_time}, reason={self.reason}, active={self.active})')
 
     @staticmethod
     def query_pair_locks(pair: Optional[str], now: datetime) -> Query:
@@ -905,7 +1449,6 @@ class PairLock(_DECL_BASE):
         :param pair: Pair to check for. Returns all current locks if pair is empty
         :param now: Datetime object (generated via datetime.now(timezone.utc)).
         """
-
         filters = [PairLock.lock_end_time > now,
                    # Only active locks
                    PairLock.active.is_(True), ]
diff --git a/freqtrade/persistence/pairlock_middleware.py b/freqtrade/persistence/pairlock_middleware.py
index 8662fc36d..afbd9781b 100644
--- a/freqtrade/persistence/pairlock_middleware.py
+++ b/freqtrade/persistence/pairlock_middleware.py
@@ -103,6 +103,36 @@ class PairLocks():
         if PairLocks.use_db:
             PairLock.query.session.commit()
 
+    @staticmethod
+    def unlock_reason(reason: str, now: Optional[datetime] = None) -> None:
+        """
+        Release all locks for this reason.
+        :param reason: Which reason to unlock
+        :param now: Datetime object (generated via datetime.now(timezone.utc)).
+            defaults to datetime.now(timezone.utc)
+        """
+        if not now:
+            now = datetime.now(timezone.utc)
+
+        if PairLocks.use_db:
+            # used in live modes
+            logger.info(f"Releasing all locks with reason '{reason}':")
+            filters = [PairLock.lock_end_time > now,
+                       PairLock.active.is_(True),
+                       PairLock.reason == reason
+                       ]
+            locks = PairLock.query.filter(*filters)
+            for lock in locks:
+                logger.info(f"Releasing lock for {lock.pair} with reason '{reason}'.")
+                lock.active = False
+            PairLock.query.session.commit()
+        else:
+            # used in backtesting mode; don't show log messages for speed
+            locks = PairLocks.get_pair_locks(None)
+            for lock in locks:
+                if lock.reason == reason:
+                    lock.active = False
+
     @staticmethod
     def is_global_lock(now: Optional[datetime] = None) -> bool:
         """
@@ -128,7 +158,9 @@ class PairLocks():
 
     @staticmethod
     def get_all_locks() -> List[PairLock]:
-
+        """
+        Return all locks, also locks with expired end date
+        """
         if PairLocks.use_db:
             return PairLock.query.all()
         else:
diff --git a/freqtrade/plot/plotting.py b/freqtrade/plot/plotting.py
index 509c03e90..747248be7 100644
--- a/freqtrade/plot/plotting.py
+++ b/freqtrade/plot/plotting.py
@@ -1,15 +1,17 @@
 import logging
 from pathlib import Path
-from typing import Any, Dict, List
+from typing import Any, Dict, List, Optional
 
 import pandas as pd
 
 from freqtrade.configuration import TimeRange
-from freqtrade.data.btanalysis import (calculate_max_drawdown, combine_dataframes_with_mean,
+from freqtrade.data.btanalysis import (analyze_trade_parallelism, calculate_max_drawdown,
+                                       calculate_underwater, combine_dataframes_with_mean,
                                        create_cum_profit, extract_trades_of_period, load_trades)
 from freqtrade.data.converter import trim_dataframe
 from freqtrade.data.dataprovider import DataProvider
 from freqtrade.data.history import get_timerange, load_data
+from freqtrade.enums import CandleType
 from freqtrade.exceptions import OperationalException
 from freqtrade.exchange import timeframe_to_prev_date, timeframe_to_seconds
 from freqtrade.misc import pair_to_filename
@@ -51,6 +53,7 @@ def init_plotscript(config, markets: List, startup_candles: int = 0):
         timerange=timerange,
         startup_candles=startup_candles,
         data_format=config.get('dataformat_ohlcv', 'json'),
+        candle_type=config.get('candle_type_def', CandleType.SPOT)
     )
 
     if startup_candles and data:
@@ -60,8 +63,8 @@ def init_plotscript(config, markets: List, startup_candles: int = 0):
                                             startup_candles, min_date)
 
     no_trades = False
-    filename = config.get('exportfilename')
-    if config.get('no_trades', False):
+    filename = config.get("exportfilename")
+    if config.get("no_trades", False):
         no_trades = True
     elif config['trade_source'] == 'file':
         if not filename.is_dir() and not filename.is_file():
@@ -160,7 +163,7 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
     Add scatter points indicating max drawdown
     """
     try:
-        max_drawdown, highdate, lowdate, _, _ = calculate_max_drawdown(trades)
+        _, highdate, lowdate, _, _, max_drawdown = calculate_max_drawdown(trades)
 
         drawdown = go.Scatter(
             x=[highdate, lowdate],
@@ -169,8 +172,8 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
                 df_comb.loc[timeframe_to_prev_date(timeframe, lowdate), 'cum_profit'],
             ],
             mode='markers',
-            name=f"Max drawdown {max_drawdown * 100:.2f}%",
-            text=f"Max drawdown {max_drawdown * 100:.2f}%",
+            name=f"Max drawdown {max_drawdown:.2%}",
+            text=f"Max drawdown {max_drawdown:.2%}",
             marker=dict(
                 symbol='square-open',
                 size=9,
@@ -185,6 +188,48 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
     return fig
 
 
+def add_underwater(fig, row, trades: pd.DataFrame) -> make_subplots:
+    """
+    Add underwater plot
+    """
+    try:
+        underwater = calculate_underwater(trades, value_col="profit_abs")
+
+        underwater = go.Scatter(
+            x=underwater['date'],
+            y=underwater['drawdown'],
+            name="Underwater Plot",
+            fill='tozeroy',
+            fillcolor='#cc362b',
+            line={'color': '#cc362b'},
+        )
+        fig.add_trace(underwater, row, 1)
+    except ValueError:
+        logger.warning("No trades found - not plotting underwater plot")
+    return fig
+
+
+def add_parallelism(fig, row, trades: pd.DataFrame, timeframe: str) -> make_subplots:
+    """
+    Add Chart showing trade parallelism
+    """
+    try:
+        result = analyze_trade_parallelism(trades, timeframe)
+
+        drawdown = go.Scatter(
+            x=result.index,
+            y=result['open_trades'],
+            name="Parallel trades",
+            fill='tozeroy',
+            fillcolor='#242222',
+            line={'color': '#242222'},
+        )
+        fig.add_trace(drawdown, row, 1)
+    except ValueError:
+        logger.warning("No trades found - not plotting Parallelism.")
+    return fig
+
+
 def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
     """
     Add trades to "fig"
@@ -192,10 +237,12 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
     # Trades can be empty
     if trades is not None and len(trades) > 0:
         # Create description for sell summarizing the trade
-        trades['desc'] = trades.apply(lambda row: f"{round(row['profit_ratio'] * 100, 1)}%, "
-                                                  f"{row['sell_reason']}, "
-                                                  f"{row['trade_duration']} min",
-                                      axis=1)
+        trades['desc'] = trades.apply(
+            lambda row: f"{row['profit_ratio']:.2%}, " +
+            (f"{row['enter_tag']}, " if row['enter_tag'] is not None else "") +
+            f"{row['exit_reason']}, " +
+            f"{row['trade_duration']} min",
+            axis=1)
         trade_buys = go.Scatter(
             x=trades["open_date"],
             y=trades["open_rate"],
@@ -340,6 +387,35 @@ def add_areas(fig, row: int, data: pd.DataFrame, indicators) -> make_subplots:
     return fig
 
 
+def create_scatter(
+    data,
+    column_name,
+    color,
+    direction
+) -> Optional[go.Scatter]:
+
+    if column_name in data.columns:
+        df_short = data[data[column_name] == 1]
+        if len(df_short) > 0:
+            shorts = go.Scatter(
+                x=df_short.date,
+                y=df_short.close,
+                mode='markers',
+                name=column_name,
+                marker=dict(
+                    symbol=f"triangle-{direction}-dot",
+                    size=9,
+                    line=dict(width=1),
+                    color=color,
+                )
+            )
+            return shorts
+        else:
+            logger.warning(f"No {column_name}-signals found.")
+
+    return None
+
+
 def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None, *,
                                indicators1: List[str] = [],
                                indicators2: List[str] = [],
@@ -386,43 +462,15 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
     )
     fig.add_trace(candles, 1, 1)
 
-    if 'buy' in data.columns:
-        df_buy = data[data['buy'] == 1]
-        if len(df_buy) > 0:
-            buys = go.Scatter(
-                x=df_buy.date,
-                y=df_buy.close,
-                mode='markers',
-                name='buy',
-                marker=dict(
-                    symbol='triangle-up-dot',
-                    size=9,
-                    line=dict(width=1),
-                    color='green',
-                )
-            )
-            fig.add_trace(buys, 1, 1)
-        else:
-            logger.warning("No buy-signals found.")
+    longs = create_scatter(data, 'enter_long', 'green', 'up')
+    exit_longs = create_scatter(data, 'exit_long', 'red', 'down')
+    shorts = create_scatter(data, 'enter_short', 'blue', 'down')
+    exit_shorts = create_scatter(data, 'exit_short', 'violet', 'up')
+
+    for scatter in [longs, exit_longs, shorts, exit_shorts]:
+        if scatter:
+            fig.add_trace(scatter, 1, 1)
 
-    if 'sell' in data.columns:
-        df_sell = data[data['sell'] == 1]
-        if len(df_sell) > 0:
-            sells = go.Scatter(
-                x=df_sell.date,
-                y=df_sell.close,
-                mode='markers',
-                name='sell',
-                marker=dict(
-                    symbol='triangle-down-dot',
-                    size=9,
-                    line=dict(width=1),
-                    color='red',
-                )
-            )
-            fig.add_trace(sells, 1, 1)
-        else:
-            logger.warning("No sell-signals found.")
     # Add Bollinger Bands
     fig = plot_area(fig, 1, data, 'bb_lowerband', 'bb_upperband',
                     label="Bollinger Band")
@@ -460,7 +508,12 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
 def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
                           trades: pd.DataFrame, timeframe: str, stake_currency: str) -> go.Figure:
     # Combine close-values for all pairs, rename columns to "pair"
-    df_comb = combine_dataframes_with_mean(data, "close")
+    try:
+        df_comb = combine_dataframes_with_mean(data, "close")
+    except ValueError:
+        raise OperationalException(
+            "No data found. Please make sure that data is available for "
+            "the timerange and pairs selected.")
 
     # Trim trades to available OHLCV data
     trades = extract_trades_of_period(df_comb, trades, date_index=True)
@@ -477,20 +530,30 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
         name='Avg close price',
     )
 
-    fig = make_subplots(rows=3, cols=1, shared_xaxes=True,
-                        row_width=[1, 1, 1],
+    fig = make_subplots(rows=5, cols=1, shared_xaxes=True,
+                        row_heights=[1, 1, 1, 0.5, 1],
                         vertical_spacing=0.05,
-                        subplot_titles=["AVG Close Price", "Combined Profit", "Profit per pair"])
+                        subplot_titles=[
+                            "AVG Close Price",
+                            "Combined Profit",
+                            "Profit per pair",
+                            "Parallelism",
+                            "Underwater",
+                        ])
     fig['layout'].update(title="Freqtrade Profit plot")
     fig['layout']['yaxis1'].update(title='Price')
     fig['layout']['yaxis2'].update(title=f'Profit {stake_currency}')
     fig['layout']['yaxis3'].update(title=f'Profit {stake_currency}')
+    fig['layout']['yaxis4'].update(title='Trade count')
+    fig['layout']['yaxis5'].update(title='Underwater Plot')
     fig['layout']['xaxis']['rangeslider'].update(visible=False)
     fig.update_layout(modebar_add=["v1hovermode", "toggleSpikeLines"])
 
     fig.add_trace(avgclose, 1, 1)
     fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
     fig = add_max_drawdown(fig, 2, trades, df_comb, timeframe)
+    fig = add_parallelism(fig, 4, trades, timeframe)
+    fig = add_underwater(fig, 5, trades)
 
     for pair in pairs:
         profit_col = f'cum_profit_{pair}'
diff --git a/freqtrade/plugins/pairlist/AgeFilter.py b/freqtrade/plugins/pairlist/AgeFilter.py
index 5627d82ce..bb6f75012 100644
--- a/freqtrade/plugins/pairlist/AgeFilter.py
+++ b/freqtrade/plugins/pairlist/AgeFilter.py
@@ -9,6 +9,7 @@ import arrow
 from pandas import DataFrame
 
 from freqtrade.configuration import PeriodicCache
+from freqtrade.constants import ListPairsWithTimeframes
 from freqtrade.exceptions import OperationalException
 from freqtrade.misc import plural
 from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -71,8 +72,8 @@ class AgeFilter(IPairList):
         :param tickers: Tickers (from exchange.get_tickers()). May be cached.
         :return: new allowlist
         """
-        needed_pairs = [
-            (p, '1d') for p in pairlist
+        needed_pairs: ListPairsWithTimeframes = [
+            (p, '1d', self._config['candle_type_def']) for p in pairlist
             if p not in self._symbolsChecked and p not in self._symbolsCheckFailed]
         if not needed_pairs:
             # Remove pairs that have been removed before
@@ -88,7 +89,8 @@ class AgeFilter(IPairList):
         candles = self._exchange.refresh_latest_ohlcv(needed_pairs, since_ms=since_ms, cache=False)
         if self._enabled:
             for p in deepcopy(pairlist):
-                daily_candles = candles[(p, '1d')] if (p, '1d') in candles else None
+                daily_candles = candles[(p, '1d', self._config['candle_type_def'])] if (
+                    p, '1d', self._config['candle_type_def']) in candles else None
                 if not self._validate_pair_loc(p, daily_candles):
                     pairlist.remove(p)
         self.log_once(f"Validated {len(pairlist)} pairs.", logger.info)
@@ -98,7 +100,7 @@ class AgeFilter(IPairList):
         """
         Validate age for the ticker
         :param pair: Pair that's currently validated
-        :param ticker: ticker dict as returned from ccxt.fetch_tickers()
+        :param daily_candles: Downloaded daily candles
         :return: True if the pair can stay, false if it should be removed
         """
         # Check symbol in cache
diff --git a/freqtrade/plugins/pairlist/PerformanceFilter.py b/freqtrade/plugins/pairlist/PerformanceFilter.py
index 301ee57ab..5b02a47ab 100644
--- a/freqtrade/plugins/pairlist/PerformanceFilter.py
+++ b/freqtrade/plugins/pairlist/PerformanceFilter.py
@@ -21,6 +21,7 @@ class PerformanceFilter(IPairList):
         super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
 
         self._minutes = pairlistconfig.get('minutes', 0)
+        self._min_profit = pairlistconfig.get('min_profit', None)
 
     @property
     def needstickers(self) -> bool:
@@ -59,6 +60,7 @@ class PerformanceFilter(IPairList):
 
         # Get pairlist from performance dataframe values
         list_df = pd.DataFrame({'pair': pairlist})
+        list_df['prior_idx'] = list_df.index
 
         # Set initial value for pairs with no trades to 0
         # Sort the list using:
@@ -66,8 +68,16 @@ class PerformanceFilter(IPairList):
         #  - then count (low to high, so as to favor same performance with fewer trades)
         #  - then pair name alphametically
         sorted_df = list_df.merge(performance, on='pair', how='left')\
-            .fillna(0).sort_values(by=['count', 'pair'], ascending=True)\
-            .sort_values(by=['profit'], ascending=False)
+            .fillna(0).sort_values(by=['count', 'prior_idx'], ascending=True)\
+            .sort_values(by=['profit_ratio'], ascending=False)
+        if self._min_profit is not None:
+            removed = sorted_df[sorted_df['profit_ratio'] < self._min_profit]
+            for _, row in removed.iterrows():
+                self.log_once(
+                    f"Removing pair {row['pair']} since {row['profit_ratio']} is "
+                    f"below {self._min_profit}", logger.info)
+            sorted_df = sorted_df[sorted_df['profit_ratio'] >= self._min_profit]
+
         pairlist = sorted_df['pair'].tolist()
 
         return pairlist
diff --git a/freqtrade/plugins/pairlist/PrecisionFilter.py b/freqtrade/plugins/pairlist/PrecisionFilter.py
index a3c262e8c..521f38635 100644
--- a/freqtrade/plugins/pairlist/PrecisionFilter.py
+++ b/freqtrade/plugins/pairlist/PrecisionFilter.py
@@ -51,7 +51,7 @@ class PrecisionFilter(IPairList):
         :param ticker: ticker dict as returned from ccxt.fetch_tickers()
         :return: True if the pair can stay, false if it should be removed
         """
-        stop_price = ticker['ask'] * self._stoploss
+        stop_price = ticker['last'] * self._stoploss
 
         # Adjust stop-prices to precision
         sp = self._exchange.price_to_precision(pair, stop_price)
diff --git a/freqtrade/plugins/pairlist/PriceFilter.py b/freqtrade/plugins/pairlist/PriceFilter.py
index 5b5afb557..009789eaf 100644
--- a/freqtrade/plugins/pairlist/PriceFilter.py
+++ b/freqtrade/plugins/pairlist/PriceFilter.py
@@ -50,7 +50,7 @@ class PriceFilter(IPairList):
         """
         active_price_filters = []
         if self._low_price_ratio != 0:
-            active_price_filters.append(f"below {self._low_price_ratio * 100}%")
+            active_price_filters.append(f"below {self._low_price_ratio:.1%}")
         if self._min_price != 0:
             active_price_filters.append(f"below {self._min_price:.8f}")
         if self._max_price != 0:
@@ -82,7 +82,7 @@ class PriceFilter(IPairList):
             changeperc = compare / ticker['last']
             if changeperc > self._low_price_ratio:
                 self.log_once(f"Removed {pair} from whitelist, "
-                              f"because 1 unit is {changeperc * 100:.3f}%", logger.info)
+                              f"because 1 unit is {changeperc:.3%}", logger.info)
                 return False
 
         # Perform low_amount check
@@ -90,8 +90,7 @@ class PriceFilter(IPairList):
             price = ticker['last']
             market = self._exchange.markets[pair]
             limits = market['limits']
-            if ('amount' in limits and 'min' in limits['amount']
-                    and limits['amount']['min'] is not None):
+            if (limits['amount']['min'] is not None):
                 min_amount = limits['amount']['min']
                 min_precision = market['precision']['amount']
 
diff --git a/freqtrade/plugins/pairlist/ShuffleFilter.py b/freqtrade/plugins/pairlist/ShuffleFilter.py
index 4d3dd29e3..663bba49b 100644
--- a/freqtrade/plugins/pairlist/ShuffleFilter.py
+++ b/freqtrade/plugins/pairlist/ShuffleFilter.py
@@ -5,6 +5,7 @@ import logging
 import random
 from typing import Any, Dict, List
 
+from freqtrade.enums import RunMode
 from freqtrade.plugins.pairlist.IPairList import IPairList
 
 
@@ -18,7 +19,15 @@ class ShuffleFilter(IPairList):
                  pairlist_pos: int) -> None:
         super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
 
-        self._seed = pairlistconfig.get('seed')
+        # Apply seed in backtesting mode to get comparable results,
+        # but not in live modes to get a non-repeating order of pairs during live modes.
+        if config.get('runmode') in (RunMode.LIVE, RunMode.DRY_RUN):
+            self._seed = None
+            logger.info("Live mode detected, not applying seed.")
+        else:
+            self._seed = pairlistconfig.get('seed')
+            logger.info(f"Backtesting mode detected, applying seed value: {self._seed}")
+
         self._random = random.Random(self._seed)
 
     @property
diff --git a/freqtrade/plugins/pairlist/SpreadFilter.py b/freqtrade/plugins/pairlist/SpreadFilter.py
index 1b152774b..d1f88d2a5 100644
--- a/freqtrade/plugins/pairlist/SpreadFilter.py
+++ b/freqtrade/plugins/pairlist/SpreadFilter.py
@@ -4,6 +4,7 @@ Spread pair list filter
 import logging
 from typing import Any, Dict
 
+from freqtrade.exceptions import OperationalException
 from freqtrade.plugins.pairlist.IPairList import IPairList
 
 
@@ -20,6 +21,12 @@ class SpreadFilter(IPairList):
         self._max_spread_ratio = pairlistconfig.get('max_spread_ratio', 0.005)
         self._enabled = self._max_spread_ratio != 0
 
+        if not self._exchange.exchange_has('fetchTickers'):
+            raise OperationalException(
+                'Exchange does not support fetchTickers, therefore SpreadFilter cannot be used.'
+                'Please edit your config and restart the bot.'
+            )
+
     @property
     def needstickers(self) -> bool:
         """
@@ -34,7 +41,7 @@ class SpreadFilter(IPairList):
         Short whitelist method description - used for startup-messages
         """
         return (f"{self.name} - Filtering pairs with ask/bid diff above "
-                f"{self._max_spread_ratio * 100}%.")
+                f"{self._max_spread_ratio:.2%}.")
 
     def _validate_pair(self, pair: str, ticker: Dict[str, Any]) -> bool:
         """
@@ -47,7 +54,7 @@ class SpreadFilter(IPairList):
             spread = 1 - ticker['bid'] / ticker['ask']
             if spread > self._max_spread_ratio:
                 self.log_once(f"Removed {pair} from whitelist, because spread "
-                              f"{spread * 100:.3f}% > {self._max_spread_ratio * 100}%",
+                              f"{spread:.3%} > {self._max_spread_ratio:.3%}",
                               logger.info)
                 return False
             else:
diff --git a/freqtrade/plugins/pairlist/StaticPairList.py b/freqtrade/plugins/pairlist/StaticPairList.py
index d8623e13d..30fa474e4 100644
--- a/freqtrade/plugins/pairlist/StaticPairList.py
+++ b/freqtrade/plugins/pairlist/StaticPairList.py
@@ -4,9 +4,9 @@ Static Pair List provider
 Provides pair white list as it configured in config
 """
 import logging
+from copy import deepcopy
 from typing import Any, Dict, List
 
-from freqtrade.exceptions import OperationalException
 from freqtrade.plugins.pairlist.IPairList import IPairList
 
 
@@ -20,10 +20,6 @@ class StaticPairList(IPairList):
                  pairlist_pos: int) -> None:
         super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
 
-        if self._pairlist_pos != 0:
-            raise OperationalException(f"{self.name} can only be used in the first position "
-                                       "in the list of Pairlist Handlers.")
-
         self._allow_inactive = self._pairlistconfig.get('allow_inactive', False)
 
     @property
@@ -64,4 +60,8 @@ class StaticPairList(IPairList):
         :param tickers: Tickers (from exchange.get_tickers()). May be cached.
         :return: new whitelist
         """
-        return pairlist
+        pairlist_ = deepcopy(pairlist)
+        for pair in self._config['exchange']['pair_whitelist']:
+            if pair not in pairlist_:
+                pairlist_.append(pair)
+        return pairlist_
diff --git a/freqtrade/plugins/pairlist/VolatilityFilter.py b/freqtrade/plugins/pairlist/VolatilityFilter.py
index 9383e5d06..6aa857c2c 100644
--- a/freqtrade/plugins/pairlist/VolatilityFilter.py
+++ b/freqtrade/plugins/pairlist/VolatilityFilter.py
@@ -8,9 +8,10 @@ from typing import Any, Dict, List, Optional
 
 import arrow
 import numpy as np
-from cachetools.ttl import TTLCache
+from cachetools import TTLCache
 from pandas import DataFrame
 
+from freqtrade.constants import ListPairsWithTimeframes
 from freqtrade.exceptions import OperationalException
 from freqtrade.misc import plural
 from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -33,6 +34,7 @@ class VolatilityFilter(IPairList):
         self._min_volatility = pairlistconfig.get('min_volatility', 0)
         self._max_volatility = pairlistconfig.get('max_volatility', sys.maxsize)
         self._refresh_period = pairlistconfig.get('refresh_period', 1440)
+        self._def_candletype = self._config['candle_type_def']
 
         self._pair_cache: TTLCache = TTLCache(maxsize=1000, ttl=self._refresh_period)
 
@@ -67,7 +69,8 @@ class VolatilityFilter(IPairList):
         :param tickers: Tickers (from exchange.get_tickers()). May be cached.
         :return: new allowlist
         """
-        needed_pairs = [(p, '1d') for p in pairlist if p not in self._pair_cache]
+        needed_pairs: ListPairsWithTimeframes = [
+            (p, '1d', self._def_candletype) for p in pairlist if p not in self._pair_cache]
 
         since_ms = (arrow.utcnow()
                          .floor('day')
@@ -81,7 +84,8 @@ class VolatilityFilter(IPairList):
 
         if self._enabled:
             for p in deepcopy(pairlist):
-                daily_candles = candles[(p, '1d')] if (p, '1d') in candles else None
+                daily_candles = candles[(p, '1d', self._def_candletype)] if (
+                    p, '1d', self._def_candletype) in candles else None
                 if not self._validate_pair_loc(p, daily_candles):
                     pairlist.remove(p)
         return pairlist
@@ -90,7 +94,7 @@ class VolatilityFilter(IPairList):
         """
         Validate trading range
         :param pair: Pair that's currently validated
-        :param ticker: ticker dict as returned from ccxt.fetch_tickers()
+        :param daily_candles: Downloaded daily candles
         :return: True if the pair can stay, false if it should be removed
         """
         # Check symbol in cache
@@ -103,7 +107,7 @@ class VolatilityFilter(IPairList):
             returns = (np.log(daily_candles.close / daily_candles.close.shift(-1)))
             returns.fillna(0, inplace=True)
 
-            volatility_series = returns.rolling(window=self._days).std()*np.sqrt(self._days)
+            volatility_series = returns.rolling(window=self._days).std() * np.sqrt(self._days)
             volatility_avg = volatility_series.mean()
 
             if self._min_volatility <= volatility_avg <= self._max_volatility:
diff --git a/freqtrade/plugins/pairlist/VolumePairList.py b/freqtrade/plugins/pairlist/VolumePairList.py
index 0ffc8a8c8..26e7d45be 100644
--- a/freqtrade/plugins/pairlist/VolumePairList.py
+++ b/freqtrade/plugins/pairlist/VolumePairList.py
@@ -4,12 +4,12 @@ Volume PairList provider
 Provides dynamic pair list based on trade volumes
 """
 import logging
-from functools import partial
 from typing import Any, Dict, List
 
 import arrow
-from cachetools.ttl import TTLCache
+from cachetools import TTLCache
 
+from freqtrade.constants import ListPairsWithTimeframes
 from freqtrade.exceptions import OperationalException
 from freqtrade.exchange import timeframe_to_minutes
 from freqtrade.misc import format_ms_time
@@ -43,6 +43,7 @@ class VolumePairList(IPairList):
         self._lookback_days = self._pairlistconfig.get('lookback_days', 0)
         self._lookback_timeframe = self._pairlistconfig.get('lookback_timeframe', '1d')
         self._lookback_period = self._pairlistconfig.get('lookback_period', 0)
+        self._def_candletype = self._config['candle_type_def']
 
         if (self._lookback_days > 0) & (self._lookback_period > 0):
             raise OperationalException(
@@ -70,10 +71,13 @@ class VolumePairList(IPairList):
                 f'to at least {self._tf_in_sec} and restart the bot.'
             )
 
-        if not self._exchange.exchange_has('fetchTickers'):
+        if (not self._use_range and not (
+                self._exchange.exchange_has('fetchTickers')
+                and self._exchange._ft_has["tickers_have_quoteVolume"])):
             raise OperationalException(
-                'Exchange does not support dynamic whitelist. '
-                'Please edit your config and restart the bot.'
+                "Exchange does not support dynamic whitelist in this configuration. "
+                "Please edit your config and either remove Volumepairlist, "
+                "or switch to using candles. and restart the bot."
             )
 
         if not self._validate_keys(self._sort_key):
@@ -94,7 +98,7 @@ class VolumePairList(IPairList):
         If no Pairlist requires tickers, an empty Dict is passed
         as tickers argument to filter_pairlist
         """
-        return True
+        return not self._use_range
 
     def _validate_keys(self, key):
         return key in SORT_VALUES
@@ -120,11 +124,20 @@ class VolumePairList(IPairList):
         else:
             # Use fresh pairlist
             # Check if pair quote currency equals to the stake currency.
-            filtered_tickers = [
-                v for k, v in tickers.items()
-                if (self._exchange.get_pair_quote_currency(k) == self._stake_currency
-                    and (self._use_range or v[self._sort_key] is not None))]
-            pairlist = [s['symbol'] for s in filtered_tickers]
+            _pairlist = [k for k in self._exchange.get_markets(
+                quote_currencies=[self._stake_currency],
+                tradable_only=True, active_only=True).keys()]
+            # No point in testing for blacklisted pairs...
+            _pairlist = self.verify_blacklist(_pairlist, logger.info)
+            if not self._use_range:
+                filtered_tickers = [
+                    v for k, v in tickers.items()
+                    if (self._exchange.get_pair_quote_currency(k) == self._stake_currency
+                        and (self._use_range or v[self._sort_key] is not None)
+                        and v['symbol'] in _pairlist)]
+                pairlist = [s['symbol'] for s in filtered_tickers]
+            else:
+                pairlist = _pairlist
 
             pairlist = self.filter_pairlist(pairlist, tickers)
             self._pair_cache['pairlist'] = pairlist.copy()
@@ -139,11 +152,11 @@ class VolumePairList(IPairList):
         :param tickers: Tickers (from exchange.get_tickers()). May be cached.
         :return: new whitelist
         """
-        # Use the incoming pairlist.
-        filtered_tickers = [v for k, v in tickers.items() if k in pairlist]
-
-        # get lookback period in ms, for exchange ohlcv fetch
         if self._use_range:
+            # Create bare minimum from tickers structure.
+            filtered_tickers: List[Dict[str, Any]] = [{'symbol': k} for k in pairlist]
+
+            # get lookback period in ms, for exchange ohlcv fetch
             since_ms = int(arrow.utcnow()
                            .floor('minute')
                            .shift(minutes=-(self._lookback_period * self._tf_in_min)
@@ -159,11 +172,10 @@ class VolumePairList(IPairList):
             self.log_once(f"Using volume range of {self._lookback_period} candles, timeframe: "
                           f"{self._lookback_timeframe}, starting from {format_ms_time(since_ms)} "
                           f"till {format_ms_time(to_ms)}", logger.info)
-            needed_pairs = [
-                (p, self._lookback_timeframe) for p in
-                [
-                    s['symbol'] for s in filtered_tickers
-                ] if p not in self._pair_cache
+            needed_pairs: ListPairsWithTimeframes = [
+                (p, self._lookback_timeframe, self._def_candletype) for p in
+                [s['symbol'] for s in filtered_tickers]
+                if p not in self._pair_cache
             ]
 
             # Get all candles
@@ -174,16 +186,22 @@ class VolumePairList(IPairList):
                 )
             for i, p in enumerate(filtered_tickers):
                 pair_candles = candles[
-                    (p['symbol'], self._lookback_timeframe)
-                ] if (p['symbol'], self._lookback_timeframe) in candles else None
+                    (p['symbol'], self._lookback_timeframe, self._def_candletype)
+                ] if (
+                    p['symbol'], self._lookback_timeframe, self._def_candletype
+                    ) in candles else None
                 # in case of candle data calculate typical price and quoteVolume for candle
                 if pair_candles is not None and not pair_candles.empty:
-                    pair_candles['typical_price'] = (pair_candles['high'] + pair_candles['low']
-                                                     + pair_candles['close']) / 3
-                    pair_candles['quoteVolume'] = (
-                        pair_candles['volume'] * pair_candles['typical_price']
-                    )
+                    if self._exchange._ft_has["ohlcv_volume_currency"] == "base":
+                        pair_candles['typical_price'] = (pair_candles['high'] + pair_candles['low']
+                                                         + pair_candles['close']) / 3
 
+                        pair_candles['quoteVolume'] = (
+                            pair_candles['volume'] * pair_candles['typical_price']
+                        )
+                    else:
+                        # Exchange ohlcv data is in quote volume already.
+                        pair_candles['quoteVolume'] = pair_candles['volume']
                     # ensure that a rolling sum over the lookback_period is built
                     # if pair_candles contains more candles than lookback_period
                     quoteVolume = (pair_candles['quoteVolume']
@@ -195,6 +213,9 @@ class VolumePairList(IPairList):
                     filtered_tickers[i]['quoteVolume'] = quoteVolume
                 else:
                     filtered_tickers[i]['quoteVolume'] = 0
+        else:
+            # Tickers mode - filter based on incomming pairlist.
+            filtered_tickers = [v for k, v in tickers.items() if k in pairlist]
 
         if self._min_value > 0:
             filtered_tickers = [
@@ -204,7 +225,7 @@ class VolumePairList(IPairList):
 
         # Validate whitelist to only have active market pairs
         pairs = self._whitelist_for_active_markets([s['symbol'] for s in sorted_tickers])
-        pairs = self.verify_blacklist(pairs, partial(self.log_once, logmethod=logger.info))
+        pairs = self.verify_blacklist(pairs, logmethod=logger.info)
         # Limit pairlist to the requested number of pairs
         pairs = pairs[:self._number_pairs]
 
diff --git a/freqtrade/plugins/pairlist/rangestabilityfilter.py b/freqtrade/plugins/pairlist/rangestabilityfilter.py
index 3e5a002ff..c9edfd13d 100644
--- a/freqtrade/plugins/pairlist/rangestabilityfilter.py
+++ b/freqtrade/plugins/pairlist/rangestabilityfilter.py
@@ -6,9 +6,10 @@ from copy import deepcopy
 from typing import Any, Dict, List, Optional
 
 import arrow
-from cachetools.ttl import TTLCache
+from cachetools import TTLCache
 from pandas import DataFrame
 
+from freqtrade.constants import ListPairsWithTimeframes
 from freqtrade.exceptions import OperationalException
 from freqtrade.misc import plural
 from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -28,6 +29,7 @@ class RangeStabilityFilter(IPairList):
         self._min_rate_of_change = pairlistconfig.get('min_rate_of_change', 0.01)
         self._max_rate_of_change = pairlistconfig.get('max_rate_of_change', None)
         self._refresh_period = pairlistconfig.get('refresh_period', 1440)
+        self._def_candletype = self._config['candle_type_def']
 
         self._pair_cache: TTLCache = TTLCache(maxsize=1000, ttl=self._refresh_period)
 
@@ -65,7 +67,8 @@ class RangeStabilityFilter(IPairList):
         :param tickers: Tickers (from exchange.get_tickers()). May be cached.
         :return: new allowlist
         """
-        needed_pairs = [(p, '1d') for p in pairlist if p not in self._pair_cache]
+        needed_pairs: ListPairsWithTimeframes = [
+            (p, '1d', self._def_candletype) for p in pairlist if p not in self._pair_cache]
 
         since_ms = (arrow.utcnow()
                          .floor('day')
@@ -79,7 +82,8 @@ class RangeStabilityFilter(IPairList):
 
         if self._enabled:
             for p in deepcopy(pairlist):
-                daily_candles = candles[(p, '1d')] if (p, '1d') in candles else None
+                daily_candles = candles[(p, '1d', self._def_candletype)] if (
+                    p, '1d', self._def_candletype) in candles else None
                 if not self._validate_pair_loc(p, daily_candles):
                     pairlist.remove(p)
         return pairlist
@@ -88,7 +92,7 @@ class RangeStabilityFilter(IPairList):
         """
         Validate trading range
         :param pair: Pair that's currently validated
-        :param ticker: ticker dict as returned from ccxt.fetch_tickers()
+        :param daily_candles: Downloaded daily candles
         :return: True if the pair can stay, false if it should be removed
         """
         # Check symbol in cache
diff --git a/freqtrade/plugins/pairlistmanager.py b/freqtrade/plugins/pairlistmanager.py
index face79729..2ae67a157 100644
--- a/freqtrade/plugins/pairlistmanager.py
+++ b/freqtrade/plugins/pairlistmanager.py
@@ -2,13 +2,15 @@
 PairList manager class
 """
 import logging
-from copy import deepcopy
+from functools import partial
 from typing import Dict, List
 
 from cachetools import TTLCache, cached
 
 from freqtrade.constants import ListPairsWithTimeframes
+from freqtrade.enums import CandleType
 from freqtrade.exceptions import OperationalException
+from freqtrade.mixins import LoggingMixin
 from freqtrade.plugins.pairlist.IPairList import IPairList
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.resolvers import PairListResolver
@@ -17,7 +19,7 @@ from freqtrade.resolvers import PairListResolver
 logger = logging.getLogger(__name__)
 
 
-class PairListManager():
+class PairListManager(LoggingMixin):
 
     def __init__(self, exchange, config: dict) -> None:
         self._exchange = exchange
@@ -41,6 +43,9 @@ class PairListManager():
         if not self._pairlist_handlers:
             raise OperationalException("No Pairlist Handlers defined")
 
+        refresh_period = config.get('pairlist_refresh_period', 3600)
+        LoggingMixin.__init__(self, logger, refresh_period)
+
     @property
     def whitelist(self) -> List[str]:
         """The current whitelist"""
@@ -108,9 +113,10 @@ class PairListManager():
         except ValueError as err:
             logger.error(f"Pair blacklist contains an invalid Wildcard: {err}")
             return []
-        for pair in deepcopy(pairlist):
+        log_once = partial(self.log_once, logmethod=logmethod)
+        for pair in pairlist.copy():
             if pair in blacklist:
-                logmethod(f"Pair {pair} in your blacklist. Removing it from whitelist...")
+                log_once(f"Pair {pair} in your blacklist. Removing it from whitelist...")
                 pairlist.remove(pair)
         return pairlist
 
@@ -127,7 +133,6 @@ class PairListManager():
         :return: pairlist - whitelisted pairs
         """
         try:
-
             whitelist = expand_pairlist(pairlist, self._exchange.get_markets().keys(), keep_invalid)
         except ValueError as err:
             logger.error(f"Pair whitelist contains an invalid Wildcard: {err}")
@@ -138,4 +143,10 @@ class PairListManager():
         """
         Create list of pair tuples with (pair, timeframe)
         """
-        return [(pair, timeframe or self._config['timeframe']) for pair in pairs]
+        return [
+            (
+                pair,
+                timeframe or self._config['timeframe'],
+                self._config.get('candle_type_def', CandleType.SPOT)
+            ) for pair in pairs
+        ]
diff --git a/freqtrade/plugins/protections/max_drawdown_protection.py b/freqtrade/plugins/protections/max_drawdown_protection.py
index 67e204039..b6ef92bd5 100644
--- a/freqtrade/plugins/protections/max_drawdown_protection.py
+++ b/freqtrade/plugins/protections/max_drawdown_protection.py
@@ -36,7 +36,7 @@ class MaxDrawdown(IProtection):
         """
         LockReason to use
         """
-        return (f'{drawdown} > {self._max_allowed_drawdown} in {self.lookback_period_str}, '
+        return (f'{drawdown} passed {self._max_allowed_drawdown} in {self.lookback_period_str}, '
                 f'locking for {self.stop_duration_str}.')
 
     def _max_drawdown(self, date_now: datetime) -> ProtectionReturn:
@@ -55,7 +55,8 @@ class MaxDrawdown(IProtection):
 
         # Drawdown is always positive
         try:
-            drawdown, _, _, _, _ = calculate_max_drawdown(trades_df, value_col='close_profit')
+            # TODO: This should use absolute profit calculation, considering account balance.
+            drawdown, _, _, _, _, _ = calculate_max_drawdown(trades_df, value_col='close_profit')
         except ValueError:
             return False, None, None
 
diff --git a/freqtrade/plugins/protections/stoploss_guard.py b/freqtrade/plugins/protections/stoploss_guard.py
index 40edf1204..8d7fb2a0e 100644
--- a/freqtrade/plugins/protections/stoploss_guard.py
+++ b/freqtrade/plugins/protections/stoploss_guard.py
@@ -3,7 +3,7 @@ import logging
 from datetime import datetime, timedelta
 from typing import Any, Dict
 
-from freqtrade.enums import SellType
+from freqtrade.enums import ExitType
 from freqtrade.persistence import Trade
 from freqtrade.plugins.protections import IProtection, ProtectionReturn
 
@@ -41,21 +41,11 @@ class StoplossGuard(IProtection):
         Evaluate recent trades
         """
         look_back_until = date_now - timedelta(minutes=self._lookback_period)
-        # filters = [
-        #     Trade.is_open.is_(False),
-        #     Trade.close_date > look_back_until,
-        #     or_(Trade.sell_reason == SellType.STOP_LOSS.value,
-        #         and_(Trade.sell_reason == SellType.TRAILING_STOP_LOSS.value,
-        #              Trade.close_profit < 0))
-        # ]
-        # if pair:
-        #     filters.append(Trade.pair == pair)
-        # trades = Trade.get_trades(filters).all()
 
         trades1 = Trade.get_trades_proxy(pair=pair, is_open=False, close_date=look_back_until)
-        trades = [trade for trade in trades1 if (str(trade.sell_reason) in (
-            SellType.TRAILING_STOP_LOSS.value, SellType.STOP_LOSS.value,
-            SellType.STOPLOSS_ON_EXCHANGE.value)
+        trades = [trade for trade in trades1 if (str(trade.exit_reason) in (
+            ExitType.TRAILING_STOP_LOSS.value, ExitType.STOP_LOSS.value,
+            ExitType.STOPLOSS_ON_EXCHANGE.value)
             and trade.close_profit and trade.close_profit < 0)]
 
         if len(trades) < self._trade_limit:
diff --git a/freqtrade/resolvers/hyperopt_resolver.py b/freqtrade/resolvers/hyperopt_resolver.py
index 6f0263e93..e3c234f60 100644
--- a/freqtrade/resolvers/hyperopt_resolver.py
+++ b/freqtrade/resolvers/hyperopt_resolver.py
@@ -44,7 +44,6 @@ class HyperOptLossResolver(IResolver):
                                                         extra_dir=config.get('hyperopt_path'))
 
         # Assign timeframe to be used in hyperopt
-        hyperoptloss.__class__.ticker_interval = str(config['timeframe'])
         hyperoptloss.__class__.timeframe = str(config['timeframe'])
 
         return hyperoptloss
diff --git a/freqtrade/resolvers/iresolver.py b/freqtrade/resolvers/iresolver.py
index 2cccec70a..3ab461041 100644
--- a/freqtrade/resolvers/iresolver.py
+++ b/freqtrade/resolvers/iresolver.py
@@ -6,6 +6,7 @@ This module load custom objects
 import importlib.util
 import inspect
 import logging
+import sys
 from pathlib import Path
 from typing import Any, Dict, Iterator, List, Optional, Tuple, Type, Union
 
@@ -15,6 +16,22 @@ from freqtrade.exceptions import OperationalException
 logger = logging.getLogger(__name__)
 
 
+class PathModifier:
+    def __init__(self, path: Path):
+        self.path = path
+
+    def __enter__(self):
+        """Inject path to allow importing with relative imports."""
+        sys.path.insert(0, str(self.path))
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        """Undo insertion of local path."""
+        str_path = str(self.path)
+        if str_path in sys.path:
+            sys.path.remove(str_path)
+
+
 class IResolver:
     """
     This class contains all the logic to load custom classes
@@ -57,27 +74,32 @@ class IResolver:
 
         # Generate spec based on absolute path
         # Pass object_name as first argument to have logging print a reasonable name.
-        spec = importlib.util.spec_from_file_location(object_name or "", str(module_path))
-        if not spec:
-            return iter([None])
-
-        module = importlib.util.module_from_spec(spec)
-        try:
-            spec.loader.exec_module(module)  # type: ignore # importlib does not use typehints
-        except (ModuleNotFoundError, SyntaxError, ImportError, NameError) as err:
-            # Catch errors in case a specific module is not installed
-            logger.warning(f"Could not import {module_path} due to '{err}'")
-            if enum_failed:
+        with PathModifier(module_path.parent):
+            module_name = module_path.stem or ""
+            spec = importlib.util.spec_from_file_location(module_name, str(module_path))
+            if not spec:
                 return iter([None])
 
-        valid_objects_gen = (
-            (obj, inspect.getsource(module)) for
-            name, obj in inspect.getmembers(
-                module, inspect.isclass) if ((object_name is None or object_name == name)
-                                             and issubclass(obj, cls.object_type)
-                                             and obj is not cls.object_type)
-        )
-        return valid_objects_gen
+            module = importlib.util.module_from_spec(spec)
+            try:
+                spec.loader.exec_module(module)  # type: ignore # importlib does not use typehints
+            except (ModuleNotFoundError, SyntaxError, ImportError, NameError) as err:
+                # Catch errors in case a specific module is not installed
+                logger.warning(f"Could not import {module_path} due to '{err}'")
+                if enum_failed:
+                    return iter([None])
+
+            valid_objects_gen = (
+                (obj, inspect.getsource(module)) for
+                name, obj in inspect.getmembers(
+                    module, inspect.isclass) if ((object_name is None or object_name == name)
+                                                 and issubclass(obj, cls.object_type)
+                                                 and obj is not cls.object_type
+                                                 and obj.__module__ == module_name
+                                                 )
+            )
+            # The __module__ check ensures we only use strategies that are defined in this folder.
+            return valid_objects_gen
 
     @classmethod
     def _search_object(cls, directory: Path, *, object_name: str, add_source: bool = False
@@ -91,7 +113,7 @@ class IResolver:
         logger.debug(f"Searching for {cls.object_type.__name__} {object_name} in '{directory}'")
         for entry in directory.iterdir():
             # Only consider python files
-            if not str(entry).endswith('.py'):
+            if entry.suffix != '.py':
                 logger.debug('Ignoring %s', entry)
                 continue
             if entry.is_symlink() and not entry.is_file():
@@ -169,7 +191,7 @@ class IResolver:
         objects = []
         for entry in directory.iterdir():
             # Only consider python files
-            if not str(entry).endswith('.py'):
+            if entry.suffix != '.py':
                 logger.debug('Ignoring %s', entry)
                 continue
             module_path = entry.resolve()
diff --git a/freqtrade/resolvers/strategy_resolver.py b/freqtrade/resolvers/strategy_resolver.py
index e7c077e84..76515026c 100644
--- a/freqtrade/resolvers/strategy_resolver.py
+++ b/freqtrade/resolvers/strategy_resolver.py
@@ -10,7 +10,9 @@ from inspect import getfullargspec
 from pathlib import Path
 from typing import Any, Dict, Optional
 
+from freqtrade.configuration.config_validation import validate_migrated_strategy_settings
 from freqtrade.constants import REQUIRED_ORDERTIF, REQUIRED_ORDERTYPES, USERPATH_STRATEGIES
+from freqtrade.enums import TradingMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.resolvers import IResolver
 from freqtrade.strategy.interface import IStrategy
@@ -45,28 +47,24 @@ class StrategyResolver(IResolver):
             strategy_name, config=config,
             extra_dir=config.get('strategy_path'))
 
-        if hasattr(strategy, 'ticker_interval') and not hasattr(strategy, 'timeframe'):
-            # Assign ticker_interval to timeframe to keep compatibility
-            if 'timeframe' not in config:
-                logger.warning(
-                    "DEPRECATED: Please migrate to using 'timeframe' instead of 'ticker_interval'."
-                )
-                strategy.timeframe = strategy.ticker_interval
-
         if strategy._ft_params_from_file:
             # Set parameters from Hyperopt results file
             params = strategy._ft_params_from_file
-            strategy.minimal_roi = params.get('roi', strategy.minimal_roi)
+            strategy.minimal_roi = params.get('roi', getattr(strategy, 'minimal_roi', {}))
 
-            strategy.stoploss = params.get('stoploss', {}).get('stoploss', strategy.stoploss)
+            strategy.stoploss = params.get('stoploss', {}).get(
+                'stoploss', getattr(strategy, 'stoploss', -0.1))
             trailing = params.get('trailing', {})
-            strategy.trailing_stop = trailing.get('trailing_stop', strategy.trailing_stop)
-            strategy.trailing_stop_positive = trailing.get('trailing_stop_positive',
-                                                           strategy.trailing_stop_positive)
+            strategy.trailing_stop = trailing.get(
+                'trailing_stop', getattr(strategy, 'trailing_stop', False))
+            strategy.trailing_stop_positive = trailing.get(
+                'trailing_stop_positive', getattr(strategy, 'trailing_stop_positive', None))
             strategy.trailing_stop_positive_offset = trailing.get(
-                'trailing_stop_positive_offset', strategy.trailing_stop_positive_offset)
+                'trailing_stop_positive_offset',
+                getattr(strategy, 'trailing_stop_positive_offset', 0))
             strategy.trailing_only_offset_is_reached = trailing.get(
-                'trailing_only_offset_is_reached', strategy.trailing_only_offset_is_reached)
+                'trailing_only_offset_is_reached',
+                getattr(strategy, 'trailing_only_offset_is_reached', 0.0))
 
         # Set attributes
         # Check if we need to override configuration
@@ -87,12 +85,14 @@ class StrategyResolver(IResolver):
                       ("protections",                     None),
                       ("startup_candle_count",            None),
                       ("unfilledtimeout",                 None),
-                      ("use_sell_signal",                 True),
-                      ("sell_profit_only",                False),
-                      ("ignore_roi_if_buy_signal",        False),
-                      ("sell_profit_offset",              0.0),
+                      ("use_exit_signal",                 True),
+                      ("exit_profit_only",                False),
+                      ("ignore_roi_if_entry_signal",      False),
+                      ("exit_profit_offset",              0.0),
                       ("disable_dataframe_checks",        False),
-                      ("ignore_buying_expired_candle_after",  0)
+                      ("ignore_buying_expired_candle_after",  0),
+                      ("position_adjustment_enable",      False),
+                      ("max_entry_position_adjustment",      -1),
                       ]
         for attribute, default in attributes:
             StrategyResolver._override_attribute_helper(strategy, config,
@@ -139,10 +139,6 @@ class StrategyResolver(IResolver):
         """
         Normalize attributes to have the correct type.
         """
-        # Assign deprecated variable - to not break users code relying on this.
-        if hasattr(strategy, 'timeframe'):
-            strategy.ticker_interval = strategy.timeframe
-
         # Sort and apply type conversions
         if hasattr(strategy, 'minimal_roi'):
             strategy.minimal_roi = dict(sorted(
@@ -153,14 +149,83 @@ class StrategyResolver(IResolver):
         return strategy
 
     @staticmethod
-    def _strategy_sanity_validations(strategy):
+    def _strategy_sanity_validations(strategy: IStrategy):
+        # Ensure necessary migrations are performed first.
+        validate_migrated_strategy_settings(strategy.config)
+
         if not all(k in strategy.order_types for k in REQUIRED_ORDERTYPES):
             raise ImportError(f"Impossible to load Strategy '{strategy.__class__.__name__}'. "
                               f"Order-types mapping is incomplete.")
-
         if not all(k in strategy.order_time_in_force for k in REQUIRED_ORDERTIF):
             raise ImportError(f"Impossible to load Strategy '{strategy.__class__.__name__}'. "
                               f"Order-time-in-force mapping is incomplete.")
+        trading_mode = strategy.config.get('trading_mode', TradingMode.SPOT)
+
+        if (strategy.can_short and trading_mode == TradingMode.SPOT):
+            raise ImportError(
+                "Short strategies cannot run in spot markets. Please make sure that this "
+                "is the correct strategy and that your trading mode configuration is correct. "
+                "You can run this strategy in spot markets by setting `can_short=False`"
+                " in your strategy. Please note that short signals will be ignored in that case."
+                )
+
+    @staticmethod
+    def validate_strategy(strategy: IStrategy) -> IStrategy:
+        if strategy.config.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
+            # Require new method
+            warn_deprecated_setting(strategy, 'sell_profit_only', 'exit_profit_only', True)
+            warn_deprecated_setting(strategy, 'sell_profit_offset', 'exit_profit_offset', True)
+            warn_deprecated_setting(strategy, 'use_sell_signal', 'use_exit_signal', True)
+            warn_deprecated_setting(strategy, 'ignore_roi_if_buy_signal',
+                                    'ignore_roi_if_entry_signal', True)
+
+            if not check_override(strategy, IStrategy, 'populate_entry_trend'):
+                raise OperationalException("`populate_entry_trend` must be implemented.")
+            if not check_override(strategy, IStrategy, 'populate_exit_trend'):
+                raise OperationalException("`populate_exit_trend` must be implemented.")
+            if check_override(strategy, IStrategy, 'check_buy_timeout'):
+                raise OperationalException("Please migrate your implementation "
+                                           "of `check_buy_timeout` to `check_entry_timeout`.")
+            if check_override(strategy, IStrategy, 'check_sell_timeout'):
+                raise OperationalException("Please migrate your implementation "
+                                           "of `check_sell_timeout` to `check_exit_timeout`.")
+
+            if check_override(strategy, IStrategy, 'custom_sell'):
+                raise OperationalException(
+                    "Please migrate your implementation of `custom_sell` to `custom_exit`.")
+
+        else:
+            # TODO: Implementing one of the following methods should show a deprecation warning
+            #  buy_trend and sell_trend, custom_sell
+            warn_deprecated_setting(strategy, 'sell_profit_only', 'exit_profit_only')
+            warn_deprecated_setting(strategy, 'sell_profit_offset', 'exit_profit_offset')
+            warn_deprecated_setting(strategy, 'use_sell_signal', 'use_exit_signal')
+            warn_deprecated_setting(strategy, 'ignore_roi_if_buy_signal',
+                                    'ignore_roi_if_entry_signal')
+
+            if (
+                not check_override(strategy, IStrategy, 'populate_buy_trend')
+                and not check_override(strategy, IStrategy, 'populate_entry_trend')
+            ):
+                raise OperationalException(
+                    "`populate_entry_trend` or `populate_buy_trend` must be implemented.")
+            if (
+                not check_override(strategy, IStrategy, 'populate_sell_trend')
+                and not check_override(strategy, IStrategy, 'populate_exit_trend')
+            ):
+                raise OperationalException(
+                    "`populate_exit_trend` or `populate_sell_trend` must be implemented.")
+
+            strategy._populate_fun_len = len(getfullargspec(strategy.populate_indicators).args)
+            strategy._buy_fun_len = len(getfullargspec(strategy.populate_buy_trend).args)
+            strategy._sell_fun_len = len(getfullargspec(strategy.populate_sell_trend).args)
+            if any(x == 2 for x in [
+                strategy._populate_fun_len,
+                strategy._buy_fun_len,
+                strategy._sell_fun_len
+            ]):
+                strategy.INTERFACE_VERSION = 1
+        return strategy
 
     @staticmethod
     def _load_strategy(strategy_name: str,
@@ -193,23 +258,35 @@ class StrategyResolver(IResolver):
                 # register temp path with the bot
                 abs_paths.insert(0, temp.resolve())
 
-        strategy = StrategyResolver._load_object(paths=abs_paths,
-                                                 object_name=strategy_name,
-                                                 add_source=True,
-                                                 kwargs={'config': config},
-                                                 )
-        if strategy:
-            strategy._populate_fun_len = len(getfullargspec(strategy.populate_indicators).args)
-            strategy._buy_fun_len = len(getfullargspec(strategy.populate_buy_trend).args)
-            strategy._sell_fun_len = len(getfullargspec(strategy.populate_sell_trend).args)
-            if any(x == 2 for x in [strategy._populate_fun_len,
-                                    strategy._buy_fun_len,
-                                    strategy._sell_fun_len]):
-                strategy.INTERFACE_VERSION = 1
+        strategy = StrategyResolver._load_object(
+            paths=abs_paths,
+            object_name=strategy_name,
+            add_source=True,
+            kwargs={'config': config},
+        )
 
-            return strategy
+        if strategy:
+
+            return StrategyResolver.validate_strategy(strategy)
 
         raise OperationalException(
             f"Impossible to load Strategy '{strategy_name}'. This class does not exist "
             "or contains Python code errors."
         )
+
+
+def warn_deprecated_setting(strategy: IStrategy, old: str, new: str, error=False):
+    if hasattr(strategy, old):
+        errormsg = f"DEPRECATED: Using '{old}' moved to '{new}'."
+        if error:
+            raise OperationalException(errormsg)
+        logger.warning(errormsg)
+        setattr(strategy, new, getattr(strategy, f'{old}'))
+
+
+def check_override(object, parentclass, attribute):
+    """
+    Checks if a object overrides the parent class attribute.
+    :returns: True if the object is overridden.
+    """
+    return getattr(type(object), attribute) != getattr(parentclass, attribute)
diff --git a/freqtrade/rpc/api_server/api_backtest.py b/freqtrade/rpc/api_server/api_backtest.py
index 4623c187e..a902ea984 100644
--- a/freqtrade/rpc/api_server/api_backtest.py
+++ b/freqtrade/rpc/api_server/api_backtest.py
@@ -1,13 +1,17 @@
 import asyncio
 import logging
 from copy import deepcopy
+from typing import Any, Dict, List
 
 from fastapi import APIRouter, BackgroundTasks, Depends
 
+from freqtrade.configuration.config_validation import validate_config_consistency
+from freqtrade.data.btanalysis import get_backtest_resultlist, load_and_merge_backtest_result
 from freqtrade.enums import BacktestState
 from freqtrade.exceptions import DependencyException
-from freqtrade.rpc.api_server.api_schemas import BacktestRequest, BacktestResponse
-from freqtrade.rpc.api_server.deps import get_config
+from freqtrade.rpc.api_server.api_schemas import (BacktestHistoryEntry, BacktestRequest,
+                                                  BacktestResponse)
+from freqtrade.rpc.api_server.deps import get_config, is_webserver_mode
 from freqtrade.rpc.api_server.webserver import ApiServer
 from freqtrade.rpc.rpc import RPCException
 
@@ -19,8 +23,9 @@ router = APIRouter()
 
 
 @router.post('/backtest', response_model=BacktestResponse, tags=['webserver', 'backtest'])
+# flake8: noqa: C901
 async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: BackgroundTasks,
-                             config=Depends(get_config)):
+                             config=Depends(get_config), ws_mode=Depends(is_webserver_mode)):
     """Start backtesting if not done so already"""
     if ApiServer._bgtask_running:
         raise RPCException('Bot Background task already running')
@@ -31,52 +36,73 @@ async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: Bac
     for setting in settings.keys():
         if settings[setting] is not None:
             btconfig[setting] = settings[setting]
+    try:
+        btconfig['stake_amount'] = float(btconfig['stake_amount'])
+    except ValueError:
+        pass
+
+    # Force dry-run for backtesting
+    btconfig['dry_run'] = True
 
     # Start backtesting
     # Initialize backtesting object
     def run_backtest():
-        from freqtrade.optimize.optimize_reports import generate_backtest_stats
+        from freqtrade.optimize.optimize_reports import (generate_backtest_stats,
+                                                         store_backtest_stats)
         from freqtrade.resolvers import StrategyResolver
         asyncio.set_event_loop(asyncio.new_event_loop())
         try:
             # Reload strategy
             lastconfig = ApiServer._bt_last_config
             strat = StrategyResolver.load_strategy(btconfig)
+            validate_config_consistency(btconfig)
 
             if (
                 not ApiServer._bt
                 or lastconfig.get('timeframe') != strat.timeframe
                 or lastconfig.get('timeframe_detail') != btconfig.get('timeframe_detail')
-                or lastconfig.get('dry_run_wallet') != btconfig.get('dry_run_wallet', 0)
                 or lastconfig.get('timerange') != btconfig['timerange']
             ):
                 from freqtrade.optimize.backtesting import Backtesting
                 ApiServer._bt = Backtesting(btconfig)
-                if ApiServer._bt.timeframe_detail:
-                    ApiServer._bt.load_bt_data_detail()
-
+                ApiServer._bt.load_bt_data_detail()
+            else:
+                ApiServer._bt.config = btconfig
+                ApiServer._bt.init_backtest()
             # Only reload data if timeframe changed.
             if (
                 not ApiServer._bt_data
                 or not ApiServer._bt_timerange
-                or lastconfig.get('stake_amount') != btconfig.get('stake_amount')
-                or lastconfig.get('enable_protections') != btconfig.get('enable_protections')
-                or lastconfig.get('protections') != btconfig.get('protections', [])
                 or lastconfig.get('timeframe') != strat.timeframe
+                or lastconfig.get('timerange') != btconfig['timerange']
             ):
-                lastconfig['timerange'] = btconfig['timerange']
-                lastconfig['protections'] = btconfig.get('protections', [])
-                lastconfig['enable_protections'] = btconfig.get('enable_protections')
-                lastconfig['dry_run_wallet'] = btconfig.get('dry_run_wallet')
-                lastconfig['timeframe'] = strat.timeframe
                 ApiServer._bt_data, ApiServer._bt_timerange = ApiServer._bt.load_bt_data()
 
+            lastconfig['timerange'] = btconfig['timerange']
+            lastconfig['timeframe'] = strat.timeframe
+            lastconfig['protections'] = btconfig.get('protections', [])
+            lastconfig['enable_protections'] = btconfig.get('enable_protections')
+            lastconfig['dry_run_wallet'] = btconfig.get('dry_run_wallet')
+
+            ApiServer._bt.results = {}
+            ApiServer._bt.load_prior_backtest()
+
             ApiServer._bt.abort = False
-            min_date, max_date = ApiServer._bt.backtest_one_strategy(
-                strat, ApiServer._bt_data, ApiServer._bt_timerange)
-            ApiServer._bt.results = generate_backtest_stats(
-                ApiServer._bt_data, ApiServer._bt.all_results,
-                min_date=min_date, max_date=max_date)
+            if (ApiServer._bt.results and
+                    strat.get_strategy_name() in ApiServer._bt.results['strategy']):
+                # When previous result hash matches - reuse that result and skip backtesting.
+                logger.info(f'Reusing result of previous backtest for {strat.get_strategy_name()}')
+            else:
+                min_date, max_date = ApiServer._bt.backtest_one_strategy(
+                    strat, ApiServer._bt_data, ApiServer._bt_timerange)
+
+                ApiServer._bt.results = generate_backtest_stats(
+                    ApiServer._bt_data, ApiServer._bt.all_results,
+                    min_date=min_date, max_date=max_date)
+
+            if btconfig.get('export', 'none') == 'trades':
+                store_backtest_stats(btconfig['exportfilename'], ApiServer._bt.results)
+
             logger.info("Backtest finished.")
 
         except DependencyException as e:
@@ -98,7 +124,7 @@ async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: Bac
 
 
 @router.get('/backtest', response_model=BacktestResponse, tags=['webserver', 'backtest'])
-def api_get_backtest():
+def api_get_backtest(ws_mode=Depends(is_webserver_mode)):
     """
     Get backtesting result.
     Returns Result after backtesting has been ran.
@@ -134,7 +160,7 @@ def api_get_backtest():
 
 
 @router.delete('/backtest', response_model=BacktestResponse, tags=['webserver', 'backtest'])
-def api_delete_backtest():
+def api_delete_backtest(ws_mode=Depends(is_webserver_mode)):
     """Reset backtesting"""
     if ApiServer._bgtask_running:
         return {
@@ -160,7 +186,7 @@ def api_delete_backtest():
 
 
 @router.get('/backtest/abort', response_model=BacktestResponse, tags=['webserver', 'backtest'])
-def api_backtest_abort():
+def api_backtest_abort(ws_mode=Depends(is_webserver_mode)):
     if not ApiServer._bgtask_running:
         return {
             "status": "not_running",
@@ -177,3 +203,30 @@ def api_backtest_abort():
         "progress": 0,
         "status_msg": "Backtest ended",
     }
+
+
+@router.get('/backtest/history', response_model=List[BacktestHistoryEntry], tags=['webserver', 'backtest'])
+def api_backtest_history(config=Depends(get_config), ws_mode=Depends(is_webserver_mode)):
+    # Get backtest result history, read from metadata files
+    return get_backtest_resultlist(config['user_data_dir'] / 'backtest_results')
+
+
+@router.get('/backtest/history/result', response_model=BacktestResponse, tags=['webserver', 'backtest'])
+def api_backtest_history_result(filename: str, strategy: str, config=Depends(get_config), ws_mode=Depends(is_webserver_mode)):
+    # Get backtest result history, read from metadata files
+    fn = config['user_data_dir'] / 'backtest_results' / filename
+    results: Dict[str, Any] = {
+        'metadata': {},
+        'strategy': {},
+        'strategy_comparison': [],
+    }
+
+    load_and_merge_backtest_result(strategy, fn, results)
+    return {
+        "status": "ended",
+        "running": False,
+        "step": "",
+        "progress": 1,
+        "status_msg": "Historic result",
+        "backtest_result": results,
+    }
diff --git a/freqtrade/rpc/api_server/api_schemas.py b/freqtrade/rpc/api_server/api_schemas.py
index 46187f571..a9135cce2 100644
--- a/freqtrade/rpc/api_server/api_schemas.py
+++ b/freqtrade/rpc/api_server/api_schemas.py
@@ -4,6 +4,7 @@ from typing import Any, Dict, List, Optional, Union
 from pydantic import BaseModel
 
 from freqtrade.constants import DATETIME_PRINT_FORMAT
+from freqtrade.enums import OrderTypeValues, SignalDirection, TradingMode
 
 
 class Ping(BaseModel):
@@ -37,6 +38,11 @@ class Balance(BaseModel):
     used: float
     est_stake: float
     stake: str
+    # Starting with 2.x
+    side: str
+    leverage: float
+    is_position: bool
+    position: float
 
 
 class Balances(BaseModel):
@@ -63,6 +69,8 @@ class Count(BaseModel):
 class PerformanceEntry(BaseModel):
     pair: str
     profit: float
+    profit_ratio: float
+    profit_pct: float
     profit_abs: float
     count: int
 
@@ -93,6 +101,7 @@ class Profit(BaseModel):
     avg_duration: str
     best_pair: str
     best_rate: float
+    best_pair_profit_ratio: float
     winning_trades: int
     losing_trades: int
 
@@ -104,8 +113,8 @@ class SellReason(BaseModel):
 
 
 class Stats(BaseModel):
-    sell_reasons: Dict[str, SellReason]
-    durations: Dict[str, Union[str, float]]
+    exit_reasons: Dict[str, SellReason]
+    durations: Dict[str, Optional[float]]
 
 
 class DailyRecord(BaseModel):
@@ -121,10 +130,33 @@ class Daily(BaseModel):
     stake_currency: str
 
 
+class UnfilledTimeout(BaseModel):
+    entry: Optional[int]
+    exit: Optional[int]
+    unit: Optional[str]
+    exit_timeout_count: Optional[int]
+
+
+class OrderTypes(BaseModel):
+    entry: OrderTypeValues
+    exit: OrderTypeValues
+    emergency_exit: Optional[OrderTypeValues]
+    force_exit: Optional[OrderTypeValues]
+    force_entry: Optional[OrderTypeValues]
+    stoploss: OrderTypeValues
+    stoploss_on_exchange: bool
+    stoploss_on_exchange_interval: Optional[int]
+
+
 class ShowConfig(BaseModel):
+    version: str
+    strategy_version: Optional[str]
+    api_version: float
     dry_run: bool
+    trading_mode: str
+    short_allowed: bool
     stake_currency: str
-    stake_amount: Union[float, str]
+    stake_amount: str
     available_capital: Optional[float]
     stake_currency_decimals: int
     max_open_trades: int
@@ -134,30 +166,54 @@ class ShowConfig(BaseModel):
     trailing_stop_positive: Optional[float]
     trailing_stop_positive_offset: Optional[float]
     trailing_only_offset_is_reached: Optional[bool]
+    unfilledtimeout: UnfilledTimeout
+    order_types: Optional[OrderTypes]
     use_custom_stoploss: Optional[bool]
     timeframe: Optional[str]
     timeframe_ms: int
     timeframe_min: int
     exchange: str
     strategy: Optional[str]
-    forcebuy_enabled: bool
-    ask_strategy: Dict[str, Any]
-    bid_strategy: Dict[str, Any]
+    force_entry_enable: bool
+    exit_pricing: Dict[str, Any]
+    entry_pricing: Dict[str, Any]
     bot_name: str
     state: str
     runmode: str
+    position_adjustment_enable: bool
+    max_entry_position_adjustment: int
+
+
+class OrderSchema(BaseModel):
+    pair: str
+    order_id: str
+    status: str
+    remaining: float
+    amount: float
+    safe_price: float
+    cost: float
+    filled: float
+    ft_order_side: str
+    order_type: str
+    is_open: bool
+    order_timestamp: Optional[int]
+    order_filled_timestamp: Optional[int]
 
 
 class TradeSchema(BaseModel):
     trade_id: int
     pair: str
+    base_currency: str
+    quote_currency: str
     is_open: bool
+    is_short: bool
     exchange: str
     amount: float
     amount_requested: float
     stake_amount: float
     strategy: str
-    buy_tag: Optional[str]
+    buy_tag: Optional[str]  # Deprecated
+    enter_tag: Optional[str]
     timeframe: int
     fee_open: Optional[float]
     fee_open_cost: Optional[float]
@@ -181,8 +237,9 @@ class TradeSchema(BaseModel):
     profit_pct: Optional[float]
     profit_abs: Optional[float]
     profit_fiat: Optional[float]
-    sell_reason: Optional[str]
-    sell_order_status: Optional[str]
+    sell_reason: Optional[str]  # Deprecated
+    exit_reason: Optional[str]
+    exit_order_status: Optional[str]
     stop_loss_abs: Optional[float]
     stop_loss_ratio: Optional[float]
     stop_loss_pct: Optional[float]
@@ -195,6 +252,12 @@ class TradeSchema(BaseModel):
     min_rate: Optional[float]
     max_rate: Optional[float]
     open_order_id: Optional[str]
+    orders: List[OrderSchema]
+
+    leverage: Optional[float]
+    interest_rate: Optional[float]
+    funding_fees: Optional[float]
+    trading_mode: Optional[TradingMode]
 
 
 class OpenTradeSchema(TradeSchema):
@@ -216,7 +279,7 @@ class TradeResponse(BaseModel):
     total_trades: int
 
 
-class ForceBuyResponse(BaseModel):
+class ForceEnterResponse(BaseModel):
     __root__: Union[TradeSchema, StatusMsg]
 
 
@@ -246,13 +309,18 @@ class Logs(BaseModel):
     logs: List[List]
 
 
-class ForceBuyPayload(BaseModel):
+class ForceEnterPayload(BaseModel):
     pair: str
+    side: SignalDirection = SignalDirection.LONG
     price: Optional[float]
+    ordertype: Optional[OrderTypeValues]
+    stakeamount: Optional[float]
+    entry_tag: Optional[str]
 
 
-class ForceSellPayload(BaseModel):
+class ForceExitPayload(BaseModel):
     tradeid: str
+    ordertype: Optional[OrderTypeValues]
 
 
 class BlacklistPayload(BaseModel):
@@ -314,6 +382,10 @@ class PairHistory(BaseModel):
     length: int
     buy_signals: int
     sell_signals: int
+    enter_long_signals: int
+    exit_long_signals: int
+    enter_short_signals: int
+    exit_short_signals: int
     last_analyzed: datetime
     last_analyzed_ts: int
     data_start_ts: int
@@ -333,7 +405,7 @@ class BacktestRequest(BaseModel):
     timeframe_detail: Optional[str]
     timerange: Optional[str]
     max_open_trades: Optional[int]
-    stake_amount: Optional[Union[float, str]]
+    stake_amount: Optional[str]
     enable_protections: bool
     dry_run_wallet: Optional[float]
 
@@ -347,3 +419,20 @@ class BacktestResponse(BaseModel):
     trade_count: Optional[float]
     # TODO: Properly type backtestresult...
     backtest_result: Optional[Dict[str, Any]]
+
+
+class BacktestHistoryEntry(BaseModel):
+    filename: str
+    strategy: str
+    run_id: str
+    backtest_start_time: int
+
+
+class SysInfo(BaseModel):
+    cpu_pct: List[float]
+    ram_pct: float
+
+
+class Health(BaseModel):
+    last_process: datetime
+    last_process_ts: int
diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py
index 7e613f184..5021c99f9 100644
--- a/freqtrade/rpc/api_server/api_v1.py
+++ b/freqtrade/rpc/api_server/api_v1.py
@@ -3,28 +3,41 @@ from copy import deepcopy
 from pathlib import Path
 from typing import List, Optional
 
-from fastapi import APIRouter, Depends
+from fastapi import APIRouter, Depends, Query
 from fastapi.exceptions import HTTPException
 
 from freqtrade import __version__
 from freqtrade.constants import USERPATH_STRATEGIES
 from freqtrade.data.history import get_datahandler
+from freqtrade.enums import CandleType, TradingMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.rpc import RPC
 from freqtrade.rpc.api_server.api_schemas import (AvailablePairs, Balances, BlacklistPayload,
                                                   BlacklistResponse, Count, Daily,
-                                                  DeleteLockRequest, DeleteTrade, ForceBuyPayload,
-                                                  ForceBuyResponse, ForceSellPayload, Locks, Logs,
-                                                  OpenTradeSchema, PairHistory, PerformanceEntry,
-                                                  Ping, PlotConfig, Profit, ResultMsg, ShowConfig,
-                                                  Stats, StatusMsg, StrategyListResponse,
-                                                  StrategyResponse, Version, WhitelistResponse)
-from freqtrade.rpc.api_server.deps import get_config, get_rpc, get_rpc_optional
+                                                  DeleteLockRequest, DeleteTrade, ForceEnterPayload,
+                                                  ForceEnterResponse, ForceExitPayload, Health,
+                                                  Locks, Logs, OpenTradeSchema, PairHistory,
+                                                  PerformanceEntry, Ping, PlotConfig, Profit,
+                                                  ResultMsg, ShowConfig, Stats, StatusMsg,
+                                                  StrategyListResponse, StrategyResponse, SysInfo,
+                                                  Version, WhitelistResponse)
+from freqtrade.rpc.api_server.deps import get_config, get_exchange, get_rpc, get_rpc_optional
 from freqtrade.rpc.rpc import RPCException
 
 
 logger = logging.getLogger(__name__)
 
+# API version
+# Pre-1.1, no version was provided
+# Version increments should happen in "small" steps (1.1, 1.12, ...) unless big changes happen.
+# 1.11: forcebuy and forcesell accept ordertype
+# 1.12: add blacklist delete endpoint
+# 1.13: forcebuy supports stake_amount
+# versions 2.xx -> futures/short branch
+# 2.14: Add entry/exit orders to trade response
+# 2.15: Add backtest history endpoints
+API_VERSION = 2.15
+
 # Public API, requires no auth.
 router_public = APIRouter()
 # Private API, protected by authentication
@@ -114,24 +127,40 @@ def edge(rpc: RPC = Depends(get_rpc)):
 @router.get('/show_config', response_model=ShowConfig, tags=['info'])
 def show_config(rpc: Optional[RPC] = Depends(get_rpc_optional), config=Depends(get_config)):
     state = ''
+    strategy_version = None
     if rpc:
         state = rpc._freqtrade.state
-    return RPC._rpc_show_config(config, state)
+        strategy_version = rpc._freqtrade.strategy.version()
+    resp = RPC._rpc_show_config(config, state, strategy_version)
+    resp['api_version'] = API_VERSION
+    return resp
 
 
-@router.post('/forcebuy', response_model=ForceBuyResponse, tags=['trading'])
-def forcebuy(payload: ForceBuyPayload, rpc: RPC = Depends(get_rpc)):
-    trade = rpc._rpc_forcebuy(payload.pair, payload.price)
+# /forcebuy is deprecated with short addition. use /forceentry instead
+@router.post('/forceenter', response_model=ForceEnterResponse, tags=['trading'])
+@router.post('/forcebuy', response_model=ForceEnterResponse, tags=['trading'])
+def force_entry(payload: ForceEnterPayload, rpc: RPC = Depends(get_rpc)):
+    ordertype = payload.ordertype.value if payload.ordertype else None
+    stake_amount = payload.stakeamount if payload.stakeamount else None
+    entry_tag = payload.entry_tag if payload.entry_tag else 'force_entry'
+
+    trade = rpc._rpc_force_entry(payload.pair, payload.price, order_side=payload.side,
+                                 order_type=ordertype, stake_amount=stake_amount,
+                                 enter_tag=entry_tag)
 
     if trade:
-        return ForceBuyResponse.parse_obj(trade.to_json())
+        return ForceEnterResponse.parse_obj(trade.to_json())
     else:
-        return ForceBuyResponse.parse_obj({"status": f"Error buying pair {payload.pair}."})
+        return ForceEnterResponse.parse_obj(
+            {"status": f"Error entering {payload.side} trade for pair {payload.pair}."})
 
 
+# /forcesell is deprecated with short addition. use /forceexit instead
+@router.post('/forceexit', response_model=ResultMsg, tags=['trading'])
 @router.post('/forcesell', response_model=ResultMsg, tags=['trading'])
-def forcesell(payload: ForceSellPayload, rpc: RPC = Depends(get_rpc)):
-    return rpc._rpc_forcesell(payload.tradeid)
+def forceexit(payload: ForceExitPayload, rpc: RPC = Depends(get_rpc)):
+    ordertype = payload.ordertype.value if payload.ordertype else None
+    return rpc._rpc_force_exit(payload.tradeid, ordertype)
 
 
 @router.get('/blacklist', response_model=BlacklistResponse, tags=['info', 'pairlist'])
@@ -144,6 +173,13 @@ def blacklist_post(payload: BlacklistPayload, rpc: RPC = Depends(get_rpc)):
     return rpc._rpc_blacklist(payload.blacklist)
 
 
+@router.delete('/blacklist', response_model=BlacklistResponse, tags=['info', 'pairlist'])
+def blacklist_delete(pairs_to_delete: List[str] = Query([]), rpc: RPC = Depends(get_rpc)):
+    """Provide a list of pairs to delete from the blacklist"""
+
+    return rpc._rpc_blacklist_delete(pairs_to_delete)
+
+
 @router.get('/whitelist', response_model=WhitelistResponse, tags=['info', 'pairlist'])
 def whitelist(rpc: RPC = Depends(get_rpc)):
     return rpc._rpc_whitelist()
@@ -190,18 +226,21 @@ def reload_config(rpc: RPC = Depends(get_rpc)):
 
 
 @router.get('/pair_candles', response_model=PairHistory, tags=['candle data'])
-def pair_candles(pair: str, timeframe: str, limit: Optional[int], rpc: RPC = Depends(get_rpc)):
+def pair_candles(
+        pair: str, timeframe: str, limit: Optional[int] = None, rpc: RPC = Depends(get_rpc)):
     return rpc._rpc_analysed_dataframe(pair, timeframe, limit)
 
 
 @router.get('/pair_history', response_model=PairHistory, tags=['candle data'])
 def pair_history(pair: str, timeframe: str, timerange: str, strategy: str,
-                 config=Depends(get_config)):
+                 config=Depends(get_config), exchange=Depends(get_exchange)):
+    # The initial call to this endpoint can be slow, as it may need to initialize
+    # the exchange class.
     config = deepcopy(config)
     config.update({
         'strategy': strategy,
     })
-    return RPC._rpc_analysed_history_full(config, pair, timeframe, timerange)
+    return RPC._rpc_analysed_history_full(config, pair, timeframe, timerange, exchange)
 
 
 @router.get('/plot_config', response_model=PlotConfig, tags=['candle data'])
@@ -239,16 +278,22 @@ def get_strategy(strategy: str, config=Depends(get_config)):
 
 @router.get('/available_pairs', response_model=AvailablePairs, tags=['candle data'])
 def list_available_pairs(timeframe: Optional[str] = None, stake_currency: Optional[str] = None,
-                         config=Depends(get_config)):
+                         candletype: Optional[CandleType] = None, config=Depends(get_config)):
 
     dh = get_datahandler(config['datadir'], config.get('dataformat_ohlcv', None))
-
-    pair_interval = dh.ohlcv_get_available_data(config['datadir'])
+    trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT)
+    pair_interval = dh.ohlcv_get_available_data(config['datadir'], trading_mode)
 
     if timeframe:
         pair_interval = [pair for pair in pair_interval if pair[1] == timeframe]
     if stake_currency:
         pair_interval = [pair for pair in pair_interval if pair[0].endswith(stake_currency)]
+    if candletype:
+        pair_interval = [pair for pair in pair_interval if pair[2] == candletype]
+    else:
+        candle_type = CandleType.get_default(trading_mode)
+        pair_interval = [pair for pair in pair_interval if pair[2] == candle_type]
+
     pair_interval = sorted(pair_interval, key=lambda x: x[0])
 
     pairs = list({x[0] for x in pair_interval})
@@ -259,3 +304,13 @@ def list_available_pairs(timeframe: Optional[str] = None, stake_currency: Option
         'pair_interval': pair_interval,
     }
     return result
+
+
+@router.get('/sysinfo', response_model=SysInfo, tags=['info'])
+def sysinfo():
+    return RPC._rpc_sysinfo()
+
+
+@router.get('/health', response_model=Health, tags=['info'])
+def health(rpc: RPC = Depends(get_rpc)):
+    return rpc._health()
diff --git a/freqtrade/rpc/api_server/deps.py b/freqtrade/rpc/api_server/deps.py
index d2459010f..f5e61602e 100644
--- a/freqtrade/rpc/api_server/deps.py
+++ b/freqtrade/rpc/api_server/deps.py
@@ -1,5 +1,9 @@
-from typing import Any, Dict, Optional
+from typing import Any, Dict, Iterator, Optional
 
+from fastapi import Depends
+
+from freqtrade.enums import RunMode
+from freqtrade.persistence import Trade
 from freqtrade.rpc.rpc import RPC, RPCException
 
 from .webserver import ApiServer
@@ -11,10 +15,12 @@ def get_rpc_optional() -> Optional[RPC]:
     return None
 
 
-def get_rpc() -> Optional[RPC]:
+def get_rpc() -> Optional[Iterator[RPC]]:
     _rpc = get_rpc_optional()
     if _rpc:
-        return _rpc
+        Trade.query.session.rollback()
+        yield _rpc
+        Trade.query.session.rollback()
     else:
         raise RPCException('Bot is not in the correct state')
 
@@ -25,3 +31,17 @@ def get_config() -> Dict[str, Any]:
 
 def get_api_config() -> Dict[str, Any]:
     return ApiServer._config['api_server']
+
+
+def get_exchange(config=Depends(get_config)):
+    if not ApiServer._exchange:
+        from freqtrade.resolvers import ExchangeResolver
+        ApiServer._exchange = ExchangeResolver.load_exchange(
+            config['exchange']['name'], config)
+    return ApiServer._exchange
+
+
+def is_webserver_mode(config=Depends(get_config)):
+    if config['runmode'] != RunMode.WEBSERVER:
+        raise RPCException('Bot is not in the correct state')
+    return None
diff --git a/freqtrade/rpc/api_server/uvicorn_threaded.py b/freqtrade/rpc/api_server/uvicorn_threaded.py
index 79af659c7..a79c1a5fc 100644
--- a/freqtrade/rpc/api_server/uvicorn_threaded.py
+++ b/freqtrade/rpc/api_server/uvicorn_threaded.py
@@ -47,7 +47,7 @@ class UvicornServer(uvicorn.Server):
         else:
             asyncio.set_event_loop(uvloop.new_event_loop())
         try:
-            loop = asyncio.get_event_loop()
+            loop = asyncio.get_running_loop()
         except RuntimeError:
             # When running in a thread, we'll not have an eventloop yet.
             loop = asyncio.new_event_loop()
diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py
index 235063191..63812f52f 100644
--- a/freqtrade/rpc/api_server/webserver.py
+++ b/freqtrade/rpc/api_server/webserver.py
@@ -41,6 +41,8 @@ class ApiServer(RPCHandler):
     _has_rpc: bool = False
     _bgtask_running: bool = False
     _config: Dict[str, Any] = {}
+    # Exchange - only available in webserver mode.
+    _exchange = None
 
     def __new__(cls, *args, **kwargs):
         """
diff --git a/freqtrade/rpc/fiat_convert.py b/freqtrade/rpc/fiat_convert.py
index f4e82261e..df33693ac 100644
--- a/freqtrade/rpc/fiat_convert.py
+++ b/freqtrade/rpc/fiat_convert.py
@@ -7,7 +7,7 @@ import datetime
 import logging
 from typing import Dict, List
 
-from cachetools.ttl import TTLCache
+from cachetools import TTLCache
 from pycoingecko import CoinGeckoAPI
 from requests.exceptions import RequestException
 
@@ -17,6 +17,16 @@ from freqtrade.constants import SUPPORTED_FIAT
 logger = logging.getLogger(__name__)
 
 
+# Manually map symbol to ID for some common coins
+# with duplicate coingecko entries
+coingecko_mapping = {
+    'eth': 'ethereum',
+    'bnb': 'binancecoin',
+    'sol': 'solana',
+    'usdt': 'tether',
+}
+
+
 class CryptoToFiatConverter:
     """
     Main class to initiate Crypto to FIAT.
@@ -53,7 +63,7 @@ class CryptoToFiatConverter:
         except RequestException as request_exception:
             if "429" in str(request_exception):
                 logger.warning(
-                    "Too many requests for Coingecko API, backing off and trying again later.")
+                    "Too many requests for CoinGecko API, backing off and trying again later.")
                 # Set backoff timestamp to 60 seconds in the future
                 self._backoff = datetime.datetime.now().timestamp() + 60
                 return
@@ -76,13 +86,17 @@ class CryptoToFiatConverter:
                     return None
             else:
                 return None
-        found = [x for x in self._coinlistings if x['symbol'] == crypto_symbol]
+        found = [x for x in self._coinlistings if x['symbol'].lower() == crypto_symbol]
+
+        if crypto_symbol in coingecko_mapping.keys():
+            found = [x for x in self._coinlistings if x['id'] == coingecko_mapping[crypto_symbol]]
+
         if len(found) == 1:
             return found[0]['id']
 
         if len(found) > 0:
             # Wrong!
-            logger.warning(f"Found multiple mappings in goingekko for {crypto_symbol}.")
+            logger.warning(f"Found multiple mappings in CoinGecko for {crypto_symbol}.")
             return None
 
     def convert_amount(self, crypto_amount: float, crypto_symbol: str, fiat_symbol: str) -> float:
@@ -146,7 +160,7 @@ class CryptoToFiatConverter:
 
     def _find_price(self, crypto_symbol: str, fiat_symbol: str) -> float:
         """
-        Call CoinGekko API to retrieve the price in the FIAT
+        Call CoinGecko API to retrieve the price in the FIAT
         :param crypto_symbol: Crypto-currency you want to convert (e.g btc)
         :param fiat_symbol: FIAT currency you want to convert to (e.g usd)
         :return: float, price of the crypto-currency in Fiat
diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index f6599b429..12adc34d1 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -8,13 +8,18 @@ from math import isnan
 from typing import Any, Dict, List, Optional, Tuple, Union
 
 import arrow
+import psutil
+from dateutil.relativedelta import relativedelta
+from dateutil.tz import tzlocal
 from numpy import NAN, inf, int64, mean
-from pandas import DataFrame
+from pandas import DataFrame, NaT
 
+from freqtrade import __version__
 from freqtrade.configuration.timerange import TimeRange
 from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT
 from freqtrade.data.history import load_data
-from freqtrade.enums import SellType, State
+from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, State,
+                             TradingMode)
 from freqtrade.exceptions import ExchangeError, PricingError
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs
 from freqtrade.loggers import bufferHandler
@@ -23,7 +28,7 @@ from freqtrade.persistence import PairLocks, Trade
 from freqtrade.persistence.models import PairLock
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
-from freqtrade.strategy.interface import SellCheckTuple
+from freqtrade.wallets import PositionWallet, Wallet
 
 
 logger = logging.getLogger(__name__)
@@ -95,17 +100,22 @@ class RPC:
             self._fiat_converter = CryptoToFiatConverter()
 
     @staticmethod
-    def _rpc_show_config(config, botstate: Union[State, str]) -> Dict[str, Any]:
+    def _rpc_show_config(config, botstate: Union[State, str],
+                         strategy_version: Optional[str] = None) -> Dict[str, Any]:
         """
         Return a dict of config options.
         Explicitly does NOT return the full config to avoid leakage of sensitive
         information via rpc.
         """
         val = {
+            'version': __version__,
+            'strategy_version': strategy_version,
             'dry_run': config['dry_run'],
+            'trading_mode': config.get('trading_mode', 'spot'),
+            'short_allowed': config.get('trading_mode', 'spot') != 'spot',
             'stake_currency': config['stake_currency'],
-            'stake_currency_decimals':  decimals_per_coin(config['stake_currency']),
-            'stake_amount': config['stake_amount'],
+            'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
+            'stake_amount': str(config['stake_amount']),
             'available_capital': config.get('available_capital'),
             'max_open_trades': (config['max_open_trades']
                                 if config['max_open_trades'] != float('inf') else -1),
@@ -115,7 +125,9 @@ class RPC:
             'trailing_stop_positive': config.get('trailing_stop_positive'),
             'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset'),
             'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached'),
+            'unfilledtimeout': config.get('unfilledtimeout'),
             'use_custom_stoploss': config.get('use_custom_stoploss'),
+            'order_types': config.get('order_types'),
             'bot_name': config.get('bot_name', 'freqtrade'),
             'timeframe': config.get('timeframe'),
             'timeframe_ms': timeframe_to_msecs(config['timeframe']
@@ -124,11 +136,16 @@ class RPC:
                                                   ) if 'timeframe' in config else 0,
             'exchange': config['exchange']['name'],
             'strategy': config['strategy'],
-            'forcebuy_enabled': config.get('forcebuy_enable', False),
-            'ask_strategy': config.get('ask_strategy', {}),
-            'bid_strategy': config.get('bid_strategy', {}),
+            'force_entry_enable': config.get('force_entry_enable', False),
+            'exit_pricing': config.get('exit_pricing', {}),
+            'entry_pricing': config.get('entry_pricing', {}),
             'state': str(botstate),
-            'runmode': config['runmode'].value
+            'runmode': config['runmode'].value,
+            'position_adjustment_enable': config.get('position_adjustment_enable', False),
+            'max_entry_position_adjustment': (
+                config.get('max_entry_position_adjustment', -1)
+                if config.get('max_entry_position_adjustment') != float('inf')
+                else -1)
         }
         return val
 
@@ -139,7 +156,7 @@ class RPC:
         """
         # Fetch open trades
         if trade_ids:
-            trades = Trade.get_trades(trade_filter=Trade.id.in_(trade_ids)).all()
+            trades: List[Trade] = Trade.get_trades(trade_filter=Trade.id.in_(trade_ids)).all()
         else:
             trades = Trade.get_open_trades()
 
@@ -155,7 +172,7 @@ class RPC:
                 if trade.is_open:
                     try:
                         current_rate = self._freqtrade.exchange.get_rate(
-                            trade.pair, refresh=False, side="sell")
+                            trade.pair, side='exit', is_short=trade.is_short, refresh=False)
                     except (ExchangeError, PricingError):
                         current_rate = NAN
                 else:
@@ -180,7 +197,6 @@ class RPC:
 
                 trade_dict = trade.to_json()
                 trade_dict.update(dict(
-                    base_currency=self._freqtrade.config['stake_currency'],
                     close_profit=trade.close_profit if trade.close_profit is not None else None,
                     current_rate=current_rate,
                     current_profit=current_profit,  # Deprecated
@@ -205,7 +221,8 @@ class RPC:
 
     def _rpc_status_table(self, stake_currency: str,
                           fiat_display_currency: str) -> Tuple[List, List, float]:
-        trades = Trade.get_open_trades()
+        trades: List[Trade] = Trade.get_open_trades()
+        nonspot = self._config.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT
         if not trades:
             raise RPCException('no active trade')
         else:
@@ -215,12 +232,12 @@ class RPC:
                 # calculate profit and send message to user
                 try:
                     current_rate = self._freqtrade.exchange.get_rate(
-                        trade.pair, refresh=False, side="sell")
+                        trade.pair, side='exit', is_short=trade.is_short, refresh=False)
                 except (PricingError, ExchangeError):
                     current_rate = NAN
-                trade_percent = (100 * trade.calc_profit_ratio(current_rate))
                 trade_profit = trade.calc_profit(current_rate)
-                profit_str = f'{trade_percent:.2f}%'
+                profit_str = f'{trade.calc_profit_ratio(current_rate):.2%}'
+                direction_str = ('S' if trade.is_short else 'L') if nonspot else ''
                 if self._fiat_converter:
                     fiat_profit = self._fiat_converter.convert_amount(
                         trade_profit,
@@ -231,25 +248,38 @@ class RPC:
                         profit_str += f" ({fiat_profit:.2f})"
                         fiat_profit_sum = fiat_profit if isnan(fiat_profit_sum) \
                             else fiat_profit_sum + fiat_profit
-                trades_list.append([
-                    trade.id,
+                detail_trade = [
+                    f'{trade.id} {direction_str}',
                     trade.pair + ('*' if (trade.open_order_id is not None
                                           and trade.close_rate_requested is None) else '')
-                               + ('**' if (trade.close_rate_requested is not None) else ''),
+                    + ('**' if (trade.close_rate_requested is not None) else ''),
                     shorten_date(arrow.get(trade.open_date).humanize(only_distance=True)),
                     profit_str
-                ])
+                ]
+                if self._config.get('position_adjustment_enable', False):
+                    max_entry_str = ''
+                    if self._config.get('max_entry_position_adjustment', -1) > 0:
+                        max_entry_str = f"/{self._config['max_entry_position_adjustment'] + 1}"
+                    filled_entries = trade.nr_of_successful_entries
+                    detail_trade.append(f"{filled_entries}{max_entry_str}")
+                trades_list.append(detail_trade)
             profitcol = "Profit"
             if self._fiat_converter:
                 profitcol += " (" + fiat_display_currency + ")"
 
-            columns = ['ID', 'Pair', 'Since', profitcol]
+            columns = [
+                'ID L/S' if nonspot else 'ID',
+                'Pair',
+                'Since',
+                profitcol]
+            if self._config.get('position_adjustment_enable', False):
+                columns.append('# Entries')
             return trades_list, columns, fiat_profit_sum
 
     def _rpc_daily_profit(
             self, timescale: int,
             stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
-        today = datetime.utcnow().date()
+        today = datetime.now(timezone.utc).date()
         profit_days: Dict[date, Dict] = {}
 
         if not (isinstance(timescale, int) and timescale > 0):
@@ -288,6 +318,91 @@ class RPC:
             'data': data
         }
 
+    def _rpc_weekly_profit(
+            self, timescale: int,
+            stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
+        today = datetime.now(timezone.utc).date()
+        first_iso_day_of_week = today - timedelta(days=today.weekday())  # Monday
+        profit_weeks: Dict[date, Dict] = {}
+
+        if not (isinstance(timescale, int) and timescale > 0):
+            raise RPCException('timescale must be an integer greater than 0')
+
+        for week in range(0, timescale):
+            profitweek = first_iso_day_of_week - timedelta(weeks=week)
+            trades = Trade.get_trades(trade_filter=[
+                Trade.is_open.is_(False),
+                Trade.close_date >= profitweek,
+                Trade.close_date < (profitweek + timedelta(weeks=1))
+            ]).order_by(Trade.close_date).all()
+            curweekprofit = sum(
+                trade.close_profit_abs for trade in trades if trade.close_profit_abs is not None)
+            profit_weeks[profitweek] = {
+                'amount': curweekprofit,
+                'trades': len(trades)
+            }
+
+        data = [
+            {
+                'date': key,
+                'abs_profit': value["amount"],
+                'fiat_value': self._fiat_converter.convert_amount(
+                    value['amount'],
+                    stake_currency,
+                    fiat_display_currency
+                ) if self._fiat_converter else 0,
+                'trade_count': value["trades"],
+            }
+            for key, value in profit_weeks.items()
+        ]
+        return {
+            'stake_currency': stake_currency,
+            'fiat_display_currency': fiat_display_currency,
+            'data': data
+        }
+
+    def _rpc_monthly_profit(
+            self, timescale: int,
+            stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
+        first_day_of_month = datetime.now(timezone.utc).date().replace(day=1)
+        profit_months: Dict[date, Dict] = {}
+
+        if not (isinstance(timescale, int) and timescale > 0):
+            raise RPCException('timescale must be an integer greater than 0')
+
+        for month in range(0, timescale):
+            profitmonth = first_day_of_month - relativedelta(months=month)
+            trades = Trade.get_trades(trade_filter=[
+                Trade.is_open.is_(False),
+                Trade.close_date >= profitmonth,
+                Trade.close_date < (profitmonth + relativedelta(months=1))
+            ]).order_by(Trade.close_date).all()
+            curmonthprofit = sum(
+                trade.close_profit_abs for trade in trades if trade.close_profit_abs is not None)
+            profit_months[profitmonth] = {
+                'amount': curmonthprofit,
+                'trades': len(trades)
+            }
+
+        data = [
+            {
+                'date': f"{key.year}-{key.month:02d}",
+                'abs_profit': value["amount"],
+                'fiat_value': self._fiat_converter.convert_amount(
+                    value['amount'],
+                    stake_currency,
+                    fiat_display_currency
+                ) if self._fiat_converter else 0,
+                'trade_count': value["trades"],
+            }
+            for key, value in profit_months.items()
+        ]
+        return {
+            'stake_currency': stake_currency,
+            'fiat_display_currency': fiat_display_currency,
+            'data': data
+        }
+
     def _rpc_trade_history(self, limit: int, offset: int = 0, order_by_id: bool = False) -> Dict:
         """ Returns the X last trades """
         order_by = Trade.id if order_by_id else Trade.close_date.desc()
@@ -317,13 +432,13 @@ class RPC:
                 return 'losses'
             else:
                 return 'draws'
-        trades = trades = Trade.get_trades([Trade.is_open.is_(False)])
+        trades: List[Trade] = Trade.get_trades([Trade.is_open.is_(False)])
         # Sell reason
-        sell_reasons = {}
+        exit_reasons = {}
         for trade in trades:
-            if trade.sell_reason not in sell_reasons:
-                sell_reasons[trade.sell_reason] = {'wins': 0, 'losses': 0, 'draws': 0}
-            sell_reasons[trade.sell_reason][trade_win_loss(trade)] += 1
+            if trade.exit_reason not in exit_reasons:
+                exit_reasons[trade.exit_reason] = {'wins': 0, 'losses': 0, 'draws': 0}
+            exit_reasons[trade.exit_reason][trade_win_loss(trade)] += 1
 
         # Duration
         dur: Dict[str, List[int]] = {'wins': [], 'draws': [], 'losses': []}
@@ -332,12 +447,12 @@ class RPC:
                 trade_dur = (trade.close_date - trade.open_date).total_seconds()
                 dur[trade_win_loss(trade)].append(trade_dur)
 
-        wins_dur = sum(dur['wins']) / len(dur['wins']) if len(dur['wins']) > 0 else 'N/A'
-        draws_dur = sum(dur['draws']) / len(dur['draws']) if len(dur['draws']) > 0 else 'N/A'
-        losses_dur = sum(dur['losses']) / len(dur['losses']) if len(dur['losses']) > 0 else 'N/A'
+        wins_dur = sum(dur['wins']) / len(dur['wins']) if len(dur['wins']) > 0 else None
+        draws_dur = sum(dur['draws']) / len(dur['draws']) if len(dur['draws']) > 0 else None
+        losses_dur = sum(dur['losses']) / len(dur['losses']) if len(dur['losses']) > 0 else None
 
         durations = {'wins': wins_dur, 'draws': draws_dur, 'losses': losses_dur}
-        return {'sell_reasons': sell_reasons, 'durations': durations}
+        return {'exit_reasons': exit_reasons, 'durations': durations}
 
     def _rpc_trade_statistics(
             self, stake_currency: str, fiat_display_currency: str,
@@ -345,7 +460,7 @@ class RPC:
         """ Returns cumulative profit statistics """
         trade_filter = ((Trade.is_open.is_(False) & (Trade.close_date >= start_date)) |
                         Trade.is_open.is_(True))
-        trades = Trade.get_trades(trade_filter).order_by(Trade.id).all()
+        trades: List[Trade] = Trade.get_trades(trade_filter).order_by(Trade.id).all()
 
         profit_all_coin = []
         profit_all_ratio = []
@@ -375,7 +490,7 @@ class RPC:
                 # Get current rate
                 try:
                     current_rate = self._freqtrade.exchange.get_rate(
-                        trade.pair, refresh=False, side="sell")
+                        trade.pair, side='exit', is_short=trade.is_short, refresh=False)
                 except (PricingError, ExchangeError):
                     current_rate = NAN
                 profit_ratio = trade.calc_profit_ratio(rate=current_rate)
@@ -443,14 +558,15 @@ class RPC:
             'latest_trade_timestamp': int(last_date.timestamp() * 1000) if last_date else 0,
             'avg_duration': str(timedelta(seconds=sum(durations) / num)).split('.')[0],
             'best_pair': best_pair[0] if best_pair else '',
-            'best_rate': round(best_pair[1] * 100, 2) if best_pair else 0,
+            'best_rate': round(best_pair[1] * 100, 2) if best_pair else 0,  # Deprecated
+            'best_pair_profit_ratio': best_pair[1] if best_pair else 0,
             'winning_trades': winning_trades,
             'losing_trades': losing_trades,
         }
 
     def _rpc_balance(self, stake_currency: str, fiat_display_currency: str) -> Dict:
         """ Returns current account balance per crypto """
-        output = []
+        currencies = []
         total = 0.0
         try:
             tickers = self._freqtrade.exchange.get_tickers(cached=True)
@@ -461,7 +577,8 @@ class RPC:
         starting_capital = self._freqtrade.wallets.get_starting_balance()
         starting_cap_fiat = self._fiat_converter.convert_amount(
             starting_capital, stake_currency, fiat_display_currency) if self._fiat_converter else 0
-
+        coin: str
+        balance: Wallet
         for coin, balance in self._freqtrade.wallets.get_all_balances().items():
             if not balance.total:
                 continue
@@ -470,10 +587,13 @@ class RPC:
             if coin == stake_currency:
                 rate = 1.0
                 est_stake = balance.total
+                if self._config.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
+                    # in Futures, "total" includes the locked stake, and therefore all positions
+                    est_stake = balance.free
             else:
                 try:
                     pair = self._freqtrade.exchange.get_valid_pair_combination(coin, stake_currency)
-                    rate = tickers.get(pair, {}).get('bid', None)
+                    rate = tickers.get(pair, {}).get('last', None)
                     if rate:
                         if pair.startswith(stake_currency) and not pair.endswith(stake_currency):
                             rate = 1.0 / rate
@@ -482,29 +602,47 @@ class RPC:
                     logger.warning(f" Could not get rate for pair {coin}.")
                     continue
             total = total + (est_stake or 0)
-            output.append({
+            currencies.append({
                 'currency': coin,
+                # TODO: The below can be simplified if we don't assign None to values.
                 'free': balance.free if balance.free is not None else 0,
                 'balance': balance.total if balance.total is not None else 0,
                 'used': balance.used if balance.used is not None else 0,
                 'est_stake': est_stake or 0,
                 'stake': stake_currency,
+                'side': 'long',
+                'leverage': 1,
+                'position': 0,
+                'is_position': False,
+            })
+        symbol: str
+        position: PositionWallet
+        for symbol, position in self._freqtrade.wallets.get_all_positions().items():
+            total += position.collateral
+
+            currencies.append({
+                'currency': symbol,
+                'free': 0,
+                'balance': 0,
+                'used': 0,
+                'position': position.position,
+                'est_stake': position.collateral,
+                'stake': stake_currency,
+                'leverage': position.leverage,
+                'side': position.side,
+                'is_position': True
             })
-        if total == 0.0:
-            if self._freqtrade.config['dry_run']:
-                raise RPCException('Running in Dry Run, balances are not available.')
-            else:
-                raise RPCException('All balances are zero.')
 
         value = self._fiat_converter.convert_amount(
             total, stake_currency, fiat_display_currency) if self._fiat_converter else 0
 
+        trade_count = len(Trade.get_trades_proxy())
         starting_capital_ratio = 0.0
         starting_capital_ratio = (total / starting_capital) - 1 if starting_capital else 0.0
         starting_cap_fiat_ratio = (value / starting_cap_fiat) - 1 if starting_cap_fiat else 0.0
 
         return {
-            'currencies': output,
+            'currencies': currencies,
             'total': total,
             'symbol': fiat_display_currency,
             'value': value,
@@ -515,6 +653,7 @@ class RPC:
             'starting_capital_fiat': starting_cap_fiat,
             'starting_capital_fiat_ratio': starting_cap_fiat_ratio,
             'starting_capital_fiat_pct': round(starting_cap_fiat_ratio * 100, 2),
+            'trade_count': trade_count,
             'note': 'Simulated balances' if self._freqtrade.config['dry_run'] else ''
         }
 
@@ -549,31 +688,35 @@ class RPC:
 
         return {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
 
-    def _rpc_forcesell(self, trade_id: str) -> Dict[str, str]:
+    def _rpc_force_exit(self, trade_id: str, ordertype: Optional[str] = None) -> Dict[str, str]:
         """
-        Handler for forcesell <id>.
+        Handler for forceexit <id>.
         Sells the given trade at current price
         """
-        def _exec_forcesell(trade: Trade) -> None:
+        def _exec_force_exit(trade: Trade) -> None:
             # Check if there is there is an open order
             fully_canceled = False
             if trade.open_order_id:
                 order = self._freqtrade.exchange.fetch_order(trade.open_order_id, trade.pair)
 
-                if order['side'] == 'buy':
+                if order['side'] == trade.entry_side:
                     fully_canceled = self._freqtrade.handle_cancel_enter(
-                        trade, order, CANCEL_REASON['FORCE_SELL'])
+                        trade, order, CANCEL_REASON['FORCE_EXIT'])
 
-                if order['side'] == 'sell':
+                if order['side'] == trade.exit_side:
                     # Cancel order - so it is placed anew with a fresh price.
-                    self._freqtrade.handle_cancel_exit(trade, order, CANCEL_REASON['FORCE_SELL'])
+                    self._freqtrade.handle_cancel_exit(trade, order, CANCEL_REASON['FORCE_EXIT'])
 
             if not fully_canceled:
                 # Get current rate and execute sell
                 current_rate = self._freqtrade.exchange.get_rate(
-                    trade.pair, refresh=False, side="sell")
-                sell_reason = SellCheckTuple(sell_type=SellType.FORCE_SELL)
-                self._freqtrade.execute_trade_exit(trade, current_rate, sell_reason)
+                    trade.pair, side='exit', is_short=trade.is_short, refresh=True)
+                exit_check = ExitCheckTuple(exit_type=ExitType.FORCE_EXIT)
+                order_type = ordertype or self._freqtrade.strategy.order_types.get(
+                    "force_exit", self._freqtrade.strategy.order_types["exit"])
+
+                self._freqtrade.execute_trade_exit(
+                    trade, current_rate, exit_check, ordertype=order_type)
         # ---- EOF def _exec_forcesell ----
 
         if self._freqtrade.state != State.RUNNING:
@@ -583,7 +726,7 @@ class RPC:
             if trade_id == 'all':
                 # Execute sell for all open orders
                 for trade in Trade.get_open_trades():
-                    _exec_forcesell(trade)
+                    _exec_force_exit(trade)
                 Trade.commit()
                 self._freqtrade.wallets.update()
                 return {'result': 'Created sell orders for all open trades.'}
@@ -593,26 +736,33 @@ class RPC:
                 trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True), ]
             ).first()
             if not trade:
-                logger.warning('forcesell: Invalid argument received')
+                logger.warning('force_exit: Invalid argument received')
                 raise RPCException('invalid argument')
 
-            _exec_forcesell(trade)
+            _exec_force_exit(trade)
             Trade.commit()
             self._freqtrade.wallets.update()
             return {'result': f'Created sell order for trade {trade_id}.'}
 
-    def _rpc_forcebuy(self, pair: str, price: Optional[float]) -> Optional[Trade]:
+    def _rpc_force_entry(self, pair: str, price: Optional[float], *,
+                         order_type: Optional[str] = None,
+                         order_side: SignalDirection = SignalDirection.LONG,
+                         stake_amount: Optional[float] = None,
+                         enter_tag: Optional[str] = 'force_entry') -> Optional[Trade]:
         """
         Handler for forcebuy <asset> <price>
         Buys a pair trade at the given or current price
         """
 
-        if not self._freqtrade.config.get('forcebuy_enable', False):
-            raise RPCException('Forcebuy not enabled.')
+        if not self._freqtrade.config.get('force_entry_enable', False):
+            raise RPCException('Force_entry not enabled.')
 
         if self._freqtrade.state != State.RUNNING:
             raise RPCException('trader is not running')
 
+        if order_side == SignalDirection.SHORT and self._freqtrade.trading_mode == TradingMode.SPOT:
+            raise RPCException("Can't go short on Spot markets.")
+
         # Check if pair quote currency equals to the stake currency.
         stake_currency = self._freqtrade.config.get('stake_currency')
         if not self._freqtrade.exchange.get_pair_quote_currency(pair) == stake_currency:
@@ -621,20 +771,31 @@ class RPC:
         # check if valid pair
 
         # check if pair already has an open pair
-        trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
+        trade: Trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
+        is_short = (order_side == SignalDirection.SHORT)
         if trade:
-            raise RPCException(f'position for {pair} already open - id: {trade.id}')
+            is_short = trade.is_short
+            if not self._freqtrade.strategy.position_adjustment_enable:
+                raise RPCException(f'position for {pair} already open - id: {trade.id}')
 
-        # gen stake amount
-        stakeamount = self._freqtrade.wallets.get_trade_stake_amount(pair)
+        if not stake_amount:
+            # gen stake amount
+            stake_amount = self._freqtrade.wallets.get_trade_stake_amount(pair)
 
         # execute buy
-        if self._freqtrade.execute_entry(pair, stakeamount, price, forcebuy=True):
+        if not order_type:
+            order_type = self._freqtrade.strategy.order_types.get(
+                'force_entry', self._freqtrade.strategy.order_types['entry'])
+        if self._freqtrade.execute_entry(pair, stake_amount, price,
+                                         ordertype=order_type, trade=trade,
+                                         is_short=is_short,
+                                         enter_tag=enter_tag,
+                                         ):
             Trade.commit()
             trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
             return trade
         else:
-            return None
+            raise RPCException(f'Failed to enter position for {pair}.')
 
     def _rpc_delete(self, trade_id: int) -> Dict[str, Union[str, int]]:
         """
@@ -681,10 +842,32 @@ class RPC:
         Shows a performance statistic from finished trades
         """
         pair_rates = Trade.get_overall_performance()
-        # Round and convert to %
-        [x.update({'profit': round(x['profit'] * 100, 2)}) for x in pair_rates]
+
         return pair_rates
 
+    def _rpc_enter_tag_performance(self, pair: Optional[str]) -> List[Dict[str, Any]]:
+        """
+        Handler for buy tag performance.
+        Shows a performance statistic from finished trades
+        """
+        return Trade.get_enter_tag_performance(pair)
+
+    def _rpc_exit_reason_performance(self, pair: Optional[str]) -> List[Dict[str, Any]]:
+        """
+        Handler for exit reason performance.
+        Shows a performance statistic from finished trades
+        """
+        return Trade.get_exit_reason_performance(pair)
+
+    def _rpc_mix_tag_performance(self, pair: Optional[str]) -> List[Dict[str, Any]]:
+        """
+        Handler for mix tag (enter_tag + exit_reason) performance.
+        Shows a performance statistic from finished trades
+        """
+        mix_tags = Trade.get_mix_tag_performance(pair)
+
+        return mix_tags
+
     def _rpc_count(self) -> Dict[str, float]:
         """ Returns the number of trades running """
         if self._freqtrade.state != State.RUNNING:
@@ -733,6 +916,20 @@ class RPC:
                }
         return res
 
+    def _rpc_blacklist_delete(self, delete: List[str]) -> Dict:
+        """ Removes pairs from currently active blacklist """
+        errors = {}
+        for pair in delete:
+            if pair in self._freqtrade.pairlists.blacklist:
+                self._freqtrade.pairlists.blacklist.remove(pair)
+            else:
+                errors[pair] = {
+                    'error_msg': f"Pair {pair} is not in the current blacklist."
+                    }
+        resp = self._rpc_blacklist()
+        resp['errors'] = errors
+        return resp
+
     def _rpc_blacklist(self, add: List[str] = None) -> Dict:
         """ Returns the currently active blacklist"""
         errors = {}
@@ -787,22 +984,31 @@ class RPC:
     def _convert_dataframe_to_dict(strategy: str, pair: str, timeframe: str, dataframe: DataFrame,
                                    last_analyzed: datetime) -> Dict[str, Any]:
         has_content = len(dataframe) != 0
-        buy_signals = 0
-        sell_signals = 0
+        signals = {
+            'enter_long': 0,
+            'exit_long': 0,
+            'enter_short': 0,
+            'exit_short': 0,
+        }
         if has_content:
 
             dataframe.loc[:, '__date_ts'] = dataframe.loc[:, 'date'].view(int64) // 1000 // 1000
-            # Move open to separate column when signal for easy plotting
-            if 'buy' in dataframe.columns:
-                buy_mask = (dataframe['buy'] == 1)
-                buy_signals = int(buy_mask.sum())
-                dataframe.loc[buy_mask, '_buy_signal_open'] = dataframe.loc[buy_mask, 'open']
-            if 'sell' in dataframe.columns:
-                sell_mask = (dataframe['sell'] == 1)
-                sell_signals = int(sell_mask.sum())
-                dataframe.loc[sell_mask, '_sell_signal_open'] = dataframe.loc[sell_mask, 'open']
-            dataframe = dataframe.replace([inf, -inf], NAN)
-            dataframe = dataframe.replace({NAN: None})
+            # Move signal close to separate column when signal for easy plotting
+            for sig_type in signals.keys():
+                if sig_type in dataframe.columns:
+                    mask = (dataframe[sig_type] == 1)
+                    signals[sig_type] = int(mask.sum())
+                    dataframe.loc[mask, f'_{sig_type}_signal_close'] = dataframe.loc[mask, 'close']
+
+            # band-aid until this is fixed:
+            # https://github.com/pandas-dev/pandas/issues/45836
+            datetime_types = ['datetime', 'datetime64', 'datetime64[ns, UTC]']
+            date_columns = dataframe.select_dtypes(include=datetime_types)
+            for date_column in date_columns:
+                # replace NaT with `None`
+                dataframe[date_column] = dataframe[date_column].astype(object).replace({NaT: None})
+
+            dataframe = dataframe.replace({inf: None, -inf: None, NAN: None})
 
         res = {
             'pair': pair,
@@ -812,8 +1018,12 @@ class RPC:
             'columns': list(dataframe.columns),
             'data': dataframe.values.tolist(),
             'length': len(dataframe),
-            'buy_signals': buy_signals,
-            'sell_signals': sell_signals,
+            'buy_signals': signals['enter_long'],  # Deprecated
+            'sell_signals': signals['exit_long'],  # Deprecated
+            'enter_long_signals': signals['enter_long'],
+            'exit_long_signals': signals['exit_long'],
+            'enter_short_signals': signals['enter_short'],
+            'exit_short_signals': signals['exit_short'],
             'last_analyzed': last_analyzed,
             'last_analyzed_ts': int(last_analyzed.timestamp()),
             'data_start': '',
@@ -843,7 +1053,7 @@ class RPC:
 
     @staticmethod
     def _rpc_analysed_history_full(config, pair: str, timeframe: str,
-                                   timerange: str) -> Dict[str, Any]:
+                                   timerange: str, exchange) -> Dict[str, Any]:
         timerange_parsed = TimeRange.parse_timerange(timerange)
 
         _data = load_data(
@@ -852,13 +1062,14 @@ class RPC:
             timeframe=timeframe,
             timerange=timerange_parsed,
             data_format=config.get('dataformat_ohlcv', 'json'),
+            candle_type=config.get('candle_type_def', CandleType.SPOT)
         )
         if pair not in _data:
             raise RPCException(f"No data for {pair}, {timeframe} in {timerange} found.")
         from freqtrade.data.dataprovider import DataProvider
         from freqtrade.resolvers.strategy_resolver import StrategyResolver
         strategy = StrategyResolver.load_strategy(config)
-        strategy.dp = DataProvider(config, exchange=None, pairlists=None)
+        strategy.dp = DataProvider(config, exchange=exchange, pairlists=None)
 
         df_analyzed = strategy.analyze_ticker(_data[pair], {'pair': pair})
 
@@ -870,3 +1081,18 @@ class RPC:
                 'subplots' not in self._freqtrade.strategy.plot_config):
             self._freqtrade.strategy.plot_config['subplots'] = {}
         return self._freqtrade.strategy.plot_config
+
+    @staticmethod
+    def _rpc_sysinfo() -> Dict[str, Any]:
+        return {
+            "cpu_pct": psutil.cpu_percent(interval=1, percpu=True),
+            "ram_pct": psutil.virtual_memory().percent
+        }
+
+    def _health(self) -> Dict[str, Union[str, int]]:
+        last_p = self._freqtrade.last_process
+        return {
+            'last_process': str(last_p),
+            'last_process_loc': last_p.astimezone(tzlocal()).strftime(DATETIME_PRINT_FORMAT),
+            'last_process_ts': int(last_p.timestamp()),
+        }
diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py
index 8085ece94..d97d1df5f 100644
--- a/freqtrade/rpc/rpc_manager.py
+++ b/freqtrade/rpc/rpc_manager.py
@@ -60,6 +60,10 @@ class RPCManager:
         }
         """
         logger.info('Sending rpc message: %s', msg)
+        if 'pair' in msg:
+            msg.update({
+                'base_currency': self._rpc._freqtrade.exchange.get_pair_base_currency(msg['pair'])
+                })
         for mod in self.registered_modules:
             logger.debug('Forwarding message to rpc.%s', mod.name)
             try:
@@ -81,12 +85,14 @@ class RPCManager:
         timeframe = config['timeframe']
         exchange_name = config['exchange']['name']
         strategy_name = config.get('strategy', '')
+        pos_adjust_enabled = 'On' if config['position_adjustment_enable'] else 'Off'
         self.send_msg({
             'type': RPCMessageType.STARTUP,
             'status': f'*Exchange:* `{exchange_name}`\n'
                       f'*Stake per trade:* `{stake_amount} {stake_currency}`\n'
                       f'*Minimum ROI:* `{minimal_roi}`\n'
                       f'*{"Trailing " if trailing_stop else ""}Stoploss:* `{stoploss}`\n'
+                      f'*Position adjustment:* `{pos_adjust_enabled}`\n'
                       f'*Timeframe:* `{timeframe}`\n'
                       f'*Strategy:* `{strategy_name}`'
         })
diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index 059ba9c41..c2531fec3 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -7,6 +7,7 @@ import json
 import logging
 import re
 from datetime import date, datetime, timedelta
+from functools import partial
 from html import escape
 from itertools import chain
 from math import isnan
@@ -22,9 +23,10 @@ from telegram.utils.helpers import escape_markdown
 
 from freqtrade.__init__ import __version__
 from freqtrade.constants import DUST_PER_COIN
-from freqtrade.enums import RPCMessageType
+from freqtrade.enums import RPCMessageType, SignalDirection, TradingMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.misc import chunks, plural, round_coin_value
+from freqtrade.persistence import Trade
 from freqtrade.rpc import RPC, RPCException, RPCHandler
 
 
@@ -59,7 +61,8 @@ def authorized_only(command_handler: Callable[..., None]) -> Callable[..., Any]:
                 update.message.chat_id
             )
             return wrapper
-
+        # Rollback session to avoid getting data stored in a transaction.
+        Trade.query.session.rollback()
         logger.debug(
             'Executing handler: %s for chat_id: %s',
             command_handler.__name__,
@@ -100,17 +103,20 @@ class Telegram(RPCHandler):
             ['/count', '/start', '/stop', '/help']
         ]
         # do not allow commands with mandatory arguments and critical cmds
-        # like /forcesell and /forcebuy
         # TODO: DRY! - its not good to list all valid cmds here. But otherwise
         #       this needs refactoring of the whole telegram module (same
         #       problem in _help()).
         valid_keys: List[str] = [r'/start$', r'/stop$', r'/status$', r'/status table$',
-                                 r'/trades$', r'/performance$', r'/daily$', r'/daily \d+$',
-                                 r'/profit$', r'/profit \d+',
+                                 r'/trades$', r'/performance$', r'/buys', r'/entries',
+                                 r'/sells', r'/exits', r'/mix_tags',
+                                 r'/daily$', r'/daily \d+$', r'/profit$', r'/profit \d+',
                                  r'/stats$', r'/count$', r'/locks$', r'/balance$',
                                  r'/stopbuy$', r'/reload_config$', r'/show_config$',
-                                 r'/logs$', r'/whitelist$', r'/blacklist$', r'/edge$',
-                                 r'/forcebuy$', r'/help$', r'/version$']
+                                 r'/logs$', r'/whitelist$', r'/blacklist$', r'/bl_delete$',
+                                 r'/weekly$', r'/weekly \d+$', r'/monthly$', r'/monthly \d+$',
+                                 r'/forcebuy$', r'/forcelong$', r'/forceshort$',
+                                 r'/forcesell$', r'/forceexit$',
+                                 r'/edge$', r'/health$', r'/help$', r'/version$']
         # Create keys for generation
         valid_keys_print = [k.replace('$', '') for k in valid_keys]
 
@@ -147,13 +153,21 @@ class Telegram(RPCHandler):
             CommandHandler('balance', self._balance),
             CommandHandler('start', self._start),
             CommandHandler('stop', self._stop),
-            CommandHandler('forcesell', self._forcesell),
-            CommandHandler('forcebuy', self._forcebuy),
+            CommandHandler(['forcesell', 'forceexit', 'fx'], self._force_exit),
+            CommandHandler(['forcebuy', 'forcelong'], partial(
+                self._force_enter, order_side=SignalDirection.LONG)),
+            CommandHandler('forceshort', partial(
+                self._force_enter, order_side=SignalDirection.SHORT)),
             CommandHandler('trades', self._trades),
             CommandHandler('delete', self._delete_trade),
             CommandHandler('performance', self._performance),
+            CommandHandler(['buys', 'entries'], self._enter_tag_performance),
+            CommandHandler(['sells', 'exits'], self._exit_reason_performance),
+            CommandHandler('mix_tags', self._mix_tag_performance),
             CommandHandler('stats', self._stats),
             CommandHandler('daily', self._daily),
+            CommandHandler('weekly', self._weekly),
+            CommandHandler('monthly', self._monthly),
             CommandHandler('count', self._count),
             CommandHandler('locks', self._locks),
             CommandHandler(['unlock', 'delete_locks'], self._delete_locks),
@@ -162,19 +176,29 @@ class Telegram(RPCHandler):
             CommandHandler('stopbuy', self._stopbuy),
             CommandHandler('whitelist', self._whitelist),
             CommandHandler('blacklist', self._blacklist),
+            CommandHandler(['blacklist_delete', 'bl_delete'], self._blacklist_delete),
             CommandHandler('logs', self._logs),
             CommandHandler('edge', self._edge),
+            CommandHandler('health', self._health),
             CommandHandler('help', self._help),
             CommandHandler('version', self._version),
         ]
         callbacks = [
             CallbackQueryHandler(self._status_table, pattern='update_status_table'),
             CallbackQueryHandler(self._daily, pattern='update_daily'),
+            CallbackQueryHandler(self._weekly, pattern='update_weekly'),
+            CallbackQueryHandler(self._monthly, pattern='update_monthly'),
             CallbackQueryHandler(self._profit, pattern='update_profit'),
             CallbackQueryHandler(self._balance, pattern='update_balance'),
             CallbackQueryHandler(self._performance, pattern='update_performance'),
+            CallbackQueryHandler(self._enter_tag_performance,
+                                 pattern='update_enter_tag_performance'),
+            CallbackQueryHandler(self._exit_reason_performance,
+                                 pattern='update_exit_reason_performance'),
+            CallbackQueryHandler(self._mix_tag_performance, pattern='update_mix_tag_performance'),
             CallbackQueryHandler(self._count, pattern='update_count'),
-            CallbackQueryHandler(self._forcebuy_inline),
+            CallbackQueryHandler(self._force_exit_inline, pattern=r"force_exit__\S+"),
+            CallbackQueryHandler(self._force_enter_inline, pattern=r"\S+\/\S+"),
         ]
         for handle in handles:
             self._updater.dispatcher.add_handler(handle)
@@ -184,8 +208,8 @@ class Telegram(RPCHandler):
 
         self._updater.start_polling(
             bootstrap_retries=-1,
-            timeout=30,
-            read_latency=60,
+            timeout=20,
+            read_latency=60,  # Assumed transmission latency
             drop_pending_updates=True,
         )
         logger.info(
@@ -198,99 +222,116 @@ class Telegram(RPCHandler):
         Stops all running telegram threads.
         :return: None
         """
+        # This can take up to `timeout` from the call to `start_polling`.
         self._updater.stop()
 
-    def _format_buy_msg(self, msg: Dict[str, Any]) -> str:
+    def _format_entry_msg(self, msg: Dict[str, Any]) -> str:
         if self._rpc._fiat_converter:
             msg['stake_amount_fiat'] = self._rpc._fiat_converter.convert_amount(
                 msg['stake_amount'], msg['stake_currency'], msg['fiat_currency'])
         else:
             msg['stake_amount_fiat'] = 0
+        is_fill = msg['type'] in [RPCMessageType.ENTRY_FILL]
+        emoji = '\N{CHECK MARK}' if is_fill else '\N{LARGE BLUE CIRCLE}'
 
-        content = []
-        content.append(
-            f"\N{LARGE BLUE CIRCLE} *{msg['exchange']}:* Buying {msg['pair']}"
+        entry_side = ({'enter': 'Long', 'entered': 'Longed'} if msg['direction'] == 'Long'
+                      else {'enter': 'Short', 'entered': 'Shorted'})
+        message = (
+            f"{emoji} *{msg['exchange']}:*"
+            f" {entry_side['entered'] if is_fill else entry_side['enter']} {msg['pair']}"
             f" (#{msg['trade_id']})\n"
-        )
-        if msg.get('buy_tag', None):
-            content.append(f"*Buy Tag:* `{msg['buy_tag']}`\n")
-        content.append(f"*Amount:* `{msg['amount']:.8f}`\n")
-        content.append(f"*Open Rate:* `{msg['limit']:.8f}`\n")
-        content.append(f"*Current Rate:* `{msg['current_rate']:.8f}`\n")
-        content.append(
-            f"*Total:* `({round_coin_value(msg['stake_amount'], msg['stake_currency'])}"
-        )
-        if msg.get('fiat_currency', None):
-            content.append(
-                f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}"
             )
+        message += f"*Enter Tag:* `{msg['enter_tag']}`\n" if msg.get('enter_tag', None) else ""
+        message += f"*Amount:* `{msg['amount']:.8f}`\n"
+        if msg.get('leverage') and msg.get('leverage', 1.0) != 1.0:
+            message += f"*Leverage:* `{msg['leverage']}`\n"
+
+        if msg['type'] in [RPCMessageType.ENTRY_FILL]:
+            message += f"*Open Rate:* `{msg['open_rate']:.8f}`\n"
+        elif msg['type'] in [RPCMessageType.ENTRY]:
+            message += f"*Open Rate:* `{msg['limit']:.8f}`\n"\
+                       f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
+
+        message += f"*Total:* `({round_coin_value(msg['stake_amount'], msg['stake_currency'])}"
+
+        if msg.get('fiat_currency', None):
+            message += f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}"
 
-        message = ''.join(content)
         message += ")`"
         return message
 
-    def _format_sell_msg(self, msg: Dict[str, Any]) -> str:
+    def _format_exit_msg(self, msg: Dict[str, Any]) -> str:
         msg['amount'] = round(msg['amount'], 8)
         msg['profit_percent'] = round(msg['profit_ratio'] * 100, 2)
         msg['duration'] = msg['close_date'].replace(
             microsecond=0) - msg['open_date'].replace(microsecond=0)
         msg['duration_min'] = msg['duration'].total_seconds() / 60
 
+        msg['enter_tag'] = msg['enter_tag'] if "enter_tag" in msg.keys() else None
         msg['emoji'] = self._get_sell_emoji(msg)
+        msg['leverage_text'] = (f"*Leverage:* `{msg['leverage']:.1f}`\n"
+                                if msg.get('leverage', None) and msg.get('leverage', 1.0) != 1.0
+                                else "")
 
         # Check if all sell properties are available.
-        # This might not be the case if the message origin is triggered by /forcesell
+        # This might not be the case if the message origin is triggered by /forceexit
         if (all(prop in msg for prop in ['gain', 'fiat_currency', 'stake_currency'])
                 and self._rpc._fiat_converter):
             msg['profit_fiat'] = self._rpc._fiat_converter.convert_amount(
                 msg['profit_amount'], msg['stake_currency'], msg['fiat_currency'])
-            msg['profit_extra'] = (' ({gain}: {profit_amount:.8f} {stake_currency}'
-                                   ' / {profit_fiat:.3f} {fiat_currency})').format(**msg)
+            msg['profit_extra'] = (
+                f" ({msg['gain']}: {msg['profit_amount']:.8f} {msg['stake_currency']}"
+                f" / {msg['profit_fiat']:.3f} {msg['fiat_currency']})")
         else:
             msg['profit_extra'] = ''
+        is_fill = msg['type'] == RPCMessageType.EXIT_FILL
+        message = (
+            f"{msg['emoji']} *{msg['exchange']}:* "
+            f"{'Exited' if is_fill else 'Exiting'} {msg['pair']} (#{msg['trade_id']})\n"
+            f"*{'Profit' if is_fill else 'Unrealized Profit'}:* "
+            f"`{msg['profit_ratio']:.2%}{msg['profit_extra']}`\n"
+            f"*Enter Tag:* `{msg['enter_tag']}`\n"
+            f"*Exit Reason:* `{msg['exit_reason']}`\n"
+            f"*Duration:* `{msg['duration']} ({msg['duration_min']:.1f} min)`\n"
+            f"*Direction:* `{msg['direction']}`\n"
+            f"{msg['leverage_text']}"
+            f"*Amount:* `{msg['amount']:.8f}`\n"
+            f"*Open Rate:* `{msg['open_rate']:.8f}`\n"
+        )
+        if msg['type'] == RPCMessageType.EXIT:
+            message += (f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
+                        f"*Close Rate:* `{msg['limit']:.8f}`")
 
-        message = ("{emoji} *{exchange}:* Selling {pair} (#{trade_id})\n"
-                   "*Profit:* `{profit_percent:.2f}%{profit_extra}`\n"
-                   "*Sell Reason:* `{sell_reason}`\n"
-                   "*Duration:* `{duration} ({duration_min:.1f} min)`\n"
-                   "*Amount:* `{amount:.8f}`\n"
-                   "*Open Rate:* `{open_rate:.8f}`\n"
-                   "*Current Rate:* `{current_rate:.8f}`\n"
-                   "*Close Rate:* `{limit:.8f}`").format(**msg)
+        elif msg['type'] == RPCMessageType.EXIT_FILL:
+            message += f"*Close Rate:* `{msg['close_rate']:.8f}`"
 
         return message
 
     def compose_message(self, msg: Dict[str, Any], msg_type: RPCMessageType) -> str:
+        if msg_type in [RPCMessageType.ENTRY, RPCMessageType.ENTRY_FILL]:
+            message = self._format_entry_msg(msg)
 
-        if msg_type == RPCMessageType.BUY:
-            message = self._format_buy_msg(msg)
+        elif msg_type in [RPCMessageType.EXIT, RPCMessageType.EXIT_FILL]:
+            message = self._format_exit_msg(msg)
 
-        elif msg_type in (RPCMessageType.BUY_CANCEL, RPCMessageType.SELL_CANCEL):
-            msg['message_side'] = 'buy' if msg_type == RPCMessageType.BUY_CANCEL else 'sell'
+        elif msg_type in (RPCMessageType.ENTRY_CANCEL, RPCMessageType.EXIT_CANCEL):
+            msg['message_side'] = 'enter' if msg_type in [RPCMessageType.ENTRY_CANCEL] else 'exit'
             message = ("\N{WARNING SIGN} *{exchange}:* "
-                       "Cancelling open {message_side} Order for {pair} (#{trade_id}). "
+                       "Cancelling {message_side} Order for {pair} (#{trade_id}). "
                        "Reason: {reason}.".format(**msg))
 
-        elif msg_type == RPCMessageType.BUY_FILL:
-            message = ("\N{LARGE CIRCLE} *{exchange}:* "
-                       "Buy order for {pair} (#{trade_id}) filled "
-                       "for {open_rate}.".format(**msg))
-        elif msg_type == RPCMessageType.SELL_FILL:
-            message = ("\N{LARGE CIRCLE} *{exchange}:* "
-                       "Sell order for {pair} (#{trade_id}) filled "
-                       "for {close_rate}.".format(**msg))
-        elif msg_type == RPCMessageType.SELL:
-            message = self._format_sell_msg(msg)
         elif msg_type == RPCMessageType.PROTECTION_TRIGGER:
             message = (
                 "*Protection* triggered due to {reason}. "
                 "`{pair}` will be locked until `{lock_end_time}`."
             ).format(**msg)
+
         elif msg_type == RPCMessageType.PROTECTION_TRIGGER_GLOBAL:
             message = (
                 "*Protection* triggered due to {reason}. "
                 "*All pairs* will be locked until `{lock_end_time}`."
             ).format(**msg)
+
         elif msg_type == RPCMessageType.STATUS:
             message = '*Status:* `{status}`'.format(**msg)
 
@@ -311,14 +352,14 @@ class Telegram(RPCHandler):
 
         msg_type = msg['type']
         noti = ''
-        if msg_type == RPCMessageType.SELL:
+        if msg_type == RPCMessageType.EXIT:
             sell_noti = self._config['telegram'] \
                 .get('notification_settings', {}).get(str(msg_type), {})
             # For backward compatibility sell still can be string
             if isinstance(sell_noti, str):
                 noti = sell_noti
             else:
-                noti = sell_noti.get(str(msg['sell_reason']), default_noti)
+                noti = sell_noti.get(str(msg['exit_reason']), default_noti)
         else:
             noti = self._config['telegram'] \
                 .get('notification_settings', {}).get(str(msg_type), default_noti)
@@ -341,11 +382,60 @@ class Telegram(RPCHandler):
             return "\N{ROCKET}"
         elif float(msg['profit_percent']) >= 0.0:
             return "\N{EIGHT SPOKED ASTERISK}"
-        elif msg['sell_reason'] == "stop_loss":
-            return"\N{WARNING SIGN}"
+        elif msg['exit_reason'] == "stop_loss":
+            return "\N{WARNING SIGN}"
         else:
             return "\N{CROSS MARK}"
 
+    def _prepare_entry_details(self, filled_orders: List, quote_currency: str, is_open: bool):
+        """
+        Prepare details of trade with entry adjustment enabled
+        """
+        lines: List[str] = []
+        if len(filled_orders) > 0:
+            first_avg = filled_orders[0]["safe_price"]
+
+        for x, order in enumerate(filled_orders):
+            if not order['ft_is_entry']:
+                continue
+            cur_entry_datetime = arrow.get(order["order_filled_date"])
+            cur_entry_amount = order["amount"]
+            cur_entry_average = order["safe_price"]
+            lines.append("  ")
+            if x == 0:
+                lines.append(f"*Entry #{x+1}:*")
+                lines.append(
+                    f"*Entry Amount:* {cur_entry_amount} ({order['cost']:.8f} {quote_currency})")
+                lines.append(f"*Average Entry Price:* {cur_entry_average}")
+            else:
+                sumA = 0
+                sumB = 0
+                for y in range(x):
+                    sumA += (filled_orders[y]["amount"] * filled_orders[y]["safe_price"])
+                    sumB += filled_orders[y]["amount"]
+                prev_avg_price = sumA / sumB
+                price_to_1st_entry = ((cur_entry_average - first_avg) / first_avg)
+                minus_on_entry = 0
+                if prev_avg_price:
+                    minus_on_entry = (cur_entry_average - prev_avg_price) / prev_avg_price
+
+                dur_entry = cur_entry_datetime - arrow.get(
+                    filled_orders[x - 1]["order_filled_date"])
+                days = dur_entry.days
+                hours, remainder = divmod(dur_entry.seconds, 3600)
+                minutes, seconds = divmod(remainder, 60)
+                lines.append(f"*Entry #{x+1}:* at {minus_on_entry:.2%} avg profit")
+                if is_open:
+                    lines.append("({})".format(cur_entry_datetime
+                                               .humanize(granularity=["day", "hour", "minute"])))
+                lines.append(
+                    f"*Entry Amount:* {cur_entry_amount} ({order['cost']:.8f} {quote_currency})")
+                lines.append(f"*Average Entry Price:* {cur_entry_average} "
+                             f"({price_to_1st_entry:.2%} from 1st entry rate)")
+                lines.append(f"*Order filled at:* {order['order_filled_date']}")
+                lines.append(f"({days}d {hours}h {minutes}m {seconds}s from previous entry)")
+        return lines
+
     @authorized_only
     def _status(self, update: Update, context: CallbackContext) -> None:
         """
@@ -369,37 +459,59 @@ class Telegram(RPCHandler):
                 trade_ids = [int(i) for i in context.args if i.isnumeric()]
 
             results = self._rpc._rpc_trade_status(trade_ids=trade_ids)
-
+            position_adjust = self._config.get('position_adjustment_enable', False)
+            max_entries = self._config.get('max_entry_position_adjustment', -1)
             messages = []
             for r in results:
                 r['open_date_hum'] = arrow.get(r['open_date']).humanize()
+                r['num_entries'] = len([o for o in r['orders'] if o['ft_is_entry']])
+                r['exit_reason'] = r.get('exit_reason', "")
                 lines = [
-                    "*Trade ID:* `{trade_id}` `(since {open_date_hum})`",
+                    "*Trade ID:* `{trade_id}`" +
+                    ("` (since {open_date_hum})`" if r['is_open'] else ""),
                     "*Current Pair:* {pair}",
-                    "*Amount:* `{amount} ({stake_amount} {base_currency})`",
-                    "*Buy Tag:* `{buy_tag}`" if r['buy_tag'] else "",
-                    "*Open Rate:* `{open_rate:.8f}`",
-                    "*Close Rate:* `{close_rate}`" if r['close_rate'] else "",
-                    "*Current Rate:* `{current_rate:.8f}`",
-                    ("*Current Profit:* " if r['is_open'] else "*Close Profit: *")
-                    + "`{profit_pct:.2f}%`",
+                    "*Direction:* " + ("`Short`" if r.get('is_short') else "`Long`"),
+                    "*Leverage:* `{leverage}`" if r.get('leverage') else "",
+                    "*Amount:* `{amount} ({stake_amount} {quote_currency})`",
+                    "*Enter Tag:* `{enter_tag}`" if r['enter_tag'] else "",
+                    "*Exit Reason:* `{exit_reason}`" if r['exit_reason'] else "",
                 ]
-                if (r['stop_loss_abs'] != r['initial_stop_loss_abs']
-                        and r['initial_stop_loss_pct'] is not None):
-                    # Adding initial stoploss only if it is different from stoploss
-                    lines.append("*Initial Stoploss:* `{initial_stop_loss_abs:.8f}` "
-                                 "`({initial_stop_loss_pct:.2f}%)`")
 
-                # Adding stoploss and stoploss percentage only if it is not None
-                lines.append("*Stoploss:* `{stop_loss_abs:.8f}` " +
-                             ("`({stop_loss_pct:.2f}%)`" if r['stop_loss_pct'] else ""))
-                lines.append("*Stoploss distance:* `{stoploss_current_dist:.8f}` "
-                             "`({stoploss_current_dist_pct:.2f}%)`")
-                if r['open_order']:
-                    if r['sell_order_status']:
-                        lines.append("*Open Order:* `{open_order}` - `{sell_order_status}`")
-                    else:
-                        lines.append("*Open Order:* `{open_order}`")
+                if position_adjust:
+                    max_buy_str = (f"/{max_entries + 1}" if (max_entries > 0) else "")
+                    lines.append("*Number of Entries:* `{num_entries}`" + max_buy_str)
+
+                lines.extend([
+                    "*Open Rate:* `{open_rate:.8f}`",
+                    "*Close Rate:* `{close_rate:.8f}`" if r['close_rate'] else "",
+                    "*Open Date:* `{open_date}`",
+                    "*Close Date:* `{close_date}`" if r['close_date'] else "",
+                    "*Current Rate:* `{current_rate:.8f}`" if r['is_open'] else "",
+                    ("*Current Profit:* " if r['is_open'] else "*Close Profit: *")
+                    + "`{profit_ratio:.2%}`",
+                ])
+
+                if r['is_open']:
+                    if (r['stop_loss_abs'] != r['initial_stop_loss_abs']
+                            and r['initial_stop_loss_ratio'] is not None):
+                        # Adding initial stoploss only if it is different from stoploss
+                        lines.append("*Initial Stoploss:* `{initial_stop_loss_abs:.8f}` "
+                                     "`({initial_stop_loss_ratio:.2%})`")
+
+                    # Adding stoploss and stoploss percentage only if it is not None
+                    lines.append("*Stoploss:* `{stop_loss_abs:.8f}` " +
+                                 ("`({stop_loss_ratio:.2%})`" if r['stop_loss_ratio'] else ""))
+                    lines.append("*Stoploss distance:* `{stoploss_current_dist:.8f}` "
+                                 "`({stoploss_current_dist_ratio:.2%})`")
+                    if r['open_order']:
+                        if r['exit_order_status']:
+                            lines.append("*Open Order:* `{open_order}` - `{exit_order_status}`")
+                        else:
+                            lines.append("*Open Order:* `{open_order}`")
+
+                lines_detail = self._prepare_entry_details(
+                    r['orders'], r['quote_currency'], r['is_open'])
+                lines.extend(lines_detail if lines_detail else "")
 
                 # Filter empty lines using list-comprehension
                 messages.append("\n".join([line for line in lines if line]).format(**r))
@@ -490,6 +602,86 @@ class Telegram(RPCHandler):
         except RPCException as e:
             self._send_msg(str(e))
 
+    @authorized_only
+    def _weekly(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /weekly <n>
+        Returns a weekly profit (in BTC) over the last n weeks.
+        :param bot: telegram bot
+        :param update: message update
+        :return: None
+        """
+        stake_cur = self._config['stake_currency']
+        fiat_disp_cur = self._config.get('fiat_display_currency', '')
+        try:
+            timescale = int(context.args[0]) if context.args else 8
+        except (TypeError, ValueError, IndexError):
+            timescale = 8
+        try:
+            stats = self._rpc._rpc_weekly_profit(
+                timescale,
+                stake_cur,
+                fiat_disp_cur
+            )
+            stats_tab = tabulate(
+                [[week['date'],
+                  f"{round_coin_value(week['abs_profit'], stats['stake_currency'])}",
+                  f"{week['fiat_value']:.3f} {stats['fiat_display_currency']}",
+                  f"{week['trade_count']} trades"] for week in stats['data']],
+                headers=[
+                    'Monday',
+                    f'Profit {stake_cur}',
+                    f'Profit {fiat_disp_cur}',
+                    'Trades',
+                ],
+                tablefmt='simple')
+            message = f'<b>Weekly Profit over the last {timescale} weeks ' \
+                      f'(starting from Monday)</b>:\n<pre>{stats_tab}</pre> '
+            self._send_msg(message, parse_mode=ParseMode.HTML, reload_able=True,
+                           callback_path="update_weekly", query=update.callback_query)
+        except RPCException as e:
+            self._send_msg(str(e))
+
+    @authorized_only
+    def _monthly(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /monthly <n>
+        Returns a monthly profit (in BTC) over the last n months.
+        :param bot: telegram bot
+        :param update: message update
+        :return: None
+        """
+        stake_cur = self._config['stake_currency']
+        fiat_disp_cur = self._config.get('fiat_display_currency', '')
+        try:
+            timescale = int(context.args[0]) if context.args else 6
+        except (TypeError, ValueError, IndexError):
+            timescale = 6
+        try:
+            stats = self._rpc._rpc_monthly_profit(
+                timescale,
+                stake_cur,
+                fiat_disp_cur
+            )
+            stats_tab = tabulate(
+                [[month['date'],
+                  f"{round_coin_value(month['abs_profit'], stats['stake_currency'])}",
+                  f"{month['fiat_value']:.3f} {stats['fiat_display_currency']}",
+                  f"{month['trade_count']} trades"] for month in stats['data']],
+                headers=[
+                    'Month',
+                    f'Profit {stake_cur}',
+                    f'Profit {fiat_disp_cur}',
+                    'Trades',
+                ],
+                tablefmt='simple')
+            message = f'<b>Monthly Profit over the last {timescale} months' \
+                      f'</b>:\n<pre>{stats_tab}</pre> '
+            self._send_msg(message, parse_mode=ParseMode.HTML, reload_able=True,
+                           callback_path="update_monthly", query=update.callback_query)
+        except RPCException as e:
+            self._send_msg(str(e))
+
     @authorized_only
     def _profit(self, update: Update, context: CallbackContext) -> None:
         """
@@ -517,11 +709,11 @@ class Telegram(RPCHandler):
             fiat_disp_cur,
             start_date)
         profit_closed_coin = stats['profit_closed_coin']
-        profit_closed_percent_mean = stats['profit_closed_percent_mean']
+        profit_closed_ratio_mean = stats['profit_closed_ratio_mean']
         profit_closed_percent = stats['profit_closed_percent']
         profit_closed_fiat = stats['profit_closed_fiat']
         profit_all_coin = stats['profit_all_coin']
-        profit_all_percent_mean = stats['profit_all_percent_mean']
+        profit_all_ratio_mean = stats['profit_all_ratio_mean']
         profit_all_percent = stats['profit_all_percent']
         profit_all_fiat = stats['profit_all_fiat']
         trade_count = stats['trade_count']
@@ -529,7 +721,7 @@ class Telegram(RPCHandler):
         latest_trade_date = stats['latest_trade_date']
         avg_duration = stats['avg_duration']
         best_pair = stats['best_pair']
-        best_rate = stats['best_rate']
+        best_pair_profit_ratio = stats['best_pair_profit_ratio']
         if stats['trade_count'] == 0:
             markdown_msg = 'No trades yet.'
         else:
@@ -537,7 +729,7 @@ class Telegram(RPCHandler):
             if stats['closed_trade_count'] > 0:
                 markdown_msg = ("*ROI:* Closed trades\n"
                                 f"∙ `{round_coin_value(profit_closed_coin, stake_cur)} "
-                                f"({profit_closed_percent_mean:.2f}%) "
+                                f"({profit_closed_ratio_mean:.2%}) "
                                 f"({profit_closed_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
                                 f"∙ `{round_coin_value(profit_closed_fiat, fiat_disp_cur)}`\n")
             else:
@@ -546,7 +738,7 @@ class Telegram(RPCHandler):
             markdown_msg += (
                 f"*ROI:* All trades\n"
                 f"∙ `{round_coin_value(profit_all_coin, stake_cur)} "
-                f"({profit_all_percent_mean:.2f}%) "
+                f"({profit_all_ratio_mean:.2%}) "
                 f"({profit_all_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
                 f"∙ `{round_coin_value(profit_all_fiat, fiat_disp_cur)}`\n"
                 f"*Total Trade Count:* `{trade_count}`\n"
@@ -557,7 +749,7 @@ class Telegram(RPCHandler):
             )
             if stats['closed_trade_count'] > 0:
                 markdown_msg += (f"\n*Avg. Duration:* `{avg_duration}`\n"
-                                 f"*Best Performing:* `{best_pair}: {best_rate:.2f}%`")
+                                 f"*Best Performing:* `{best_pair}: {best_pair_profit_ratio:.2%}`")
         self._send_msg(markdown_msg, reload_able=True, callback_path="update_profit",
                        query=update.callback_query)
 
@@ -574,33 +766,39 @@ class Telegram(RPCHandler):
             'stop_loss': 'Stoploss',
             'trailing_stop_loss': 'Trail. Stop',
             'stoploss_on_exchange': 'Stoploss',
-            'sell_signal': 'Sell Signal',
-            'force_sell': 'Forcesell',
-            'emergency_sell': 'Emergency Sell',
+            'exit_signal': 'Exit Signal',
+            'force_exit': 'Force Exit',
+            'emergency_exit': 'Emergency Exit',
         }
-        sell_reasons_tabulate = [
+        exit_reasons_tabulate = [
             [
                 reason_map.get(reason, reason),
                 sum(count.values()),
                 count['wins'],
                 count['losses']
-            ] for reason, count in stats['sell_reasons'].items()
+            ] for reason, count in stats['exit_reasons'].items()
         ]
-        sell_reasons_msg = tabulate(
-            sell_reasons_tabulate,
-            headers=['Sell Reason', 'Sells', 'Wins', 'Losses']
-        )
+        exit_reasons_msg = 'No trades yet.'
+        for reason in chunks(exit_reasons_tabulate, 25):
+            exit_reasons_msg = tabulate(
+                reason,
+                headers=['Exit Reason', 'Exits', 'Wins', 'Losses']
+            )
+            if len(exit_reasons_tabulate) > 25:
+                self._send_msg(exit_reasons_msg, ParseMode.MARKDOWN)
+                exit_reasons_msg = ''
+
         durations = stats['durations']
         duration_msg = tabulate(
             [
                 ['Wins', str(timedelta(seconds=durations['wins']))
-                 if durations['wins'] != 'N/A' else 'N/A'],
+                 if durations['wins'] is not None else 'N/A'],
                 ['Losses', str(timedelta(seconds=durations['losses']))
-                 if durations['losses'] != 'N/A' else 'N/A']
+                 if durations['losses'] is not None else 'N/A']
             ],
             headers=['', 'Avg. Duration']
         )
-        msg = (f"""```\n{sell_reasons_msg}```\n```\n{duration_msg}```""")
+        msg = (f"""```\n{exit_reasons_msg}```\n```\n{duration_msg}```""")
 
         self._send_msg(msg, ParseMode.MARKDOWN)
 
@@ -618,12 +816,13 @@ class Telegram(RPCHandler):
             output = ''
             if self._config['dry_run']:
                 output += "*Warning:* Simulated balances in Dry Mode.\n"
-
-            output += ("Starting capital: "
-                       f"`{result['starting_capital']}` {self._config['stake_currency']}"
-                       )
-            output += (f" `{result['starting_capital_fiat']}` "
-                       f"{self._config['fiat_display_currency']}.\n"
+            starting_cap = round_coin_value(
+                result['starting_capital'], self._config['stake_currency'])
+            output += f"Starting capital: `{starting_cap}`"
+            starting_cap_fiat = round_coin_value(
+                result['starting_capital_fiat'], self._config['fiat_display_currency']
+            ) if result['starting_capital_fiat'] > 0 else ''
+            output += (f" `, {starting_cap_fiat}`.\n"
                        ) if result['starting_capital_fiat'] > 0 else '.\n'
 
             total_dust_balance = 0
@@ -631,13 +830,21 @@ class Telegram(RPCHandler):
             for curr in result['currencies']:
                 curr_output = ''
                 if curr['est_stake'] > balance_dust_level:
-                    curr_output = (
-                        f"*{curr['currency']}:*\n"
-                        f"\t`Available: {curr['free']:.8f}`\n"
-                        f"\t`Balance: {curr['balance']:.8f}`\n"
-                        f"\t`Pending: {curr['used']:.8f}`\n"
-                        f"\t`Est. {curr['stake']}: "
-                        f"{round_coin_value(curr['est_stake'], curr['stake'], False)}`\n")
+                    if curr['is_position']:
+                        curr_output = (
+                            f"*{curr['currency']}:*\n"
+                            f"\t`{curr['side']}: {curr['position']:.8f}`\n"
+                            f"\t`Leverage: {curr['leverage']:.1f}`\n"
+                            f"\t`Est. {curr['stake']}: "
+                            f"{round_coin_value(curr['est_stake'], curr['stake'], False)}`\n")
+                    else:
+                        curr_output = (
+                            f"*{curr['currency']}:*\n"
+                            f"\t`Available: {curr['free']:.8f}`\n"
+                            f"\t`Balance: {curr['balance']:.8f}`\n"
+                            f"\t`Pending: {curr['used']:.8f}`\n"
+                            f"\t`Est. {curr['stake']}: "
+                            f"{round_coin_value(curr['est_stake'], curr['stake'], False)}`\n")
                 elif curr['est_stake'] <= balance_dust_level:
                     total_dust_balance += curr['est_stake']
                     total_dust_currencies += 1
@@ -656,14 +863,17 @@ class Telegram(RPCHandler):
                     f"(< {balance_dust_level} {result['stake']}):*\n"
                     f"\t`Est. {result['stake']}: "
                     f"{round_coin_value(total_dust_balance, result['stake'], False)}`\n")
+            tc = result['trade_count'] > 0
+            stake_improve = f" `({result['starting_capital_ratio']:.2%})`" if tc else ''
+            fiat_val = f" `({result['starting_capital_fiat_ratio']:.2%})`" if tc else ''
 
             output += ("\n*Estimated Value*:\n"
                        f"\t`{result['stake']}: "
                        f"{round_coin_value(result['total'], result['stake'], False)}`"
-                       f" `({result['starting_capital_pct']}%)`\n"
+                       f"{stake_improve}\n"
                        f"\t`{result['symbol']}: "
                        f"{round_coin_value(result['value'], result['symbol'], False)}`"
-                       f" `({result['starting_capital_fiat_pct']}%)`\n")
+                       f"{fiat_val}\n")
             self._send_msg(output, reload_able=True, callback_path="update_balance",
                            query=update.callback_query)
         except RPCException as e:
@@ -718,49 +928,93 @@ class Telegram(RPCHandler):
         self._send_msg('Status: `{status}`'.format(**msg))
 
     @authorized_only
-    def _forcesell(self, update: Update, context: CallbackContext) -> None:
+    def _force_exit(self, update: Update, context: CallbackContext) -> None:
         """
-        Handler for /forcesell <id>.
+        Handler for /forceexit <id>.
         Sells the given trade at current price
         :param bot: telegram bot
         :param update: message update
         :return: None
         """
 
-        trade_id = context.args[0] if context.args and len(context.args) > 0 else None
-        if not trade_id:
-            self._send_msg("You must specify a trade-id or 'all'.")
-            return
-        try:
-            msg = self._rpc._rpc_forcesell(trade_id)
-            self._send_msg('Forcesell Result: `{result}`'.format(**msg))
+        if context.args:
+            trade_id = context.args[0]
+            self._force_exit_action(trade_id)
+        else:
+            fiat_currency = self._config.get('fiat_display_currency', '')
+            try:
+                statlist, head, fiat_profit_sum = self._rpc._rpc_status_table(
+                    self._config['stake_currency'], fiat_currency)
+            except RPCException:
+                self._send_msg(msg='No open trade found.')
+                return
+            trades = []
+            for trade in statlist:
+                trades.append((trade[0], f"{trade[0]} {trade[1]} {trade[2]} {trade[3]}"))
 
-        except RPCException as e:
-            self._send_msg(str(e))
+            trade_buttons = [
+                InlineKeyboardButton(text=trade[1], callback_data=f"force_exit__{trade[0]}")
+                for trade in trades]
+            buttons_aligned = self._layout_inline_keyboard_onecol(trade_buttons)
 
-    def _forcebuy_action(self, pair, price=None):
-        try:
-            self._rpc._rpc_forcebuy(pair, price)
-        except RPCException as e:
-            self._send_msg(str(e))
+            buttons_aligned.append([InlineKeyboardButton(
+                text='Cancel', callback_data='force_exit__cancel')])
+            self._send_msg(msg="Which trade?", keyboard=buttons_aligned)
 
-    def _forcebuy_inline(self, update: Update, _: CallbackContext) -> None:
+    def _force_exit_action(self, trade_id):
+        if trade_id != 'cancel':
+            try:
+                self._rpc._rpc_force_exit(trade_id)
+            except RPCException as e:
+                self._send_msg(str(e))
+
+    def _force_exit_inline(self, update: Update, _: CallbackContext) -> None:
         if update.callback_query:
             query = update.callback_query
-            pair = query.data
-            query.answer()
-            query.edit_message_text(text=f"Force Buying: {pair}")
-            self._forcebuy_action(pair)
+            if query.data and '__' in query.data:
+                # Input data is "force_exit__<tradid|cancel>"
+                trade_id = query.data.split("__")[1].split(' ')[0]
+                if trade_id == 'cancel':
+                    query.answer()
+                    query.edit_message_text(text="Force exit canceled.")
+                    return
+                trade: Trade = Trade.get_trades(trade_filter=Trade.id == trade_id).first()
+                query.answer()
+                query.edit_message_text(text=f"Manually exiting Trade #{trade_id}, {trade.pair}")
+                self._force_exit_action(trade_id)
+
+    def _force_enter_action(self, pair, price: Optional[float], order_side: SignalDirection):
+        if pair != 'cancel':
+            try:
+                self._rpc._rpc_force_entry(pair, price, order_side=order_side)
+            except RPCException as e:
+                self._send_msg(str(e))
+
+    def _force_enter_inline(self, update: Update, _: CallbackContext) -> None:
+        if update.callback_query:
+            query = update.callback_query
+            if query.data and '_||_' in query.data:
+                pair, side = query.data.split('_||_')
+                order_side = SignalDirection(side)
+                query.answer()
+                query.edit_message_text(text=f"Manually entering {order_side} for {pair}")
+                self._force_enter_action(pair, None, order_side)
 
     @staticmethod
-    def _layout_inline_keyboard(buttons: List[InlineKeyboardButton],
-                                cols=3) -> List[List[InlineKeyboardButton]]:
+    def _layout_inline_keyboard(
+            buttons: List[InlineKeyboardButton], cols=3) -> List[List[InlineKeyboardButton]]:
+        return [buttons[i:i + cols] for i in range(0, len(buttons), cols)]
+
+    @staticmethod
+    def _layout_inline_keyboard_onecol(
+            buttons: List[InlineKeyboardButton], cols=1) -> List[List[InlineKeyboardButton]]:
         return [buttons[i:i + cols] for i in range(0, len(buttons), cols)]
 
     @authorized_only
-    def _forcebuy(self, update: Update, context: CallbackContext) -> None:
+    def _force_enter(
+            self, update: Update, context: CallbackContext, order_side: SignalDirection) -> None:
         """
-        Handler for /forcebuy <asset> <price>.
+        Handler for /forcelong <asset> <price> and `/forceshort <asset> <price>
         Buys a pair trade at the given or current price
         :param bot: telegram bot
         :param update: message update
@@ -769,13 +1023,19 @@ class Telegram(RPCHandler):
         if context.args:
             pair = context.args[0]
             price = float(context.args[1]) if len(context.args) > 1 else None
-            self._forcebuy_action(pair, price)
+            self._force_enter_action(pair, price, order_side)
         else:
             whitelist = self._rpc._rpc_whitelist()['whitelist']
-            pairs = [InlineKeyboardButton(text=pair, callback_data=pair) for pair in whitelist]
+            pair_buttons = [
+                InlineKeyboardButton(text=pair, callback_data=f"{pair}_||_{order_side}")
+                for pair in sorted(whitelist)
+            ]
+            buttons_aligned = self._layout_inline_keyboard(pair_buttons)
 
+            buttons_aligned.append([InlineKeyboardButton(text='Cancel', callback_data='cancel')])
             self._send_msg(msg="Which pair?",
-                           keyboard=self._layout_inline_keyboard(pairs))
+                           keyboard=buttons_aligned,
+                           query=update.callback_query)
 
     @authorized_only
     def _trades(self, update: Update, context: CallbackContext) -> None:
@@ -798,7 +1058,7 @@ class Telegram(RPCHandler):
             trades_tab = tabulate(
                 [[arrow.get(trade['close_date']).humanize(),
                   trade['pair'] + " (#" + str(trade['trade_id']) + ")",
-                  f"{(100 * trade['close_profit']):.2f}% ({trade['close_profit_abs']})"]
+                  f"{(trade['close_profit']):.2%} ({trade['close_profit_abs']})"]
                  for trade in trades['trades']],
                 headers=[
                     'Close Date',
@@ -850,7 +1110,7 @@ class Telegram(RPCHandler):
                 stat_line = (
                     f"{i+1}.\t <code>{trade['pair']}\t"
                     f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
-                    f"({trade['profit']:.2f}%) "
+                    f"({trade['profit_ratio']:.2%}) "
                     f"({trade['count']})</code>\n")
 
                 if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
@@ -865,6 +1125,111 @@ class Telegram(RPCHandler):
         except RPCException as e:
             self._send_msg(str(e))
 
+    @authorized_only
+    def _enter_tag_performance(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /buys PAIR .
+        Shows a performance statistic from finished trades
+        :param bot: telegram bot
+        :param update: message update
+        :return: None
+        """
+        try:
+            pair = None
+            if context.args and isinstance(context.args[0], str):
+                pair = context.args[0]
+
+            trades = self._rpc._rpc_enter_tag_performance(pair)
+            output = "<b>Entry Tag Performance:</b>\n"
+            for i, trade in enumerate(trades):
+                stat_line = (
+                    f"{i+1}.\t <code>{trade['enter_tag']}\t"
+                    f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
+                    f"({trade['profit_ratio']:.2%}) "
+                    f"({trade['count']})</code>\n")
+
+                if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                    self._send_msg(output, parse_mode=ParseMode.HTML)
+                    output = stat_line
+                else:
+                    output += stat_line
+
+            self._send_msg(output, parse_mode=ParseMode.HTML,
+                           reload_able=True, callback_path="update_enter_tag_performance",
+                           query=update.callback_query)
+        except RPCException as e:
+            self._send_msg(str(e))
+
+    @authorized_only
+    def _exit_reason_performance(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /sells.
+        Shows a performance statistic from finished trades
+        :param bot: telegram bot
+        :param update: message update
+        :return: None
+        """
+        try:
+            pair = None
+            if context.args and isinstance(context.args[0], str):
+                pair = context.args[0]
+
+            trades = self._rpc._rpc_exit_reason_performance(pair)
+            output = "<b>Exit Reason Performance:</b>\n"
+            for i, trade in enumerate(trades):
+                stat_line = (
+                    f"{i+1}.\t <code>{trade['exit_reason']}\t"
+                    f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
+                    f"({trade['profit_ratio']:.2%}) "
+                    f"({trade['count']})</code>\n")
+
+                if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                    self._send_msg(output, parse_mode=ParseMode.HTML)
+                    output = stat_line
+                else:
+                    output += stat_line
+
+            self._send_msg(output, parse_mode=ParseMode.HTML,
+                           reload_able=True, callback_path="update_exit_reason_performance",
+                           query=update.callback_query)
+        except RPCException as e:
+            self._send_msg(str(e))
+
+    @authorized_only
+    def _mix_tag_performance(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /mix_tags.
+        Shows a performance statistic from finished trades
+        :param bot: telegram bot
+        :param update: message update
+        :return: None
+        """
+        try:
+            pair = None
+            if context.args and isinstance(context.args[0], str):
+                pair = context.args[0]
+
+            trades = self._rpc._rpc_mix_tag_performance(pair)
+            output = "<b>Mix Tag Performance:</b>\n"
+            for i, trade in enumerate(trades):
+                stat_line = (
+                    f"{i+1}.\t <code>{trade['mix_tag']}\t"
+                    f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
+                    f"({trade['profit']:.2%}) "
+                    f"({trade['count']})</code>\n")
+
+                if len(output + stat_line) >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                    self._send_msg(output, parse_mode=ParseMode.HTML)
+                    output = stat_line
+                else:
+                    output += stat_line
+
+            self._send_msg(output, parse_mode=ParseMode.HTML,
+                           reload_able=True, callback_path="update_mix_tag_performance",
+                           query=update.callback_query)
+        except RPCException as e:
+            self._send_msg(str(e))
+
     @authorized_only
     def _count(self, update: Update, context: CallbackContext) -> None:
         """
@@ -950,22 +1315,28 @@ class Telegram(RPCHandler):
         Handler for /blacklist
         Shows the currently active blacklist
         """
-        try:
+        self.send_blacklist_msg(self._rpc._rpc_blacklist(context.args))
 
-            blacklist = self._rpc._rpc_blacklist(context.args)
-            errmsgs = []
-            for pair, error in blacklist['errors'].items():
-                errmsgs.append(f"Error adding `{pair}` to blacklist: `{error['error_msg']}`")
-            if errmsgs:
-                self._send_msg('\n'.join(errmsgs))
+    def send_blacklist_msg(self, blacklist: Dict):
+        errmsgs = []
+        for pair, error in blacklist['errors'].items():
+            errmsgs.append(f"Error adding `{pair}` to blacklist: `{error['error_msg']}`")
+        if errmsgs:
+            self._send_msg('\n'.join(errmsgs))
 
-            message = f"Blacklist contains {blacklist['length']} pairs\n"
-            message += f"`{', '.join(blacklist['blacklist'])}`"
+        message = f"Blacklist contains {blacklist['length']} pairs\n"
+        message += f"`{', '.join(blacklist['blacklist'])}`"
 
-            logger.debug(message)
-            self._send_msg(message)
-        except RPCException as e:
-            self._send_msg(str(e))
+        logger.debug(message)
+        self._send_msg(message)
+
+    @authorized_only
+    def _blacklist_delete(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /bl_delete
+        Deletes pair(s) from current blacklist
+        """
+        self.send_blacklist_msg(self._rpc._rpc_blacklist_delete(context.args or []))
 
     @authorized_only
     def _logs(self, update: Update, context: CallbackContext) -> None:
@@ -1030,43 +1401,81 @@ class Telegram(RPCHandler):
         :param update: message update
         :return: None
         """
-        forcebuy_text = ("*/forcebuy <pair> [<rate>]:* `Instantly buys the given pair. "
-                         "Optionally takes a rate at which to buy.` \n")
-        message = ("*/start:* `Starts the trader`\n"
-                   "*/stop:* `Stops the trader`\n"
-                   "*/status <trade_id>|[table]:* `Lists all open trades`\n"
-                   "         *<trade_id> :* `Lists one or more specific trades.`\n"
-                   "                        `Separate multiple <trade_id> with a blank space.`\n"
-                   "         *table :* `will display trades in a table`\n"
-                   "                `pending buy orders are marked with an asterisk (*)`\n"
-                   "                `pending sell orders are marked with a double asterisk (**)`\n"
-                   "*/trades [limit]:* `Lists last closed trades (limited to 10 by default)`\n"
-                   "*/profit [<n>]:* `Lists cumulative profit from all finished trades, "
-                   "over the last n days`\n"
-                   "*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, "
-                   "regardless of profit`\n"
-                   f"{forcebuy_text if self._config.get('forcebuy_enable', False) else ''}"
-                   "*/delete <trade_id>:* `Instantly delete the given trade in the database`\n"
-                   "*/performance:* `Show performance of each finished trade grouped by pair`\n"
-                   "*/daily <n>:* `Shows profit or loss per day, over the last n days`\n"
-                   "*/stats:* `Shows Wins / losses by Sell reason as well as "
-                   "Avg. holding durationsfor buys and sells.`\n"
-                   "*/count:* `Show number of active trades compared to allowed number of trades`\n"
-                   "*/locks:* `Show currently locked pairs`\n"
-                   "*/unlock <pair|id>:* `Unlock this Pair (or this lock id if it's numeric)`\n"
-                   "*/balance:* `Show account balance per currency`\n"
-                   "*/stopbuy:* `Stops buying, but handles open trades gracefully` \n"
-                   "*/reload_config:* `Reload configuration file` \n"
-                   "*/show_config:* `Show running configuration` \n"
-                   "*/logs [limit]:* `Show latest logs - defaults to 10` \n"
-                   "*/whitelist:* `Show current whitelist` \n"
-                   "*/blacklist [pair]:* `Show current blacklist, or adds one or more pairs "
-                   "to the blacklist.` \n"
-                   "*/edge:* `Shows validated pairs by Edge if it is enabled` \n"
-                   "*/help:* `This help message`\n"
-                   "*/version:* `Show version`")
+        force_enter_text = ("*/forcelong <pair> [<rate>]:* `Instantly buys the given pair. "
+                            "Optionally takes a rate at which to buy "
+                            "(only applies to limit orders).` \n"
+                            )
+        if self._rpc._freqtrade.trading_mode != TradingMode.SPOT:
+            force_enter_text += ("*/forceshort <pair> [<rate>]:* `Instantly shorts the given pair. "
+                                 "Optionally takes a rate at which to sell "
+                                 "(only applies to limit orders).` \n")
+        message = (
+            "_BotControl_\n"
+            "------------\n"
+            "*/start:* `Starts the trader`\n"
+            "*/stop:* Stops the trader\n"
+            "*/stopbuy:* `Stops buying, but handles open trades gracefully` \n"
+            "*/forceexit <trade_id>|all:* `Instantly exits the given trade or all trades, "
+            "regardless of profit`\n"
+            "*/fe <trade_id>|all:* `Alias to /forceexit`"
+            f"{force_enter_text if self._config.get('force_entry_enable', False) else ''}"
+            "*/delete <trade_id>:* `Instantly delete the given trade in the database`\n"
+            "*/whitelist:* `Show current whitelist` \n"
+            "*/blacklist [pair]:* `Show current blacklist, or adds one or more pairs "
+            "to the blacklist.` \n"
+            "*/blacklist_delete [pairs]| /bl_delete [pairs]:* "
+            "`Delete pair / pattern from blacklist. Will reset on reload_conf.` \n"
+            "*/reload_config:* `Reload configuration file` \n"
+            "*/unlock <pair|id>:* `Unlock this Pair (or this lock id if it's numeric)`\n"
 
-        self._send_msg(message)
+            "_Current state_\n"
+            "------------\n"
+            "*/show_config:* `Show running configuration` \n"
+            "*/locks:* `Show currently locked pairs`\n"
+            "*/balance:* `Show account balance per currency`\n"
+            "*/logs [limit]:* `Show latest logs - defaults to 10` \n"
+            "*/count:* `Show number of active trades compared to allowed number of trades`\n"
+            "*/edge:* `Shows validated pairs by Edge if it is enabled` \n"
+            "*/health* `Show latest process timestamp - defaults to 1970-01-01 00:00:00` \n"
+
+            "_Statistics_\n"
+            "------------\n"
+            "*/status <trade_id>|[table]:* `Lists all open trades`\n"
+            "         *<trade_id> :* `Lists one or more specific trades.`\n"
+            "                        `Separate multiple <trade_id> with a blank space.`\n"
+            "         *table :* `will display trades in a table`\n"
+            "                `pending buy orders are marked with an asterisk (*)`\n"
+            "                `pending sell orders are marked with a double asterisk (**)`\n"
+            "*/buys <pair|none>:* `Shows the enter_tag performance`\n"
+            "*/sells <pair|none>:* `Shows the exit reason performance`\n"
+            "*/mix_tags <pair|none>:* `Shows combined entry tag + exit reason performance`\n"
+            "*/trades [limit]:* `Lists last closed trades (limited to 10 by default)`\n"
+            "*/profit [<n>]:* `Lists cumulative profit from all finished trades, "
+            "over the last n days`\n"
+            "*/performance:* `Show performance of each finished trade grouped by pair`\n"
+            "*/daily <n>:* `Shows profit or loss per day, over the last n days`\n"
+            "*/weekly <n>:* `Shows statistics per week, over the last n weeks`\n"
+            "*/monthly <n>:* `Shows statistics per month, over the last n months`\n"
+            "*/stats:* `Shows Wins / losses by Sell reason as well as "
+            "Avg. holding durationsfor buys and sells.`\n"
+            "*/help:* `This help message`\n"
+            "*/version:* `Show version`"
+            )
+
+        self._send_msg(message, parse_mode=ParseMode.MARKDOWN)
+
+    @authorized_only
+    def _health(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /health
+        Shows the last process timestamp
+        """
+        try:
+            health = self._rpc._health()
+            message = f"Last process: `{health['last_process_loc']}`"
+            self._send_msg(message)
+        except RPCException as e:
+            self._send_msg(str(e))
 
     @authorized_only
     def _version(self, update: Update, context: CallbackContext) -> None:
@@ -1077,7 +1486,12 @@ class Telegram(RPCHandler):
         :param update: message update
         :return: None
         """
-        self._send_msg('*Version:* `{}`'.format(__version__))
+        strategy_version = self._rpc._freqtrade.strategy.version()
+        version_string = f'*Version:* `{__version__}`'
+        if strategy_version is not None:
+            version_string += f', *Strategy version: * `{strategy_version}`'
+
+        self._send_msg(version_string)
 
     @authorized_only
     def _show_config(self, update: Update, context: CallbackContext) -> None:
@@ -1101,15 +1515,25 @@ class Telegram(RPCHandler):
         else:
             sl_info = f"*Stoploss:* `{val['stoploss']}`\n"
 
+        if val['position_adjustment_enable']:
+            pa_info = (
+                f"*Position adjustment:* On\n"
+                f"*Max enter position adjustment:* `{val['max_entry_position_adjustment']}`\n"
+            )
+        else:
+            pa_info = "*Position adjustment:* Off\n"
+
         self._send_msg(
             f"*Mode:* `{'Dry-run' if val['dry_run'] else 'Live'}`\n"
             f"*Exchange:* `{val['exchange']}`\n"
+            f"*Market: * `{val['trading_mode']}`\n"
             f"*Stake per trade:* `{val['stake_amount']} {val['stake_currency']}`\n"
             f"*Max open Trades:* `{val['max_open_trades']}`\n"
             f"*Minimum ROI:* `{val['minimal_roi']}`\n"
-            f"*Ask strategy:* ```\n{json.dumps(val['ask_strategy'])}```\n"
-            f"*Bid strategy:* ```\n{json.dumps(val['bid_strategy'])}```\n"
+            f"*Entry strategy:* ```\n{json.dumps(val['entry_pricing'])}```\n"
+            f"*Exit strategy:* ```\n{json.dumps(val['exit_pricing'])}```\n"
             f"{sl_info}"
+            f"{pa_info}"
             f"*Timeframe:* `{val['timeframe']}`\n"
             f"*Strategy:* `{val['strategy']}`\n"
             f"*Current state:* `{val['state']}`"
diff --git a/freqtrade/rpc/webhook.py b/freqtrade/rpc/webhook.py
index b4c55649e..a2edcbc85 100644
--- a/freqtrade/rpc/webhook.py
+++ b/freqtrade/rpc/webhook.py
@@ -2,6 +2,7 @@
 This module manages webhook communication
 """
 import logging
+import time
 from typing import Any, Dict
 
 from requests import RequestException, post
@@ -28,12 +29,9 @@ class Webhook(RPCHandler):
         super().__init__(rpc, config)
 
         self._url = self._config['webhook']['url']
-
         self._format = self._config['webhook'].get('format', 'form')
-
-        if self._format != 'form' and self._format != 'json':
-            raise NotImplementedError('Unknown webhook format `{}`, possible values are '
-                                      '`form` (default) and `json`'.format(self._format))
+        self._retries = self._config['webhook'].get('retries', 0)
+        self._retry_delay = self._config['webhook'].get('retry_delay', 0.1)
 
     def cleanup(self) -> None:
         """
@@ -45,23 +43,23 @@ class Webhook(RPCHandler):
     def send_msg(self, msg: Dict[str, Any]) -> None:
         """ Send a message to telegram channel """
         try:
-
-            if msg['type'] == RPCMessageType.BUY:
-                valuedict = self._config['webhook'].get('webhookbuy', None)
-            elif msg['type'] == RPCMessageType.BUY_CANCEL:
-                valuedict = self._config['webhook'].get('webhookbuycancel', None)
-            elif msg['type'] == RPCMessageType.BUY_FILL:
-                valuedict = self._config['webhook'].get('webhookbuyfill', None)
-            elif msg['type'] == RPCMessageType.SELL:
-                valuedict = self._config['webhook'].get('webhooksell', None)
-            elif msg['type'] == RPCMessageType.SELL_FILL:
-                valuedict = self._config['webhook'].get('webhooksellfill', None)
-            elif msg['type'] == RPCMessageType.SELL_CANCEL:
-                valuedict = self._config['webhook'].get('webhooksellcancel', None)
+            whconfig = self._config['webhook']
+            if msg['type'] in [RPCMessageType.ENTRY]:
+                valuedict = whconfig.get('webhookentry', None)
+            elif msg['type'] in [RPCMessageType.ENTRY_CANCEL]:
+                valuedict = whconfig.get('webhookentrycancel', None)
+            elif msg['type'] in [RPCMessageType.ENTRY_FILL]:
+                valuedict = whconfig.get('webhookentryfill', None)
+            elif msg['type'] == RPCMessageType.EXIT:
+                valuedict = whconfig.get('webhookexit', None)
+            elif msg['type'] == RPCMessageType.EXIT_FILL:
+                valuedict = whconfig.get('webhookexitfill', None)
+            elif msg['type'] == RPCMessageType.EXIT_CANCEL:
+                valuedict = whconfig.get('webhookexitcancel', None)
             elif msg['type'] in (RPCMessageType.STATUS,
                                  RPCMessageType.STARTUP,
                                  RPCMessageType.WARNING):
-                valuedict = self._config['webhook'].get('webhookstatus', None)
+                valuedict = whconfig.get('webhookstatus', None)
             else:
                 raise NotImplementedError('Unknown message type: {}'.format(msg['type']))
             if not valuedict:
@@ -77,13 +75,30 @@ class Webhook(RPCHandler):
     def _send_msg(self, payload: dict) -> None:
         """do the actual call to the webhook"""
 
-        try:
-            if self._format == 'form':
-                post(self._url, data=payload)
-            elif self._format == 'json':
-                post(self._url, json=payload)
-            else:
-                raise NotImplementedError('Unknown format: {}'.format(self._format))
+        success = False
+        attempts = 0
+        while not success and attempts <= self._retries:
+            if attempts:
+                if self._retry_delay:
+                    time.sleep(self._retry_delay)
+                logger.info("Retrying webhook...")
 
-        except RequestException as exc:
-            logger.warning("Could not call webhook url. Exception: %s", exc)
+            attempts += 1
+
+            try:
+                if self._format == 'form':
+                    response = post(self._url, data=payload)
+                elif self._format == 'json':
+                    response = post(self._url, json=payload)
+                elif self._format == 'raw':
+                    response = post(self._url, data=payload['data'],
+                                    headers={'Content-Type': 'text/plain'})
+                else:
+                    raise NotImplementedError('Unknown format: {}'.format(self._format))
+
+                # Throw a RequestException if the post was not successful
+                response.raise_for_status()
+                success = True
+
+            except RequestException as exc:
+                logger.warning("Could not call webhook url. Exception: %s", exc)
diff --git a/freqtrade/strategy/hyper.py b/freqtrade/strategy/hyper.py
index dad282d7e..278954bb2 100644
--- a/freqtrade/strategy/hyper.py
+++ b/freqtrade/strategy/hyper.py
@@ -292,7 +292,7 @@ class BooleanParameter(CategoricalParameter):
                          load=load, **kwargs)
 
 
-class HyperStrategyMixin(object):
+class HyperStrategyMixin:
     """
     A helper base class which allows HyperOptAuto class to reuse implementations of buy/sell
      strategy logic.
@@ -381,7 +381,8 @@ class HyperStrategyMixin(object):
         if filename.is_file():
             logger.info(f"Loading parameters from file {filename}")
             try:
-                params = json_load(filename.open('r'))
+                with filename.open('r') as f:
+                    params = json_load(f)
                 if params.get('strategy_name') != self.__class__.__name__:
                     raise OperationalException('Invalid parameter file provided.')
                 return params
diff --git a/freqtrade/strategy/informative_decorator.py b/freqtrade/strategy/informative_decorator.py
index 4c5f21108..0dd5320cd 100644
--- a/freqtrade/strategy/informative_decorator.py
+++ b/freqtrade/strategy/informative_decorator.py
@@ -1,7 +1,9 @@
-from typing import Any, Callable, NamedTuple, Optional, Union
+from dataclasses import dataclass
+from typing import Any, Callable, Optional, Union
 
 from pandas import DataFrame
 
+from freqtrade.enums import CandleType
 from freqtrade.exceptions import OperationalException
 from freqtrade.strategy.strategy_helper import merge_informative_pair
 
@@ -9,15 +11,19 @@ from freqtrade.strategy.strategy_helper import merge_informative_pair
 PopulateIndicators = Callable[[Any, DataFrame, dict], DataFrame]
 
 
-class InformativeData(NamedTuple):
+@dataclass
+class InformativeData:
     asset: Optional[str]
     timeframe: str
     fmt: Union[str, Callable[[Any], str], None]
     ffill: bool
+    candle_type: Optional[CandleType]
 
 
 def informative(timeframe: str, asset: str = '',
                 fmt: Optional[Union[str, Callable[[Any], str]]] = None,
+                *,
+                candle_type: Optional[CandleType] = None,
                 ffill: bool = True) -> Callable[[PopulateIndicators], PopulateIndicators]:
     """
     A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
@@ -46,15 +52,17 @@ def informative(timeframe: str, asset: str = '',
     * {column} - name of dataframe column.
     * {timeframe} - timeframe of informative dataframe.
     :param ffill: ffill dataframe after merging informative pair.
+    :param candle_type: '', mark, index, premiumIndex, or funding_rate
     """
     _asset = asset
     _timeframe = timeframe
     _fmt = fmt
     _ffill = ffill
+    _candle_type = CandleType.from_string(candle_type) if candle_type else None
 
     def decorator(fn: PopulateIndicators):
         informative_pairs = getattr(fn, '_ft_informative', [])
-        informative_pairs.append(InformativeData(_asset, _timeframe, _fmt, _ffill))
+        informative_pairs.append(InformativeData(_asset, _timeframe, _fmt, _ffill, _candle_type))
         setattr(fn, '_ft_informative', informative_pairs)
         return fn
     return decorator
@@ -71,6 +79,8 @@ def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata:
     asset = inf_data.asset or ''
     timeframe = inf_data.timeframe
     fmt = inf_data.fmt
+    candle_type = inf_data.candle_type
+
     config = strategy.config
 
     if asset:
@@ -80,12 +90,11 @@ def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata:
         # Not specifying an asset will define informative dataframe for current pair.
         asset = metadata['pair']
 
-    if '/' in asset:
-        base, quote = asset.split('/')
-    else:
-        # When futures are supported this may need reevaluation.
-        # base, quote = asset, ''
-        raise OperationalException('Not implemented.')
+    market = strategy.dp.market(asset)
+    if market is None:
+        raise OperationalException(f'Market {asset} is not available.')
+    base = market['base']
+    quote = market['quote']
 
     # Default format. This optimizes for the common case: informative pairs using same stake
     # currency. When quote currency matches stake currency, column name will omit base currency.
@@ -98,7 +107,7 @@ def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata:
             fmt = '{base}_{quote}_' + fmt           # Informatives of other pairs
 
     inf_metadata = {'pair': asset, 'timeframe': timeframe}
-    inf_dataframe = strategy.dp.get_pair_dataframe(asset, timeframe)
+    inf_dataframe = strategy.dp.get_pair_dataframe(asset, timeframe, candle_type)
     inf_dataframe = populate_indicators(strategy, inf_dataframe, inf_metadata)
 
     formatter: Any = None
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index 7420bd9fd..afcc1aa99 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -13,11 +13,13 @@ from pandas import DataFrame
 
 from freqtrade.constants import ListPairsWithTimeframes
 from freqtrade.data.dataprovider import DataProvider
-from freqtrade.enums import SellType, SignalTagType, SignalType
+from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, SignalTagType,
+                             SignalType, TradingMode)
 from freqtrade.exceptions import OperationalException, StrategyError
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
 from freqtrade.exchange.exchange import timeframe_to_next_date
 from freqtrade.persistence import PairLocks, Trade
+from freqtrade.persistence.models import LocalTrade, Order
 from freqtrade.strategy.hyper import HyperStrategyMixin
 from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators,
                                                       _create_and_merge_informative_pair,
@@ -27,23 +29,7 @@ from freqtrade.wallets import Wallets
 
 
 logger = logging.getLogger(__name__)
-CUSTOM_SELL_MAX_LENGTH = 64
-
-
-class SellCheckTuple(object):
-    """
-    NamedTuple for Sell type + reason
-    """
-    sell_type: SellType
-    sell_reason: str = ''
-
-    def __init__(self, sell_type: SellType, sell_reason: str = ''):
-        self.sell_type = sell_type
-        self.sell_reason = sell_reason or sell_type.value
-
-    @property
-    def sell_flag(self):
-        return self.sell_type != SellType.NONE
+CUSTOM_EXIT_MAX_LENGTH = 64
 
 
 class IStrategy(ABC, HyperStrategyMixin):
@@ -54,20 +40,21 @@ class IStrategy(ABC, HyperStrategyMixin):
     Attributes you can use:
         minimal_roi -> Dict: Minimal ROI designed for the strategy
         stoploss -> float: optimal stoploss designed for the strategy
-        timeframe -> str: value of the timeframe (ticker interval) to use with the strategy
+        timeframe -> str: value of the timeframe to use with the strategy
     """
     # Strategy interface version
     # Default to version 2
     # Version 1 is the initial interface without metadata dict
     # Version 2 populate_* include metadata dict
-    INTERFACE_VERSION: int = 2
+    # Version 3 - First version with short and leverage support
+    INTERFACE_VERSION: int = 3
 
     _populate_fun_len: int = 0
     _buy_fun_len: int = 0
     _sell_fun_len: int = 0
-    _ft_params_from_file: Dict = {}
+    _ft_params_from_file: Dict
     # associated minimal roi
-    minimal_roi: Dict
+    minimal_roi: Dict = {}
 
     # associated stoploss
     stoploss: float
@@ -79,14 +66,16 @@ class IStrategy(ABC, HyperStrategyMixin):
     trailing_only_offset_is_reached = False
     use_custom_stoploss: bool = False
 
+    # Can this strategy go short?
+    can_short: bool = False
+
     # associated timeframe
-    ticker_interval: str  # DEPRECATED
     timeframe: str
 
     # Optional order types
     order_types: Dict = {
-        'buy': 'limit',
-        'sell': 'limit',
+        'entry': 'limit',
+        'exit': 'limit',
         'stoploss': 'limit',
         'stoploss_on_exchange': False,
         'stoploss_on_exchange_interval': 60,
@@ -94,17 +83,21 @@ class IStrategy(ABC, HyperStrategyMixin):
 
     # Optional time in force
     order_time_in_force: Dict = {
-        'buy': 'gtc',
-        'sell': 'gtc',
+        'entry': 'gtc',
+        'exit': 'gtc',
     }
 
     # run "populate_indicators" only for new candle
     process_only_new_candles: bool = False
 
-    use_sell_signal: bool
-    sell_profit_only: bool
-    sell_profit_offset: float
-    ignore_roi_if_buy_signal: bool
+    use_exit_signal: bool
+    exit_profit_only: bool
+    exit_profit_offset: float
+    ignore_roi_if_entry_signal: bool
+
+    # Position adjustment is disabled by default
+    position_adjustment_enable: bool = False
+    max_entry_position_adjustment: int = -1
 
     # Number of seconds after which the candle will no longer result in a buy on expired candles
     ignore_buying_expired_candle_after: int = 0
@@ -153,31 +146,41 @@ class IStrategy(ABC, HyperStrategyMixin):
                 if timeframe_to_minutes(informative_data.timeframe) < strategy_timeframe_minutes:
                     raise OperationalException('Informative timeframe must be equal or higher than '
                                                'strategy timeframe!')
+                if not informative_data.candle_type:
+                    informative_data.candle_type = config['candle_type_def']
                 self._ft_informative.append((informative_data, cls_method))
 
     @abstractmethod
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Populate indicators that will be used in the Buy and Sell strategy
+        Populate indicators that will be used in the Buy, Sell, Short, Exit_short strategy
         :param dataframe: DataFrame with data from the exchange
         :param metadata: Additional information, like the currently traded pair
         :return: a Dataframe with all mandatory indicators for the strategies
         """
         return dataframe
 
-    @abstractmethod
     def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators, populates the buy signal for the given dataframe
+        DEPRECATED - please migrate to populate_entry_trend
         :param dataframe: DataFrame
         :param metadata: Additional information, like the currently traded pair
         :return: DataFrame with buy column
         """
         return dataframe
 
-    @abstractmethod
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the entry signal for the given dataframe
+        :param dataframe: DataFrame
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with entry columns populated
+        """
+        return self.populate_buy_trend(dataframe, metadata)
+
     def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
+        DEPRECATED - please migrate to populate_exit_trend
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
         :param metadata: Additional information, like the currently traded pair
@@ -185,41 +188,14 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         return dataframe
 
-    def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Check buy timeout function callback.
-        This method can be used to override the buy-timeout.
-        It is called whenever a limit buy order has been created,
-        and is not yet fully filled.
-        Configuration options in `unfilledtimeout` will be verified before this,
-        so ensure to set these timeouts high enough.
-
-        When not implemented by a strategy, this simply returns False.
-        :param pair: Pair the trade is for
-        :param trade: trade object.
-        :param order: Order dictionary as returned from CCXT.
-        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        :return bool: When True is returned, then the buy-order is cancelled.
+        Based on TA indicators, populates the exit signal for the given dataframe
+        :param dataframe: DataFrame
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with exit columns populated
         """
-        return False
-
-    def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
-        """
-        Check sell timeout function callback.
-        This method can be used to override the sell-timeout.
-        It is called whenever a limit sell order has been created,
-        and is not yet fully filled.
-        Configuration options in `unfilledtimeout` will be verified before this,
-        so ensure to set these timeouts high enough.
-
-        When not implemented by a strategy, this simply returns False.
-        :param pair: Pair the trade is for
-        :param trade: trade object.
-        :param order: Order dictionary as returned from CCXT.
-        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        :return bool: When True is returned, then the sell-order is cancelled.
-        """
-        return False
+        return self.populate_sell_trend(dataframe, metadata)
 
     def bot_loop_start(self, **kwargs) -> None:
         """
@@ -230,10 +206,67 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         pass
 
-    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
-                            time_in_force: str, current_time: datetime, **kwargs) -> bool:
+    def check_buy_timeout(self, pair: str, trade: Trade, order: Order,
+                          current_time: datetime, **kwargs) -> bool:
         """
-        Called right before placing a buy order.
+        DEPRECATED: Please use `check_entry_timeout` instead.
+        """
+        return False
+
+    def check_entry_timeout(self, pair: str, trade: Trade, order: Order,
+                            current_time: datetime, **kwargs) -> bool:
+        """
+        Check entry timeout function callback.
+        This method can be used to override the entry-timeout.
+        It is called whenever a limit entry order has been created,
+        and is not yet fully filled.
+        Configuration options in `unfilledtimeout` will be verified before this,
+        so ensure to set these timeouts high enough.
+
+        When not implemented by a strategy, this simply returns False.
+        :param pair: Pair the trade is for
+        :param trade: Trade object.
+        :param order: Order object.
+        :param current_time: datetime object, containing the current datetime
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the entry order is cancelled.
+        """
+        return self.check_buy_timeout(
+            pair=pair, trade=trade, order=order, current_time=current_time)
+
+    def check_sell_timeout(self, pair: str, trade: Trade, order: Order,
+                           current_time: datetime, **kwargs) -> bool:
+        """
+        DEPRECATED: Please use `check_exit_timeout` instead.
+        """
+        return False
+
+    def check_exit_timeout(self, pair: str, trade: Trade, order: Order,
+                           current_time: datetime, **kwargs) -> bool:
+        """
+        Check exit timeout function callback.
+        This method can be used to override the exit-timeout.
+        It is called whenever a limit exit order has been created,
+        and is not yet fully filled.
+        Configuration options in `unfilledtimeout` will be verified before this,
+        so ensure to set these timeouts high enough.
+
+        When not implemented by a strategy, this simply returns False.
+        :param pair: Pair the trade is for
+        :param trade: Trade object.
+        :param order: Order object
+        :param current_time: datetime object, containing the current datetime
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the exit-order is cancelled.
+        """
+        return self.check_sell_timeout(
+            pair=pair, trade=trade, order=order, current_time=current_time)
+
+    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
+                            time_in_force: str, current_time: datetime, entry_tag: Optional[str],
+                            side: str, **kwargs) -> bool:
+        """
+        Called right before placing a entry order.
         Timing for this function is critical, so avoid doing heavy computations or
         network requests in this method.
 
@@ -241,12 +274,14 @@ class IStrategy(ABC, HyperStrategyMixin):
 
         When not implemented by a strategy, returns True (always confirming).
 
-        :param pair: Pair that's about to be bought.
+        :param pair: Pair that's about to be bought/shorted.
         :param order_type: Order type (as configured in order_types). usually limit or market.
         :param amount: Amount in target (quote) currency that's going to be traded.
         :param rate: Rate that's going to be used when using limit orders
         :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
         :param current_time: datetime object, containing the current datetime
+        :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
+        :param side: 'long' or 'short' - indicating the direction of the proposed trade
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return bool: When True is returned, then the buy-order is placed on the exchange.
             False aborts the process
@@ -254,10 +289,10 @@ class IStrategy(ABC, HyperStrategyMixin):
         return True
 
     def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
-                           rate: float, time_in_force: str, sell_reason: str,
+                           rate: float, time_in_force: str, exit_reason: str,
                            current_time: datetime, **kwargs) -> bool:
         """
-        Called right before placing a regular sell order.
+        Called right before placing a regular exit order.
         Timing for this function is critical, so avoid doing heavy computations or
         network requests in this method.
 
@@ -265,18 +300,18 @@ class IStrategy(ABC, HyperStrategyMixin):
 
         When not implemented by a strategy, returns True (always confirming).
 
-        :param pair: Pair that's about to be sold.
+        :param pair: Pair for trade that's about to be exited.
         :param trade: trade object.
         :param order_type: Order type (as configured in order_types). usually limit or market.
         :param amount: Amount in quote currency.
         :param rate: Rate that's going to be used when using limit orders
         :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
-        :param sell_reason: Sell reason.
+        :param exit_reason: Exit reason.
             Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
-                           'sell_signal', 'force_sell', 'emergency_sell']
+                           'exit_signal', 'force_exit', 'emergency_exit']
         :param current_time: datetime object, containing the current datetime
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        :return bool: When True is returned, then the sell-order is placed on the exchange.
+        :return bool: When True, then the exit-order is placed on the exchange.
             False aborts the process
         """
         return True
@@ -296,7 +331,7 @@ class IStrategy(ABC, HyperStrategyMixin):
         :param pair: Pair that's currently analyzed
         :param trade: trade object.
         :param current_time: datetime object, containing the current datetime
-        :param current_rate: Rate, calculated based on pricing settings in ask_strategy.
+        :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
         :param current_profit: Current profit (as ratio), calculated based on current_rate.
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return float: New stoploss value, relative to the current_rate
@@ -304,7 +339,7 @@ class IStrategy(ABC, HyperStrategyMixin):
         return self.stoploss
 
     def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
-                           **kwargs) -> float:
+                           entry_tag: Optional[str], side: str, **kwargs) -> float:
         """
         Custom entry price logic, returning the new entry price.
 
@@ -314,7 +349,9 @@ class IStrategy(ABC, HyperStrategyMixin):
 
         :param pair: Pair that's currently analyzed
         :param current_time: datetime object, containing the current datetime
-        :param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
+        :param proposed_rate: Rate, calculated based on pricing settings in exit_pricing.
+        :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
+        :param side: 'long' or 'short' - indicating the direction of the proposed trade
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return float: New entry price value if provided
         """
@@ -333,7 +370,7 @@ class IStrategy(ABC, HyperStrategyMixin):
         :param pair: Pair that's currently analyzed
         :param trade: trade object.
         :param current_time: datetime object, containing the current datetime
-        :param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
+        :param proposed_rate: Rate, calculated based on pricing settings in exit_pricing.
         :param current_profit: Current profit (as ratio), calculated based on current_rate.
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return float: New exit price value if provided
@@ -343,44 +380,109 @@ class IStrategy(ABC, HyperStrategyMixin):
     def custom_sell(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
                     current_profit: float, **kwargs) -> Optional[Union[str, bool]]:
         """
-        Custom sell signal logic indicating that specified position should be sold. Returning a
-        string or True from this method is equal to setting sell signal on a candle at specified
-        time. This method is not called when sell signal is set.
+        DEPRECATED - please use custom_exit instead.
+        Custom exit signal logic indicating that specified position should be sold. Returning a
+        string or True from this method is equal to setting exit signal on a candle at specified
+        time. This method is not called when exit signal is set.
 
-        This method should be overridden to create sell signals that depend on trade parameters. For
-        example you could implement a sell relative to the candle when the trade was opened,
+        This method should be overridden to create exit signals that depend on trade parameters. For
+        example you could implement an exit relative to the candle when the trade was opened,
         or a custom 1:2 risk-reward ROI.
 
-        Custom sell reason max length is 64. Exceeding characters will be removed.
+        Custom exit reason max length is 64. Exceeding characters will be removed.
 
         :param pair: Pair that's currently analyzed
         :param trade: trade object.
         :param current_time: datetime object, containing the current datetime
-        :param current_rate: Rate, calculated based on pricing settings in ask_strategy.
+        :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
         :param current_profit: Current profit (as ratio), calculated based on current_rate.
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-        :return: To execute sell, return a string with custom sell reason or True. Otherwise return
+        :return: To execute exit, return a string with custom exit reason or True. Otherwise return
         None or False.
         """
         return None
 
+    def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
+                    current_profit: float, **kwargs) -> Optional[Union[str, bool]]:
+        """
+        Custom exit signal logic indicating that specified position should be sold. Returning a
+        string or True from this method is equal to setting exit signal on a candle at specified
+        time. This method is not called when exit signal is set.
+
+        This method should be overridden to create exit signals that depend on trade parameters. For
+        example you could implement an exit relative to the candle when the trade was opened,
+        or a custom 1:2 risk-reward ROI.
+
+        Custom exit reason max length is 64. Exceeding characters will be removed.
+
+        :param pair: Pair that's currently analyzed
+        :param trade: trade object.
+        :param current_time: datetime object, containing the current datetime
+        :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
+        :param current_profit: Current profit (as ratio), calculated based on current_rate.
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return: To execute exit, return a string with custom exit reason or True. Otherwise return
+        None or False.
+        """
+        return self.custom_sell(pair, trade, current_time, current_rate, current_profit, **kwargs)
+
     def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
                             proposed_stake: float, min_stake: float, max_stake: float,
-                            **kwargs) -> float:
+                            entry_tag: Optional[str], side: str, **kwargs) -> float:
         """
-        Customize stake size for each new trade. This method is not called when edge module is
-        enabled.
+        Customize stake size for each new trade.
 
         :param pair: Pair that's currently analyzed
         :param current_time: datetime object, containing the current datetime
-        :param current_rate: Rate, calculated based on pricing settings in ask_strategy.
+        :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
         :param proposed_stake: A stake amount proposed by the bot.
         :param min_stake: Minimal stake size allowed by exchange.
         :param max_stake: Balance available for trading.
+        :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
+        :param side: 'long' or 'short' - indicating the direction of the proposed trade
         :return: A stake size, which is between min_stake and max_stake.
         """
         return proposed_stake
 
+    def adjust_trade_position(self, trade: Trade, current_time: datetime,
+                              current_rate: float, current_profit: float, min_stake: float,
+                              max_stake: float, **kwargs) -> Optional[float]:
+        """
+        Custom trade adjustment logic, returning the stake amount that a trade should be increased.
+        This means extra buy orders with additional fees.
+        Only called when `position_adjustment_enable` is set to True.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns None
+
+        :param trade: trade object.
+        :param current_time: datetime object, containing the current datetime
+        :param current_rate: Current buy rate.
+        :param current_profit: Current profit (as ratio), calculated based on current_rate.
+        :param min_stake: Minimal stake size allowed by exchange.
+        :param max_stake: Balance available for trading.
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return float: Stake amount to adjust your trade
+        """
+        return None
+
+    def leverage(self, pair: str, current_time: datetime, current_rate: float,
+                 proposed_leverage: float, max_leverage: float, side: str,
+                 **kwargs) -> float:
+        """
+        Customize leverage for each new trade. This method is only called in futures mode.
+
+        :param pair: Pair that's currently analyzed
+        :param current_time: datetime object, containing the current datetime
+        :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
+        :param proposed_leverage: A leverage proposed by the bot.
+        :param max_leverage: Max leverage allowed on this pair
+        :param side: 'long' or 'short' - indicating the direction of the proposed trade
+        :return: A leverage amount, which is between 1.0 and max_leverage.
+        """
+        return 1.0
+
     def informative_pairs(self) -> ListPairsWithTimeframes:
         """
         Define additional, informative pair/interval combinations to be cached from the exchange.
@@ -394,6 +496,12 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         return []
 
+    def version(self) -> Optional[str]:
+        """
+        Returns version of the strategy.
+        """
+        return None
+
 ###
 # END - Intended to be overridden by strategy
 ###
@@ -403,16 +511,28 @@ class IStrategy(ABC, HyperStrategyMixin):
         Internal method which gathers all informative pairs (user or automatically defined).
         """
         informative_pairs = self.informative_pairs()
+        # Compatibility code for 2 tuple informative pairs
+        informative_pairs = [
+            (p[0], p[1], CandleType.from_string(p[2]) if len(
+                p) > 2 and p[2] != '' else self.config.get('candle_type_def', CandleType.SPOT))
+            for p in informative_pairs]
         for inf_data, _ in self._ft_informative:
+            # Get default candle type if not provided explicitly.
+            candle_type = (inf_data.candle_type if inf_data.candle_type
+                           else self.config.get('candle_type_def', CandleType.SPOT))
             if inf_data.asset:
-                pair_tf = (_format_pair_name(self.config, inf_data.asset), inf_data.timeframe)
+                pair_tf = (
+                    _format_pair_name(self.config, inf_data.asset),
+                    inf_data.timeframe,
+                    candle_type,
+                )
                 informative_pairs.append(pair_tf)
             else:
                 if not self.dp:
                     raise OperationalException('@informative decorator with unspecified asset '
                                                'requires DataProvider instance.')
                 for pair in self.dp.current_whitelist():
-                    informative_pairs.append((pair, inf_data.timeframe))
+                    informative_pairs.append((pair, inf_data.timeframe, candle_type))
         return list(set(informative_pairs))
 
     def get_strategy_name(self) -> str:
@@ -443,12 +563,21 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         PairLocks.unlock_pair(pair, datetime.now(timezone.utc))
 
+    def unlock_reason(self, reason: str) -> None:
+        """
+        Unlocks all pairs previously locked using lock_pair with specified reason.
+        Not used by freqtrade itself, but intended to be used if users lock pairs
+        manually from within the strategy, to allow an easy way to unlock pairs.
+        :param reason: Unlock pairs to allow trading again
+        """
+        PairLocks.unlock_reason(reason, datetime.now(timezone.utc))
+
     def is_pair_locked(self, pair: str, candle_date: datetime = None) -> bool:
         """
         Checks if a pair is currently locked
         The 2nd, optional parameter ensures that locks are applied until the new candle arrives,
         and not stop at 14:00:00 - while the next candle arrives at 14:00:02 leaving a gap
-        of 2 seconds for a buy to happen on an old signal.
+        of 2 seconds for an entry order to happen on an old signal.
         :param pair: "Pair to check"
         :param candle_date: Date of the last candle. Optional, defaults to current date
         :returns: locking state of the pair in question.
@@ -464,15 +593,15 @@ class IStrategy(ABC, HyperStrategyMixin):
     def analyze_ticker(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Parses the given candle (OHLCV) data and returns a populated DataFrame
-        add several TA indicators and buy signal to it
+        add several TA indicators and entry order signal to it
         :param dataframe: Dataframe containing data from exchange
         :param metadata: Metadata dictionary with additional data (e.g. 'pair')
         :return: DataFrame of candle (OHLCV) data with indicator data and signals added
         """
         logger.debug("TA Analysis Launched")
         dataframe = self.advise_indicators(dataframe, metadata)
-        dataframe = self.advise_buy(dataframe, metadata)
-        dataframe = self.advise_sell(dataframe, metadata)
+        dataframe = self.advise_entry(dataframe, metadata)
+        dataframe = self.advise_exit(dataframe, metadata)
         return dataframe
 
     def _analyze_ticker_internal(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -494,15 +623,18 @@ class IStrategy(ABC, HyperStrategyMixin):
             dataframe = self.analyze_ticker(dataframe, metadata)
             self._last_candle_seen_per_pair[pair] = dataframe.iloc[-1]['date']
             if self.dp:
-                self.dp._set_cached_df(pair, self.timeframe, dataframe)
+                self.dp._set_cached_df(
+                    pair, self.timeframe, dataframe,
+                    candle_type=self.config.get('candle_type_def', CandleType.SPOT))
         else:
             logger.debug("Skipping TA Analysis for already analyzed candle")
-            dataframe['buy'] = 0
-            dataframe['sell'] = 0
-            dataframe['buy_tag'] = None
+            dataframe[SignalType.ENTER_LONG.value] = 0
+            dataframe[SignalType.EXIT_LONG.value] = 0
+            dataframe[SignalType.ENTER_SHORT.value] = 0
+            dataframe[SignalType.EXIT_SHORT.value] = 0
+            dataframe[SignalTagType.ENTER_TAG.value] = None
+            dataframe[SignalTagType.EXIT_TAG.value] = None
 
-        # Other Defs in strategy that want to be called every loop here
-        # twitter_sell = self.watch_twitter_feed(dataframe, metadata)
         logger.debug("Loop Analysis Launched")
 
         return dataframe
@@ -516,7 +648,9 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         if not self.dp:
             raise OperationalException("DataProvider not found.")
-        dataframe = self.dp.ohlcv(pair, self.timeframe)
+        dataframe = self.dp.ohlcv(
+            pair, self.timeframe, candle_type=self.config.get('candle_type_def', CandleType.SPOT)
+        )
         if not isinstance(dataframe, DataFrame) or dataframe.empty:
             logger.warning('Empty candle (OHLCV) data for pair %s', pair)
             return
@@ -558,8 +692,8 @@ class IStrategy(ABC, HyperStrategyMixin):
         message = ""
         if dataframe is None:
             message = "No dataframe returned (return statement missing?)."
-        elif 'buy' not in dataframe:
-            message = "Buy column not set."
+        elif 'enter_long' not in dataframe:
+            message = "enter_long/buy column not set."
         elif df_len != len(dataframe):
             message = message_template.format("length")
         elif df_close != dataframe["close"].iloc[-1]:
@@ -572,23 +706,24 @@ class IStrategy(ABC, HyperStrategyMixin):
             else:
                 raise StrategyError(message)
 
-    def get_signal(
+    def get_latest_candle(
         self,
         pair: str,
         timeframe: str,
-        dataframe: DataFrame
-    ) -> Tuple[bool, bool, Optional[str]]:
+        dataframe: DataFrame,
+    ) -> Tuple[Optional[DataFrame], Optional[arrow.Arrow]]:
         """
-        Calculates current signal based based on the buy / sell columns of the dataframe.
-        Used by Bot to get the signal to buy or sell
+        Calculates current signal based based on the entry order or exit order
+        columns of the dataframe.
+        Used by Bot to get the signal to enter, or exit
         :param pair: pair in format ANT/BTC
         :param timeframe: timeframe to use
         :param dataframe: Analyzed dataframe to get signal from.
-        :return: (Buy, Sell) A bool-tuple indicating buy/sell signal
+        :return: (None, None) or (Dataframe, latest_date) - corresponding to the last candle
         """
         if not isinstance(dataframe, DataFrame) or dataframe.empty:
             logger.warning(f'Empty candle (OHLCV) data for pair {pair}')
-            return False, False, None
+            return None, None
 
         latest_date = dataframe['date'].max()
         latest = dataframe.loc[dataframe['date'] == latest_date].iloc[-1]
@@ -603,122 +738,200 @@ class IStrategy(ABC, HyperStrategyMixin):
                 'Outdated history for pair %s. Last tick is %s minutes old',
                 pair, int((arrow.utcnow() - latest_date).total_seconds() // 60)
             )
+            return None, None
+        return latest, latest_date
+
+    def get_exit_signal(
+        self,
+        pair: str,
+        timeframe: str,
+        dataframe: DataFrame,
+        is_short: bool = None
+    ) -> Tuple[bool, bool, Optional[str]]:
+        """
+        Calculates current exit signal based based on the dataframe
+        columns of the dataframe.
+        Used by Bot to get the signal to exit.
+        depending on is_short, looks at "short" or "long" columns.
+        :param pair: pair in format ANT/BTC
+        :param timeframe: timeframe to use
+        :param dataframe: Analyzed dataframe to get signal from.
+        :param is_short: Indicating existing trade direction.
+        :return: (enter, exit) A bool-tuple with enter / exit values.
+        """
+        latest, latest_date = self.get_latest_candle(pair, timeframe, dataframe)
+        if latest is None:
             return False, False, None
 
-        buy = latest[SignalType.BUY.value] == 1
+        if is_short:
+            enter = latest.get(SignalType.ENTER_SHORT.value, 0) == 1
+            exit_ = latest.get(SignalType.EXIT_SHORT.value, 0) == 1
 
-        sell = False
-        if SignalType.SELL.value in latest:
-            sell = latest[SignalType.SELL.value] == 1
+        else:
+            enter = latest[SignalType.ENTER_LONG.value] == 1
+            exit_ = latest.get(SignalType.EXIT_LONG.value, 0) == 1
+        exit_tag = latest.get(SignalTagType.EXIT_TAG.value, None)
+        # Tags can be None, which does not resolve to False.
+        exit_tag = exit_tag if isinstance(exit_tag, str) else None
 
-        buy_tag = latest.get(SignalTagType.BUY_TAG.value, None)
+        logger.debug(f"exit-trigger: {latest['date']} (pair={pair}) "
+                     f"enter={enter} exit={exit_}")
+
+        return enter, exit_, exit_tag
+
+    def get_entry_signal(
+        self,
+        pair: str,
+        timeframe: str,
+        dataframe: DataFrame,
+    ) -> Tuple[Optional[SignalDirection], Optional[str]]:
+        """
+        Calculates current entry signal based based on the dataframe signals
+        columns of the dataframe.
+        Used by Bot to get the signal to enter trades.
+        :param pair: pair in format ANT/BTC
+        :param timeframe: timeframe to use
+        :param dataframe: Analyzed dataframe to get signal from.
+        :return: (SignalDirection, entry_tag)
+        """
+        latest, latest_date = self.get_latest_candle(pair, timeframe, dataframe)
+        if latest is None or latest_date is None:
+            return None, None
+
+        enter_long = latest[SignalType.ENTER_LONG.value] == 1
+        exit_long = latest.get(SignalType.EXIT_LONG.value, 0) == 1
+        enter_short = latest.get(SignalType.ENTER_SHORT.value, 0) == 1
+        exit_short = latest.get(SignalType.EXIT_SHORT.value, 0) == 1
+
+        enter_signal: Optional[SignalDirection] = None
+        enter_tag_value: Optional[str] = None
+        if enter_long == 1 and not any([exit_long, enter_short]):
+            enter_signal = SignalDirection.LONG
+            enter_tag_value = latest.get(SignalTagType.ENTER_TAG.value, None)
+        if (self.config.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT
+                and self.can_short
+                and enter_short == 1 and not any([exit_short, enter_long])):
+            enter_signal = SignalDirection.SHORT
+            enter_tag_value = latest.get(SignalTagType.ENTER_TAG.value, None)
+
+        enter_tag_value = enter_tag_value if isinstance(enter_tag_value, str) else None
 
-        logger.debug('trigger: %s (pair=%s) buy=%s sell=%s',
-                     latest['date'], pair, str(buy), str(sell))
         timeframe_seconds = timeframe_to_seconds(timeframe)
-        if self.ignore_expired_candle(latest_date=latest_date,
-                                      current_time=datetime.now(timezone.utc),
-                                      timeframe_seconds=timeframe_seconds,
-                                      buy=buy):
-            return False, sell, buy_tag
-        return buy, sell, buy_tag
 
-    def ignore_expired_candle(self, latest_date: datetime, current_time: datetime,
-                              timeframe_seconds: int, buy: bool):
-        if self.ignore_buying_expired_candle_after and buy:
+        if self.ignore_expired_candle(
+            latest_date=latest_date.datetime,
+            current_time=datetime.now(timezone.utc),
+            timeframe_seconds=timeframe_seconds,
+            enter=bool(enter_signal)
+        ):
+            return None, enter_tag_value
+
+        logger.debug(f"entry trigger: {latest['date']} (pair={pair}) "
+                     f"enter={enter_long} enter_tag_value={enter_tag_value}")
+        return enter_signal, enter_tag_value
+
+    def ignore_expired_candle(
+        self,
+        latest_date: datetime,
+        current_time: datetime,
+        timeframe_seconds: int,
+        enter: bool
+    ):
+        if self.ignore_buying_expired_candle_after and enter:
             time_delta = current_time - (latest_date + timedelta(seconds=timeframe_seconds))
             return time_delta.total_seconds() > self.ignore_buying_expired_candle_after
         else:
             return False
 
-    def should_sell(self, trade: Trade, rate: float, date: datetime, buy: bool,
-                    sell: bool, low: float = None, high: float = None,
-                    force_stoploss: float = 0) -> SellCheckTuple:
+    def should_exit(self, trade: Trade, rate: float, current_time: datetime, *,
+                    enter: bool, exit_: bool,
+                    low: float = None, high: float = None,
+                    force_stoploss: float = 0) -> ExitCheckTuple:
         """
-        This function evaluates if one of the conditions required to trigger a sell
-        has been reached, which can either be a stop-loss, ROI or sell-signal.
-        :param low: Only used during backtesting to simulate stoploss
-        :param high: Only used during backtesting, to simulate ROI
+        This function evaluates if one of the conditions required to trigger an exit order
+        has been reached, which can either be a stop-loss, ROI or exit-signal.
+        :param low: Only used during backtesting to simulate (long)stoploss/(short)ROI
+        :param high: Only used during backtesting, to simulate (short)stoploss/(long)ROI
         :param force_stoploss: Externally provided stoploss
-        :return: True if trade should be sold, False otherwise
+        :return: True if trade should be exited, False otherwise
         """
+
         current_rate = rate
         current_profit = trade.calc_profit_ratio(current_rate)
 
         trade.adjust_min_max_rates(high or current_rate, low or current_rate)
 
         stoplossflag = self.stop_loss_reached(current_rate=current_rate, trade=trade,
-                                              current_time=date, current_profit=current_profit,
+                                              current_time=current_time,
+                                              current_profit=current_profit,
                                               force_stoploss=force_stoploss, low=low, high=high)
 
-        # Set current rate to high for backtesting sell
-        current_rate = high or rate
+        # Set current rate to high for backtesting exits
+        current_rate = (low if trade.is_short else high) or rate
         current_profit = trade.calc_profit_ratio(current_rate)
 
-        # if buy signal and ignore_roi is set, we don't need to evaluate min_roi.
-        roi_reached = (not (buy and self.ignore_roi_if_buy_signal)
+        # if enter signal and ignore_roi is set, we don't need to evaluate min_roi.
+        roi_reached = (not (enter and self.ignore_roi_if_entry_signal)
                        and self.min_roi_reached(trade=trade, current_profit=current_profit,
-                                                current_time=date))
+                                                current_time=current_time))
 
-        sell_signal = SellType.NONE
+        exit_signal = ExitType.NONE
         custom_reason = ''
         # use provided rate in backtesting, not high/low.
         current_rate = rate
         current_profit = trade.calc_profit_ratio(current_rate)
 
-        if (self.sell_profit_only and current_profit <= self.sell_profit_offset):
-            # sell_profit_only and profit doesn't reach the offset - ignore sell signal
-            pass
-        elif self.use_sell_signal and not buy:
-            if sell:
-                sell_signal = SellType.SELL_SIGNAL
+        if self.use_exit_signal:
+            if exit_ and not enter:
+                exit_signal = ExitType.EXIT_SIGNAL
             else:
-                custom_reason = strategy_safe_wrapper(self.custom_sell, default_retval=False)(
-                    pair=trade.pair, trade=trade, current_time=date, current_rate=current_rate,
-                    current_profit=current_profit)
+                custom_reason = strategy_safe_wrapper(self.custom_exit, default_retval=False)(
+                    pair=trade.pair, trade=trade, current_time=current_time,
+                    current_rate=current_rate, current_profit=current_profit)
                 if custom_reason:
-                    sell_signal = SellType.CUSTOM_SELL
+                    exit_signal = ExitType.CUSTOM_EXIT
                     if isinstance(custom_reason, str):
-                        if len(custom_reason) > CUSTOM_SELL_MAX_LENGTH:
-                            logger.warning(f'Custom sell reason returned from custom_sell is too '
-                                           f'long and was trimmed to {CUSTOM_SELL_MAX_LENGTH} '
-                                           f'characters.')
-                            custom_reason = custom_reason[:CUSTOM_SELL_MAX_LENGTH]
+                        if len(custom_reason) > CUSTOM_EXIT_MAX_LENGTH:
+                            logger.warning(f'Custom exit reason returned from '
+                                           f'custom_exit is too long and was trimmed'
+                                           f'to {CUSTOM_EXIT_MAX_LENGTH} characters.')
+                            custom_reason = custom_reason[:CUSTOM_EXIT_MAX_LENGTH]
                     else:
                         custom_reason = None
-            # TODO: return here if sell-signal should be favored over ROI
+            if (
+                exit_signal == ExitType.CUSTOM_EXIT
+                or (exit_signal == ExitType.EXIT_SIGNAL
+                    and (not self.exit_profit_only or current_profit > self.exit_profit_offset))
+            ):
+                logger.debug(f"{trade.pair} - Sell signal received. "
+                             f"exit_type=ExitType.{exit_signal.name}" +
+                             (f", custom_reason={custom_reason}" if custom_reason else ""))
+                return ExitCheckTuple(exit_type=exit_signal, exit_reason=custom_reason)
 
-        # Start evaluations
         # Sequence:
+        # Exit-signal
         # ROI (if not stoploss)
-        # Sell-signal
         # Stoploss
-        if roi_reached and stoplossflag.sell_type != SellType.STOP_LOSS:
-            logger.debug(f"{trade.pair} - Required profit reached. sell_type=SellType.ROI")
-            return SellCheckTuple(sell_type=SellType.ROI)
+        if roi_reached and stoplossflag.exit_type != ExitType.STOP_LOSS:
+            logger.debug(f"{trade.pair} - Required profit reached. exit_type=ExitType.ROI")
+            return ExitCheckTuple(exit_type=ExitType.ROI)
 
-        if sell_signal != SellType.NONE:
-            logger.debug(f"{trade.pair} - Sell signal received. "
-                         f"sell_type=SellType.{sell_signal.name}" +
-                         (f", custom_reason={custom_reason}" if custom_reason else ""))
-            return SellCheckTuple(sell_type=sell_signal, sell_reason=custom_reason)
+        if stoplossflag.exit_flag:
 
-        if stoplossflag.sell_flag:
-
-            logger.debug(f"{trade.pair} - Stoploss hit. sell_type={stoplossflag.sell_type}")
+            logger.debug(f"{trade.pair} - Stoploss hit. exit_type={stoplossflag.exit_type}")
             return stoplossflag
 
         # This one is noisy, commented out...
-        # logger.debug(f"{trade.pair} - No sell signal.")
-        return SellCheckTuple(sell_type=SellType.NONE)
+        # logger.debug(f"{trade.pair} - No exit signal.")
+        return ExitCheckTuple(exit_type=ExitType.NONE)
 
     def stop_loss_reached(self, current_rate: float, trade: Trade,
                           current_time: datetime, current_profit: float,
                           force_stoploss: float, low: float = None,
-                          high: float = None) -> SellCheckTuple:
+                          high: float = None) -> ExitCheckTuple:
         """
         Based on current profit of the trade and configured (trailing) stoploss,
-        decides to sell or not
+        decides to exit or not
         :param current_profit: current profit as ratio
         :param low: Low value of this candle, only set in backtesting
         :param high: High value of this candle, only set in backtesting
@@ -728,7 +941,12 @@ class IStrategy(ABC, HyperStrategyMixin):
         # Initiate stoploss with open_rate. Does nothing if stoploss is already set.
         trade.adjust_stop_loss(trade.open_rate, stop_loss_value, initial=True)
 
-        if self.use_custom_stoploss and trade.stop_loss < (low or current_rate):
+        dir_correct = (trade.stop_loss < (low or current_rate)
+                       if not trade.is_short else
+                       trade.stop_loss > (high or current_rate)
+                       )
+
+        if self.use_custom_stoploss and dir_correct:
             stop_loss_value = strategy_safe_wrapper(self.custom_stoploss, default_retval=None
                                                     )(pair=trade.pair, trade=trade,
                                                       current_time=current_time,
@@ -741,45 +959,56 @@ class IStrategy(ABC, HyperStrategyMixin):
             else:
                 logger.warning("CustomStoploss function did not return valid stoploss")
 
-        if self.trailing_stop and trade.stop_loss < (low or current_rate):
+        sl_lower_long = (trade.stop_loss < (low or current_rate) and not trade.is_short)
+        sl_higher_short = (trade.stop_loss > (high or current_rate) and trade.is_short)
+        if self.trailing_stop and (sl_lower_long or sl_higher_short):
             # trailing stoploss handling
             sl_offset = self.trailing_stop_positive_offset
 
             # Make sure current_profit is calculated using high for backtesting.
-            high_profit = current_profit if not high else trade.calc_profit_ratio(high)
+            bound = low if trade.is_short else high
+            bound_profit = current_profit if not bound else trade.calc_profit_ratio(bound)
 
             # Don't update stoploss if trailing_only_offset_is_reached is true.
-            if not (self.trailing_only_offset_is_reached and high_profit < sl_offset):
+            if not (self.trailing_only_offset_is_reached and bound_profit < sl_offset):
                 # Specific handling for trailing_stop_positive
-                if self.trailing_stop_positive is not None and high_profit > sl_offset:
+                if self.trailing_stop_positive is not None and bound_profit > sl_offset:
                     stop_loss_value = self.trailing_stop_positive
                     logger.debug(f"{trade.pair} - Using positive stoploss: {stop_loss_value} "
-                                 f"offset: {sl_offset:.4g} profit: {current_profit:.4f}%")
+                                 f"offset: {sl_offset:.4g} profit: {current_profit:.2%}")
 
-                trade.adjust_stop_loss(high or current_rate, stop_loss_value)
+                trade.adjust_stop_loss(bound or current_rate, stop_loss_value)
 
+        sl_higher_long = (trade.stop_loss >= (low or current_rate) and not trade.is_short)
+        sl_lower_short = (trade.stop_loss <= (high or current_rate) and trade.is_short)
         # evaluate if the stoploss was hit if stoploss is not on exchange
         # in Dry-Run, this handles stoploss logic as well, as the logic will not be different to
         # regular stoploss handling.
-        if ((trade.stop_loss >= (low or current_rate)) and
+        if ((sl_higher_long or sl_lower_short) and
                 (not self.order_types.get('stoploss_on_exchange') or self.config['dry_run'])):
 
-            sell_type = SellType.STOP_LOSS
+            exit_type = ExitType.STOP_LOSS
 
             # If initial stoploss is not the same as current one then it is trailing.
             if trade.initial_stop_loss != trade.stop_loss:
-                sell_type = SellType.TRAILING_STOP_LOSS
+                exit_type = ExitType.TRAILING_STOP_LOSS
                 logger.debug(
-                    f"{trade.pair} - HIT STOP: current price at {(low or current_rate):.6f}, "
+                    f"{trade.pair} - HIT STOP: current price at "
+                    f"{((high if trade.is_short else low) or current_rate):.6f}, "
                     f"stoploss is {trade.stop_loss:.6f}, "
                     f"initial stoploss was at {trade.initial_stop_loss:.6f}, "
                     f"trade opened at {trade.open_rate:.6f}")
+                new_stoploss = (
+                    trade.stop_loss + trade.initial_stop_loss
+                    if trade.is_short else
+                    trade.stop_loss - trade.initial_stop_loss
+                )
                 logger.debug(f"{trade.pair} - Trailing stop saved "
-                             f"{trade.stop_loss - trade.initial_stop_loss:.6f}")
+                             f"{new_stoploss:.6f}")
 
-            return SellCheckTuple(sell_type=sell_type)
+            return ExitCheckTuple(exit_type=exit_type)
 
-        return SellCheckTuple(sell_type=SellType.NONE)
+        return ExitCheckTuple(exit_type=ExitType.NONE)
 
     def min_roi_reached_entry(self, trade_dur: int) -> Tuple[Optional[int], Optional[float]]:
         """
@@ -797,9 +1026,9 @@ class IStrategy(ABC, HyperStrategyMixin):
     def min_roi_reached(self, trade: Trade, current_profit: float, current_time: datetime) -> bool:
         """
         Based on trade duration, current profit of the trade and ROI configuration,
-        decides whether bot should sell.
+        decides whether bot should exit.
         :param current_profit: current profit as ratio
-        :return: True if bot should sell at current rate
+        :return: True if bot should exit at current rate
         """
         # Check if time matches and current rate is above threshold
         trade_dur = int((current_time.timestamp() - trade.open_date_utc.timestamp()) // 60)
@@ -809,10 +1038,34 @@ class IStrategy(ABC, HyperStrategyMixin):
         else:
             return current_profit > roi
 
+    def ft_check_timed_out(self, trade: LocalTrade, order: Order,
+                           current_time: datetime) -> bool:
+        """
+        FT Internal method.
+        Check if timeout is active, and if the order is still open and timed out
+        """
+        side = 'entry' if order.ft_order_side == trade.entry_side else 'exit'
+
+        timeout = self.config.get('unfilledtimeout', {}).get(side)
+        if timeout is not None:
+            timeout_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
+            timeout_kwargs = {timeout_unit: -timeout}
+            timeout_threshold = current_time + timedelta(**timeout_kwargs)
+            timedout = (order.status == 'open' and order.order_date_utc < timeout_threshold)
+            if timedout:
+                return True
+        time_method = (self.check_exit_timeout if order.side == trade.exit_side
+                       else self.check_entry_timeout)
+
+        return strategy_safe_wrapper(time_method,
+                                     default_retval=False)(
+                                        pair=trade.pair, trade=trade, order=order,
+                                        current_time=current_time)
+
     def advise_all_indicators(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
         """
         Populates indicators for given candle (OHLCV) data (for multiple pairs)
-        Does not run advise_buy or advise_sell!
+        Does not run advise_entry or advise_exit!
         Used by optimize operations only, not during dry / live runs.
         Using .copy() to get a fresh copy of the dataframe for every strategy run.
         Also copy on output to avoid PerformanceWarnings pandas 1.3.0 started to show.
@@ -824,7 +1077,7 @@ class IStrategy(ABC, HyperStrategyMixin):
 
     def advise_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Populate indicators that will be used in the Buy and Sell strategy
+        Populate indicators that will be used in the Buy, Sell, short, exit_short strategy
         This method should not be overridden.
         :param dataframe: Dataframe with data from the exchange
         :param metadata: Additional information, like the currently traded pair
@@ -844,37 +1097,46 @@ class IStrategy(ABC, HyperStrategyMixin):
         else:
             return self.populate_indicators(dataframe, metadata)
 
-    def advise_buy(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    def advise_entry(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators, populates the buy signal for the given dataframe
+        Based on TA indicators, populates the entry order signal for the given dataframe
         This method should not be overridden.
         :param dataframe: DataFrame
         :param metadata: Additional information dictionary, with details like the
             currently traded pair
         :return: DataFrame with buy column
         """
-        logger.debug(f"Populating buy signals for pair {metadata.get('pair')}.")
+
+        logger.debug(f"Populating enter signals for pair {metadata.get('pair')}.")
 
         if self._buy_fun_len == 2:
             warnings.warn("deprecated - check out the Sample strategy to see "
                           "the current function headers!", DeprecationWarning)
-            return self.populate_buy_trend(dataframe)  # type: ignore
+            df = self.populate_buy_trend(dataframe)  # type: ignore
         else:
-            return self.populate_buy_trend(dataframe, metadata)
+            df = self.populate_entry_trend(dataframe, metadata)
+        if 'enter_long' not in df.columns:
+            df = df.rename({'buy': 'enter_long', 'buy_tag': 'enter_tag'}, axis='columns')
 
-    def advise_sell(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        return df
+
+    def advise_exit(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators, populates the sell signal for the given dataframe
+        Based on TA indicators, populates the exit order signal for the given dataframe
         This method should not be overridden.
         :param dataframe: DataFrame
         :param metadata: Additional information dictionary, with details like the
             currently traded pair
-        :return: DataFrame with sell column
+        :return: DataFrame with exit column
         """
-        logger.debug(f"Populating sell signals for pair {metadata.get('pair')}.")
+
+        logger.debug(f"Populating exit signals for pair {metadata.get('pair')}.")
         if self._sell_fun_len == 2:
             warnings.warn("deprecated - check out the Sample strategy to see "
                           "the current function headers!", DeprecationWarning)
-            return self.populate_sell_trend(dataframe)  # type: ignore
+            df = self.populate_sell_trend(dataframe)  # type: ignore
         else:
-            return self.populate_sell_trend(dataframe, metadata)
+            df = self.populate_exit_trend(dataframe, metadata)
+        if 'exit_long' not in df.columns:
+            df = df.rename({'sell': 'exit_long'}, axis='columns')
+        return df
diff --git a/freqtrade/strategy/strategy_helper.py b/freqtrade/strategy/strategy_helper.py
index 175bcaccb..a36cb3dbb 100644
--- a/freqtrade/strategy/strategy_helper.py
+++ b/freqtrade/strategy/strategy_helper.py
@@ -66,7 +66,11 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
     return dataframe
 
 
-def stoploss_from_open(open_relative_stop: float, current_profit: float) -> float:
+def stoploss_from_open(
+    open_relative_stop: float,
+    current_profit: float,
+    is_short: bool = False
+) -> float:
     """
 
     Given the current profit, and a desired stop loss value relative to the open price,
@@ -76,24 +80,29 @@ def stoploss_from_open(open_relative_stop: float, current_profit: float) -> floa
     The requested stop can be positive for a stop above the open price, or negative for
     a stop below the open price. The return value is always >= 0.
 
-    Returns 0 if the resulting stop price would be above the current price.
+    Returns 0 if the resulting stop price would be above/below (longs/shorts) the current price
 
     :param open_relative_stop: Desired stop loss percentage relative to open price
     :param current_profit: The current profit percentage
-    :return: Positive stop loss value relative to current price
+    :param is_short: When true, perform the calculation for short instead of long
+    :return: Stop loss value relative to current price
     """
 
-    # formula is undefined for current_profit -1, return maximum value
-    if current_profit == -1:
+    # formula is undefined for current_profit -1 (longs) or 1 (shorts), return maximum value
+    if (current_profit == -1 and not is_short) or (is_short and current_profit == 1):
         return 1
 
-    stoploss = 1-((1+open_relative_stop)/(1+current_profit))
+    if is_short is True:
+        stoploss = -1 + ((1 - open_relative_stop) / (1 - current_profit))
+    else:
+        stoploss = 1 - ((1 + open_relative_stop) / (1 + current_profit))
 
-    # negative stoploss values indicate the requested stop price is higher than the current price
+    # negative stoploss values indicate the requested stop price is higher/lower
+    # (long/short) than the current price
     return max(stoploss, 0.0)
 
 
-def stoploss_from_absolute(stop_rate: float, current_rate: float) -> float:
+def stoploss_from_absolute(stop_rate: float, current_rate: float, is_short: bool = False) -> float:
     """
     Given current price and desired stop price, return a stop loss value that is relative to current
     price.
@@ -105,6 +114,7 @@ def stoploss_from_absolute(stop_rate: float, current_rate: float) -> float:
 
     :param stop_rate: Stop loss price.
     :param current_rate: Current asset price.
+    :param is_short: When true, perform the calculation for short instead of long
     :return: Positive stop loss value relative to current price
     """
 
@@ -113,6 +123,10 @@ def stoploss_from_absolute(stop_rate: float, current_rate: float) -> float:
         return 1
 
     stoploss = 1 - (stop_rate / current_rate)
+    if is_short:
+        stoploss = -stoploss
 
-    # negative stoploss values indicate the requested stop price is higher than the current price
-    return max(stoploss, 0.0)
+    # negative stoploss values indicate the requested stop price is higher/lower
+    # (long/short) than the current price
+    # shorts can yield stoploss values higher than 1, so limit that as well
+    return max(min(stoploss, 1.0), 0.0)
diff --git a/freqtrade/strategy/strategy_wrapper.py b/freqtrade/strategy/strategy_wrapper.py
index 121189b68..9aead8395 100644
--- a/freqtrade/strategy/strategy_wrapper.py
+++ b/freqtrade/strategy/strategy_wrapper.py
@@ -1,4 +1,5 @@
 import logging
+from copy import deepcopy
 
 from freqtrade.exceptions import StrategyError
 
@@ -14,6 +15,9 @@ def strategy_safe_wrapper(f, message: str = "", default_retval=None, supress_err
     """
     def wrapper(*args, **kwargs):
         try:
+            if 'trade' in kwargs:
+                # Protect accidental modifications from within the strategy
+                kwargs['trade'] = deepcopy(kwargs['trade'])
             return f(*args, **kwargs)
         except ValueError as error:
             logger.warning(
diff --git a/freqtrade/templates/base_config.json.j2 b/freqtrade/templates/base_config.json.j2
index 68eebdbd4..914aa964b 100644
--- a/freqtrade/templates/base_config.json.j2
+++ b/freqtrade/templates/base_config.json.j2
@@ -10,27 +10,29 @@
     "stake_currency": "{{ stake_currency }}",
     "stake_amount": {{ stake_amount }},
     "tradable_balance_ratio": 0.99,
-    "fiat_display_currency": "{{ fiat_display_currency }}",
-    "timeframe": "{{ timeframe }}",
+    "fiat_display_currency": "{{ fiat_display_currency }}",{{ ('\n    "timeframe": "' + timeframe + '",') if timeframe else '' }}
     "dry_run": {{ dry_run | lower }},
     "cancel_open_orders_on_exit": false,
+    "trading_mode": "{{ trading_mode }}",
+    "margin_mode": "{{ margin_mode }}",
     "unfilledtimeout": {
-        "buy": 10,
-        "sell": 30,
+        "entry": 10,
+        "exit": 10,
+        "exit_timeout_count": 0,
         "unit": "minutes"
     },
-    "bid_strategy": {
-        "price_side": "bid",
-        "ask_last_balance": 0.0,
+    "entry_pricing": {
+        "price_side": "same",
         "use_order_book": true,
         "order_book_top": 1,
+        "price_last_balance": 0.0,
         "check_depth_of_market": {
             "enabled": false,
             "bids_to_ask_delta": 1
         }
     },
-    "ask_strategy": {
-        "price_side": "ask",
+    "exit_pricing":{
+        "price_side": "same",
         "use_order_book": true,
         "order_book_top": 1
     },
@@ -70,7 +72,7 @@
     },
     "bot_name": "freqtrade",
     "initial_state": "running",
-    "forcebuy_enable": false,
+    "force_entry_enable": false,
     "internals": {
         "process_throttle_secs": 5
     }
diff --git a/freqtrade/templates/base_strategy.py.j2 b/freqtrade/templates/base_strategy.py.j2
index 06d7cbc5c..53237f67d 100644
--- a/freqtrade/templates/base_strategy.py.j2
+++ b/freqtrade/templates/base_strategy.py.j2
@@ -12,6 +12,7 @@ from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalP
 # --------------------------------
 # Add your lib to import here
 import talib.abstract as ta
+import pandas_ta as pta
 import freqtrade.vendor.qtpylib.indicators as qtpylib
 
 
@@ -28,13 +29,19 @@ class {{ strategy }}(IStrategy):
 
     You must keep:
     - the lib in the section "Do not remove these libs"
-    - the methods: populate_indicators, populate_buy_trend, populate_sell_trend
+    - the methods: populate_indicators, populate_entry_trend, populate_exit_trend
     You should keep:
     - timeframe, minimal_roi, stoploss, trailing_*
     """
     # Strategy interface version - allow new iterations of the strategy interface.
     # Check the documentation or the Sample strategy to get the latest version.
-    INTERFACE_VERSION = 2
+    INTERFACE_VERSION = 3
+
+    # Optimal timeframe for the strategy.
+    timeframe = '5m'
+
+    # Can this strategy go short?
+    can_short: bool = False
 
     # Minimal ROI designed for the strategy.
     # This attribute will be overridden if the config file contains "minimal_roi".
@@ -54,34 +61,36 @@ class {{ strategy }}(IStrategy):
     # trailing_stop_positive = 0.01
     # trailing_stop_positive_offset = 0.0  # Disabled / not configured
 
-    # Optimal timeframe for the strategy.
-    timeframe = '5m'
-
     # Run "populate_indicators()" only for new candle.
     process_only_new_candles = False
 
-    # These values can be overridden in the "ask_strategy" section in the config.
-    use_sell_signal = True
-    sell_profit_only = False
-    ignore_roi_if_buy_signal = False
+    # These values can be overridden in the config.
+    use_exit_signal = True
+    exit_profit_only = False
+    ignore_roi_if_entry_signal = False
 
     # Number of candles the strategy requires before producing valid signals
     startup_candle_count: int = 30
 
+    # Strategy parameters
+    buy_rsi = IntParameter(10, 40, default=30, space="buy")
+    sell_rsi = IntParameter(60, 90, default=70, space="sell")
+
     # Optional order type mapping.
     order_types = {
-        'buy': 'limit',
-        'sell': 'limit',
+        'entry': 'limit',
+        'exit': 'limit',
         'stoploss': 'market',
         'stoploss_on_exchange': False
     }
 
     # Optional order time in force.
     order_time_in_force = {
-        'buy': 'gtc',
-        'sell': 'gtc'
+        'entry': 'gtc',
+        'exit': 'gtc'
     }
     {{ plot_config | indent(4) }}
+
     def informative_pairs(self):
         """
         Define additional, informative pair/interval combinations to be cached from the exchange.
@@ -110,34 +119,52 @@ class {{ strategy }}(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators, populates the buy signal for the given dataframe
-        :param dataframe: DataFrame populated with indicators
+        Based on TA indicators, populates the entry signal for the given dataframe
+        :param dataframe: DataFrame
         :param metadata: Additional information, like the currently traded pair
-        :return: DataFrame with buy column
+        :return: DataFrame with entry columns populated
         """
         dataframe.loc[
             (
                 {{ buy_trend | indent(16) }}
                 (dataframe['volume'] > 0)  # Make sure Volume is not 0
             ),
-            'buy'] = 1
-
-        return dataframe
-
-    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        """
-        Based on TA indicators, populates the sell signal for the given dataframe
-        :param dataframe: DataFrame populated with indicators
-        :param metadata: Additional information, like the currently traded pair
-        :return: DataFrame with buy column
+            'enter_long'] = 1
+        # Uncomment to use shorts (Only used in futures/margin mode. Check the documentation for more info)
         """
         dataframe.loc[
             (
                 {{ sell_trend | indent(16) }}
                 (dataframe['volume'] > 0)  # Make sure Volume is not 0
             ),
-            'sell'] = 1
+            'enter_short'] = 1
+        """
+
+        return dataframe
+
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the exit signal for the given dataframe
+        :param dataframe: DataFrame
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with exit columns populated
+        """
+        dataframe.loc[
+            (
+                {{ sell_trend | indent(16) }}
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            'exit_long'] = 1
+        # Uncomment to use shorts (Only used in futures/margin mode. Check the documentation for more info)
+        """
+        dataframe.loc[
+            (
+                {{ buy_trend | indent(16) }}
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            'exit_short'] = 1
+        """
         return dataframe
     {{ additional_methods | indent(4) }}
diff --git a/freqtrade/templates/sample_strategy.py b/freqtrade/templates/sample_strategy.py
index 574819949..f0ae6c10d 100644
--- a/freqtrade/templates/sample_strategy.py
+++ b/freqtrade/templates/sample_strategy.py
@@ -29,13 +29,16 @@ class SampleStrategy(IStrategy):
 
     You must keep:
     - the lib in the section "Do not remove these libs"
-    - the methods: populate_indicators, populate_buy_trend, populate_sell_trend
+    - the methods: populate_indicators, populate_entry_trend, populate_exit_trend
     You should keep:
     - timeframe, minimal_roi, stoploss, trailing_*
     """
     # Strategy interface version - allow new iterations of the strategy interface.
     # Check the documentation or the Sample strategy to get the latest version.
-    INTERFACE_VERSION = 2
+    INTERFACE_VERSION = 3
+
+    # Can this strategy go short?
+    can_short: bool = False
 
     # Minimal ROI designed for the strategy.
     # This attribute will be overridden if the config file contains "minimal_roi".
@@ -55,36 +58,38 @@ class SampleStrategy(IStrategy):
     # trailing_stop_positive = 0.01
     # trailing_stop_positive_offset = 0.0  # Disabled / not configured
 
-    # Hyperoptable parameters
-    buy_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True)
-    sell_rsi = IntParameter(low=50, high=100, default=70, space='sell', optimize=True, load=True)
-
     # Optimal timeframe for the strategy.
     timeframe = '5m'
 
     # Run "populate_indicators()" only for new candle.
     process_only_new_candles = False
 
-    # These values can be overridden in the "ask_strategy" section in the config.
-    use_sell_signal = True
-    sell_profit_only = False
-    ignore_roi_if_buy_signal = False
+    # These values can be overridden in the config.
+    use_exit_signal = True
+    exit_profit_only = False
+    ignore_roi_if_entry_signal = False
+
+    # Hyperoptable parameters
+    buy_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True)
+    sell_rsi = IntParameter(low=50, high=100, default=70, space='sell', optimize=True, load=True)
+    short_rsi = IntParameter(low=51, high=100, default=70, space='sell', optimize=True, load=True)
+    exit_short_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True)
 
     # Number of candles the strategy requires before producing valid signals
     startup_candle_count: int = 30
 
     # Optional order type mapping.
     order_types = {
-        'buy': 'limit',
-        'sell': 'limit',
+        'entry': 'limit',
+        'exit': 'limit',
         'stoploss': 'market',
         'stoploss_on_exchange': False
     }
 
     # Optional order time in force.
     order_time_in_force = {
-        'buy': 'gtc',
-        'sell': 'gtc'
+        'entry': 'gtc',
+        'exit': 'gtc'
     }
 
     plot_config = {
@@ -337,12 +342,12 @@ class SampleStrategy(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators, populates the buy signal for the given dataframe
-        :param dataframe: DataFrame populated with indicators
+        Based on TA indicators, populates the entry signal for the given dataframe
+        :param dataframe: DataFrame
         :param metadata: Additional information, like the currently traded pair
-        :return: DataFrame with buy column
+        :return: DataFrame with entry columns populated
         """
         dataframe.loc[
             (
@@ -352,16 +357,26 @@ class SampleStrategy(IStrategy):
                 (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard: tema is raising
                 (dataframe['volume'] > 0)  # Make sure Volume is not 0
             ),
-            'buy'] = 1
+            'enter_long'] = 1
+
+        dataframe.loc[
+            (
+                # Signal: RSI crosses above 70
+                (qtpylib.crossed_above(dataframe['rsi'], self.short_rsi.value)) &
+                (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard: tema above BB middle
+                (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard: tema is falling
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            'enter_short'] = 1
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators, populates the sell signal for the given dataframe
-        :param dataframe: DataFrame populated with indicators
+        Based on TA indicators, populates the exit signal for the given dataframe
+        :param dataframe: DataFrame
         :param metadata: Additional information, like the currently traded pair
-        :return: DataFrame with sell column
+        :return: DataFrame with exit columns populated
         """
         dataframe.loc[
             (
@@ -371,5 +386,18 @@ class SampleStrategy(IStrategy):
                 (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard: tema is falling
                 (dataframe['volume'] > 0)  # Make sure Volume is not 0
             ),
-            'sell'] = 1
+
+            'exit_long'] = 1
+
+        dataframe.loc[
+            (
+                # Signal: RSI crosses above 30
+                (qtpylib.crossed_above(dataframe['rsi'], self.exit_short_rsi.value)) &
+                # Guard: tema below BB middle
+                (dataframe['tema'] <= dataframe['bb_middleband']) &
+                (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard: tema is raising
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            'exit_short'] = 1
+
         return dataframe
diff --git a/freqtrade/templates/strategy_analysis_example.ipynb b/freqtrade/templates/strategy_analysis_example.ipynb
index 99720ae6e..93e4b83ae 100644
--- a/freqtrade/templates/strategy_analysis_example.ipynb
+++ b/freqtrade/templates/strategy_analysis_example.ipynb
@@ -79,7 +79,9 @@
    "source": [
     "# Load strategy using values set above\n",
     "from freqtrade.resolvers import StrategyResolver\n",
+    "from freqtrade.data.dataprovider import DataProvider\n",
     "strategy = StrategyResolver.load_strategy(config)\n",
+    "strategy.dp = DataProvider(config, None, None)\n",
     "\n",
     "# Generate buy/sell signals using strategy\n",
     "df = strategy.analyze_ticker(candles, {'pair': pair})\n",
@@ -108,7 +110,7 @@
    "outputs": [],
    "source": [
     "# Report results\n",
-    "print(f\"Generated {df['buy'].sum()} buy signals\")\n",
+    "print(f\"Generated {df['enter_long'].sum()} entry signals\")\n",
     "data = df.set_index('date', drop=False)\n",
     "data.tail()"
    ]
@@ -185,7 +187,7 @@
     "trades = load_backtest_data(backtest_dir)\n",
     "\n",
     "# Show value-counts per pair\n",
-    "trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
+    "trades.groupby(\"pair\")[\"exit_reason\"].value_counts()"
    ]
   },
   {
@@ -255,7 +257,7 @@
     "trades = load_trades_from_db(\"sqlite:///tradesv3.sqlite\")\n",
     "\n",
     "# Display results\n",
-    "trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
+    "trades.groupby(\"pair\")[\"exit_reason\"].value_counts()"
    ]
   },
   {
@@ -346,7 +348,7 @@
     "hist_data = [trades.profit_ratio]\n",
     "group_labels = ['profit_ratio']  # name of the dataset\n",
     "\n",
-    "fig = ff.create_distplot(hist_data, group_labels,bin_size=0.01)\n",
+    "fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)\n",
     "fig.show()\n"
    ]
   },
diff --git a/freqtrade/templates/subtemplates/buy_trend_full.j2 b/freqtrade/templates/subtemplates/buy_trend_full.j2
index 1a0d326b3..aac8325a7 100644
--- a/freqtrade/templates/subtemplates/buy_trend_full.j2
+++ b/freqtrade/templates/subtemplates/buy_trend_full.j2
@@ -1,3 +1,3 @@
-(qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+(qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) &  # Signal: RSI crosses above buy_rsi
 (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard: tema below BB middle
 (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard: tema is raising
diff --git a/freqtrade/templates/subtemplates/buy_trend_minimal.j2 b/freqtrade/templates/subtemplates/buy_trend_minimal.j2
index 6a4079cf3..e89d3779e 100644
--- a/freqtrade/templates/subtemplates/buy_trend_minimal.j2
+++ b/freqtrade/templates/subtemplates/buy_trend_minimal.j2
@@ -1 +1 @@
-(qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+(qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) &  # Signal: RSI crosses above buy_rsi
diff --git a/freqtrade/templates/subtemplates/exchange_binance.j2 b/freqtrade/templates/subtemplates/exchange_binance.j2
index de58b6f72..dc2272119 100644
--- a/freqtrade/templates/subtemplates/exchange_binance.j2
+++ b/freqtrade/templates/subtemplates/exchange_binance.j2
@@ -2,11 +2,8 @@
     "name": "{{ exchange_name | lower }}",
     "key": "{{ exchange_key }}",
     "secret": "{{ exchange_secret }}",
-    "ccxt_config": {"enableRateLimit": true},
-    "ccxt_async_config": {
-        "enableRateLimit": true,
-        "rateLimit": 200
-    },
+    "ccxt_config": {},
+    "ccxt_async_config": {},
     "pair_whitelist": [
     ],
     "pair_blacklist": [
diff --git a/freqtrade/templates/subtemplates/exchange_bittrex.j2 b/freqtrade/templates/subtemplates/exchange_bittrex.j2
index 0394790ce..023862314 100644
--- a/freqtrade/templates/subtemplates/exchange_bittrex.j2
+++ b/freqtrade/templates/subtemplates/exchange_bittrex.j2
@@ -1,7 +1,7 @@
 "order_types": {
-    "buy": "limit",
-    "sell": "limit",
-    "emergencysell": "limit",
+    "entry": "limit",
+    "exit": "limit",
+    "emergency_exit": "limit",
     "stoploss": "limit",
     "stoploss_on_exchange": false
 },
diff --git a/freqtrade/templates/subtemplates/exchange_generic.j2 b/freqtrade/templates/subtemplates/exchange_generic.j2
index ade9c2f28..08b11f365 100644
--- a/freqtrade/templates/subtemplates/exchange_generic.j2
+++ b/freqtrade/templates/subtemplates/exchange_generic.j2
@@ -2,10 +2,8 @@
     "name": "{{ exchange_name | lower }}",
     "key": "{{ exchange_key }}",
     "secret": "{{ exchange_secret }}",
-    "ccxt_config": {"enableRateLimit": true},
-    "ccxt_async_config": {
-        "enableRateLimit": true
-    },
+    "ccxt_config": {},
+    "ccxt_async_config": {},
     "pair_whitelist": [
 
     ],
diff --git a/freqtrade/templates/subtemplates/exchange_huobi.j2 b/freqtrade/templates/subtemplates/exchange_huobi.j2
new file mode 100644
index 000000000..3cb521785
--- /dev/null
+++ b/freqtrade/templates/subtemplates/exchange_huobi.j2
@@ -0,0 +1,12 @@
+"exchange": {
+    "name": "{{ exchange_name | lower }}",
+    "key": "{{ exchange_key }}",
+    "secret": "{{ exchange_secret }}",
+    "ccxt_config": {},
+    "ccxt_async_config": {},
+    "pair_whitelist": [
+    ],
+    "pair_blacklist": [
+        "HT/.*"
+    ]
+}
diff --git a/freqtrade/templates/subtemplates/exchange_kucoin.j2 b/freqtrade/templates/subtemplates/exchange_kucoin.j2
index f9dfff663..b797dda41 100644
--- a/freqtrade/templates/subtemplates/exchange_kucoin.j2
+++ b/freqtrade/templates/subtemplates/exchange_kucoin.j2
@@ -3,14 +3,8 @@
     "key": "{{ exchange_key }}",
     "secret": "{{ exchange_secret }}",
     "password": "{{ exchange_key_password }}",
-    "ccxt_config": {
-        "enableRateLimit": true
-        "rateLimit": 200
-    },
-    "ccxt_async_config": {
-        "enableRateLimit": true,
-        "rateLimit": 200
-    },
+    "ccxt_config": {},
+    "ccxt_async_config": {},
     "pair_whitelist": [
     ],
     "pair_blacklist": [
diff --git a/freqtrade/templates/subtemplates/exchange_okex.j2 b/freqtrade/templates/subtemplates/exchange_okex.j2
new file mode 100644
index 000000000..b797dda41
--- /dev/null
+++ b/freqtrade/templates/subtemplates/exchange_okex.j2
@@ -0,0 +1,12 @@
+"exchange": {
+    "name": "{{ exchange_name | lower }}",
+    "key": "{{ exchange_key }}",
+    "secret": "{{ exchange_secret }}",
+    "password": "{{ exchange_key_password }}",
+    "ccxt_config": {},
+    "ccxt_async_config": {},
+    "pair_whitelist": [
+    ],
+    "pair_blacklist": [
+    ]
+}
diff --git a/freqtrade/templates/subtemplates/plot_config_full.j2 b/freqtrade/templates/subtemplates/plot_config_full.j2
index ab02c7892..e3f9e7ca0 100644
--- a/freqtrade/templates/subtemplates/plot_config_full.j2
+++ b/freqtrade/templates/subtemplates/plot_config_full.j2
@@ -1,18 +1,20 @@
 
-plot_config = {
-    # Main plot indicators (Moving averages, ...)
-    'main_plot': {
-        'tema': {},
-        'sar': {'color': 'white'},
-    },
-    'subplots': {
-        # Subplots - each dict defines one additional plot
-        "MACD": {
-            'macd': {'color': 'blue'},
-            'macdsignal': {'color': 'orange'},
+@property
+def plot_config(self):
+    return {
+        # Main plot indicators (Moving averages, ...)
+        'main_plot': {
+            'tema': {},
+            'sar': {'color': 'white'},
         },
-        "RSI": {
-            'rsi': {'color': 'red'},
+        'subplots': {
+            # Subplots - each dict defines one additional plot
+            "MACD": {
+                'macd': {'color': 'blue'},
+                'macdsignal': {'color': 'orange'},
+            },
+            "RSI": {
+                'rsi': {'color': 'red'},
+            }
         }
     }
-}
diff --git a/freqtrade/templates/subtemplates/sell_trend_full.j2 b/freqtrade/templates/subtemplates/sell_trend_full.j2
index 36c08c947..3068d8d57 100644
--- a/freqtrade/templates/subtemplates/sell_trend_full.j2
+++ b/freqtrade/templates/subtemplates/sell_trend_full.j2
@@ -1,3 +1,3 @@
-(qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+(qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) &  # Signal: RSI crosses above sell_rsi
 (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard: tema above BB middle
 (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard: tema is falling
diff --git a/freqtrade/templates/subtemplates/sell_trend_minimal.j2 b/freqtrade/templates/subtemplates/sell_trend_minimal.j2
index 42a7b81a2..5dabc5910 100644
--- a/freqtrade/templates/subtemplates/sell_trend_minimal.j2
+++ b/freqtrade/templates/subtemplates/sell_trend_minimal.j2
@@ -1 +1 @@
-(qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+(qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) &  # Signal: RSI crosses above sell_rsi
diff --git a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2 b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
index 2df23f365..d5e2ea8ce 100644
--- a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
+++ b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
@@ -12,19 +12,58 @@ def bot_loop_start(self, **kwargs) -> None:
     """
     pass
 
-def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate: float,
-                        proposed_stake: float, min_stake: float, max_stake: float,
-                        **kwargs) -> float:
+def custom_entry_price(self, pair: str, current_time: 'datetime', proposed_rate: float,
+                       entry_tag: 'Optional[str]', **kwargs) -> float:
     """
-    Customize stake size for each new trade. This method is not called when edge module is
-    enabled.
+    Custom entry price logic, returning the new entry price.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, returns None, orderbook is used to set entry price
 
     :param pair: Pair that's currently analyzed
     :param current_time: datetime object, containing the current datetime
-    :param current_rate: Rate, calculated based on pricing settings in ask_strategy.
+    :param proposed_rate: Rate, calculated based on pricing settings in exit_pricing.
+    :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return float: New entry price value if provided
+    """
+    return proposed_rate
+
+def custom_exit_price(self, pair: str, trade: 'Trade',
+                      current_time: 'datetime', proposed_rate: float,
+                      current_profit: float, **kwargs) -> float:
+    """
+    Custom exit price logic, returning the new exit price.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, returns None, orderbook is used to set exit price
+
+    :param pair: Pair that's currently analyzed
+    :param trade: trade object.
+    :param current_time: datetime object, containing the current datetime
+    :param proposed_rate: Rate, calculated based on pricing settings in exit_pricing.
+    :param current_profit: Current profit (as ratio), calculated based on current_rate.
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return float: New exit price value if provided
+    """
+    return proposed_rate
+
+def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate: float,
+                        proposed_stake: float, min_stake: float, max_stake: float,
+                        side: str, entry_tag: 'Optional[str]', **kwargs) -> float:
+    """
+    Customize stake size for each new trade.
+
+    :param pair: Pair that's currently analyzed
+    :param current_time: datetime object, containing the current datetime
+    :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
     :param proposed_stake: A stake amount proposed by the bot.
     :param min_stake: Minimal stake size allowed by exchange.
     :param max_stake: Balance available for trading.
+    :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
+    :param side: 'long' or 'short' - indicating the direction of the proposed trade
     :return: A stake size, which is between min_stake and max_stake.
     """
     return proposed_stake
@@ -32,8 +71,7 @@ def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate:
 use_custom_stoploss = True
 
 def custom_stoploss(self, pair: str, trade: 'Trade', current_time: 'datetime',
-                    current_rate: float, current_profit: float, dataframe: DataFrame,
-                    **kwargs) -> float:
+                    current_rate: float, current_profit: float, **kwargs) -> float:
     """
     Custom stoploss logic, returning the new distance relative to current_rate (as ratio).
     e.g. returning -0.05 would create a stoploss 5% below current_rate.
@@ -44,21 +82,20 @@ def custom_stoploss(self, pair: str, trade: 'Trade', current_time: 'datetime',
     When not implemented by a strategy, returns the initial stoploss value
     Only called when use_custom_stoploss is set to True.
 
-    :param pair: Pair that's about to be sold.
+    :param pair: Pair that's currently analyzed
     :param trade: trade object.
     :param current_time: datetime object, containing the current datetime
-    :param current_rate: Rate, calculated based on pricing settings in ask_strategy.
+    :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
     :param current_profit: Current profit (as ratio), calculated based on current_rate.
-    :param dataframe: Analyzed dataframe for this pair. Can contain future data in backtesting.
     :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-    :return float: New stoploss value, relative to the currentrate
+    :return float: New stoploss value, relative to the current_rate
     """
     return self.stoploss
 
-def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
+def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
                 current_profit: float, **kwargs) -> 'Optional[Union[str, bool]]':
     """
-    Custom sell signal logic indicating that specified position should be sold. Returning a
+    Custom exit signal logic indicating that specified position should be sold. Returning a
     string or True from this method is equal to setting sell signal on a candle at specified
     time. This method is not called when sell signal is set.
 
@@ -66,23 +103,24 @@ def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', curre
     example you could implement a sell relative to the candle when the trade was opened,
     or a custom 1:2 risk-reward ROI.
 
-    Custom sell reason max length is 64. Exceeding characters will be removed.
+    Custom exit reason max length is 64. Exceeding characters will be removed.
 
     :param pair: Pair that's currently analyzed
     :param trade: trade object.
     :param current_time: datetime object, containing the current datetime
-    :param current_rate: Rate, calculated based on pricing settings in ask_strategy.
+    :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
     :param current_profit: Current profit (as ratio), calculated based on current_rate.
     :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-    :return: To execute sell, return a string with custom sell reason or True. Otherwise return
+    :return: To execute sell, return a string with custom exit reason or True. Otherwise return
     None or False.
     """
     return None
 
 def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
-                        time_in_force: str, current_time: 'datetime', **kwargs) -> bool:
+                        time_in_force: str, current_time: datetime, entry_tag: 'Optional[str]',
+                        side: str, **kwargs) -> bool:
     """
-    Called right before placing a buy order.
+    Called right before placing a entry order.
     Timing for this function is critical, so avoid doing heavy computations or
     network requests in this method.
 
@@ -90,12 +128,14 @@ def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: f
 
     When not implemented by a strategy, returns True (always confirming).
 
-    :param pair: Pair that's about to be bought.
+    :param pair: Pair that's about to be bought/shorted.
     :param order_type: Order type (as configured in order_types). usually limit or market.
     :param amount: Amount in target (quote) currency that's going to be traded.
     :param rate: Rate that's going to be used when using limit orders
     :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
     :param current_time: datetime object, containing the current datetime
+    :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
+    :param side: 'long' or 'short' - indicating the direction of the proposed trade
     :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
     :return bool: When True is returned, then the buy-order is placed on the exchange.
         False aborts the process
@@ -103,7 +143,7 @@ def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: f
     return True
 
 def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount: float,
-                       rate: float, time_in_force: str, sell_reason: str,
+                       rate: float, time_in_force: str, exit_reason: str,
                        current_time: 'datetime', **kwargs) -> bool:
     """
     Called right before placing a regular sell order.
@@ -120,21 +160,22 @@ def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount:
     :param amount: Amount in quote currency.
     :param rate: Rate that's going to be used when using limit orders
     :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
-    :param sell_reason: Sell reason.
+    :param exit_reason: Exit reason.
         Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
-                        'sell_signal', 'force_sell', 'emergency_sell']
+                        'exit_signal', 'force_exit', 'emergency_exit']
     :param current_time: datetime object, containing the current datetime
     :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-    :return bool: When True is returned, then the sell-order is placed on the exchange.
+    :return bool: When True is returned, then the exit-order is placed on the exchange.
         False aborts the process
     """
     return True
 
-def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
+def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order',
+                        current_time: datetime, **kwargs) -> bool:
     """
-    Check buy timeout function callback.
-    This method can be used to override the buy-timeout.
-    It is called whenever a limit buy order has been created,
+    Check entry timeout function callback.
+    This method can be used to override the entry-timeout.
+    It is called whenever a limit entry order has been created,
     and is not yet fully filled.
     Configuration options in `unfilledtimeout` will be verified before this,
     so ensure to set these timeouts high enough.
@@ -143,18 +184,20 @@ def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) ->
 
     When not implemented by a strategy, this simply returns False.
     :param pair: Pair the trade is for
-    :param trade: trade object.
-    :param order: Order dictionary as returned from CCXT.
+    :param trade: Trade object.
+    :param order: Order object.
+    :param current_time: datetime object, containing the current datetime
     :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-    :return bool: When True is returned, then the buy-order is cancelled.
+    :return bool: When True is returned, then the entry order is cancelled.
     """
     return False
 
-def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
+def check_exit_timeout(self, pair: str, trade: 'Trade', order: 'Order',
+                       current_time: datetime, **kwargs) -> bool:
     """
-    Check sell timeout function callback.
-    This method can be used to override the sell-timeout.
-    It is called whenever a limit sell order has been created,
+    Check exit timeout function callback.
+    This method can be used to override the exit-timeout.
+    It is called whenever a limit exit order has been created,
     and is not yet fully filled.
     Configuration options in `unfilledtimeout` will be verified before this,
     so ensure to set these timeouts high enough.
@@ -163,9 +206,49 @@ def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -
 
     When not implemented by a strategy, this simply returns False.
     :param pair: Pair the trade is for
-    :param trade: trade object.
-    :param order: Order dictionary as returned from CCXT.
+    :param trade: Trade object.
+    :param order: Order object.
+    :param current_time: datetime object, containing the current datetime
     :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
-    :return bool: When True is returned, then the sell-order is cancelled.
+    :return bool: When True is returned, then the exit-order is cancelled.
     """
     return False
+
+def adjust_trade_position(self, trade: 'Trade', current_time: 'datetime',
+                          current_rate: float, current_profit: float, min_stake: float,
+                          max_stake: float, **kwargs) -> 'Optional[float]':
+    """
+    Custom trade adjustment logic, returning the stake amount that a trade should be increased.
+    This means extra buy orders with additional fees.
+    Only called when `position_adjustment_enable` is set to True.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, returns None
+
+    :param trade: trade object.
+    :param current_time: datetime object, containing the current datetime
+    :param current_rate: Current buy rate.
+    :param current_profit: Current profit (as ratio), calculated based on current_rate.
+    :param min_stake: Minimal stake size allowed by exchange.
+    :param max_stake: Balance available for trading.
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return float: Stake amount to adjust your trade
+    """
+    return None
+
+def leverage(self, pair: str, current_time: datetime, current_rate: float,
+                proposed_leverage: float, max_leverage: float, side: str,
+                **kwargs) -> float:
+    """
+    Customize leverage for each new trade. This method is only called in futures mode.
+
+    :param pair: Pair that's currently analyzed
+    :param current_time: datetime object, containing the current datetime
+    :param current_rate: Rate, calculated based on pricing settings in exit_pricing.
+    :param proposed_leverage: A leverage proposed by the bot.
+    :param max_leverage: Max leverage allowed on this pair
+    :param side: 'long' or 'short' - indicating the direction of the proposed trade
+    :return: A leverage amount, which is between 1.0 and max_leverage.
+    """
+    return 1.0
diff --git a/freqtrade/vendor/qtpylib/indicators.py b/freqtrade/vendor/qtpylib/indicators.py
index 4c0fb5b5c..4f14ae13c 100644
--- a/freqtrade/vendor/qtpylib/indicators.py
+++ b/freqtrade/vendor/qtpylib/indicators.py
@@ -339,11 +339,13 @@ def vwap(bars):
     (input can be pandas series or numpy array)
     bars are usually mid [ (h+l)/2 ] or typical [ (h+l+c)/3 ]
     """
-    typical = ((bars['high'] + bars['low'] + bars['close']) / 3).values
-    volume = bars['volume'].values
+    raise ValueError("using `qtpylib.vwap` facilitates lookahead bias. Please use "
+                     "`qtpylib.rolling_vwap` instead, which calculates vwap in a rolling manner.")
+    # typical = ((bars['high'] + bars['low'] + bars['close']) / 3).values
+    # volume = bars['volume'].values
 
-    return pd.Series(index=bars.index,
-                     data=np.cumsum(volume * typical) / np.cumsum(volume))
+    # return pd.Series(index=bars.index,
+    #                  data=np.cumsum(volume * typical) / np.cumsum(volume))
 
 
 # ---------------------------------------------
diff --git a/freqtrade/wallets.py b/freqtrade/wallets.py
index 237c1dc2c..d93689a0e 100644
--- a/freqtrade/wallets.py
+++ b/freqtrade/wallets.py
@@ -3,12 +3,12 @@
 
 import logging
 from copy import deepcopy
-from typing import Any, Dict, NamedTuple
+from typing import Dict, NamedTuple, Optional
 
 import arrow
 
 from freqtrade.constants import UNLIMITED_STAKE_AMOUNT
-from freqtrade.enums import RunMode
+from freqtrade.enums import RunMode, TradingMode
 from freqtrade.exceptions import DependencyException
 from freqtrade.exchange import Exchange
 from freqtrade.persistence import LocalTrade, Trade
@@ -25,6 +25,14 @@ class Wallet(NamedTuple):
     total: float = 0
 
 
+class PositionWallet(NamedTuple):
+    symbol: str
+    position: float = 0
+    leverage: float = 0
+    collateral: float = 0
+    side: str = 'long'
+
+
 class Wallets:
 
     def __init__(self, config: dict, exchange: Exchange, log: bool = True) -> None:
@@ -32,6 +40,7 @@ class Wallets:
         self._log = log
         self._exchange = exchange
         self._wallets: Dict[str, Wallet] = {}
+        self._positions: Dict[str, PositionWallet] = {}
         self.start_cap = config['dry_run_wallet']
         self._last_wallet_refresh = 0
         self.update()
@@ -66,6 +75,7 @@ class Wallets:
         """
         # Recreate _wallets to reset closed trade balances
         _wallets = {}
+        _positions = {}
         open_trades = Trade.get_trades_proxy(is_open=True)
         # If not backtesting...
         # TODO: potentially remove the ._log workaround to determine backtest mode.
@@ -73,25 +83,46 @@ class Wallets:
             tot_profit = Trade.get_total_closed_profit()
         else:
             tot_profit = LocalTrade.total_profit
-        tot_in_trades = sum([trade.stake_amount for trade in open_trades])
+        tot_in_trades = sum(trade.stake_amount for trade in open_trades)
+        used_stake = 0.0
+
+        if self._config.get('trading_mode', 'spot') != TradingMode.FUTURES:
+            current_stake = self.start_cap + tot_profit - tot_in_trades
+            total_stake = current_stake
+            for trade in open_trades:
+                curr = self._exchange.get_pair_base_currency(trade.pair)
+                _wallets[curr] = Wallet(
+                    curr,
+                    trade.amount,
+                    0,
+                    trade.amount
+                )
+        else:
+            tot_in_trades = 0
+            for position in open_trades:
+                # size = self._exchange._contracts_to_amount(position.pair, position['contracts'])
+                size = position.amount
+                collateral = position.stake_amount
+                leverage = position.leverage
+                tot_in_trades += collateral
+                _positions[position.pair] = PositionWallet(
+                    position.pair, position=size,
+                    leverage=leverage,
+                    collateral=collateral,
+                    side=position.trade_direction
+                )
+            current_stake = self.start_cap + tot_profit - tot_in_trades
+            used_stake = tot_in_trades
+            total_stake = current_stake + tot_in_trades
 
-        current_stake = self.start_cap + tot_profit - tot_in_trades
         _wallets[self._config['stake_currency']] = Wallet(
-            self._config['stake_currency'],
-            current_stake,
-            0,
-            current_stake
+            currency=self._config['stake_currency'],
+            free=current_stake,
+            used=used_stake,
+            total=total_stake
         )
-
-        for trade in open_trades:
-            curr = self._exchange.get_pair_base_currency(trade.pair)
-            _wallets[curr] = Wallet(
-                curr,
-                trade.amount,
-                0,
-                trade.amount
-            )
         self._wallets = _wallets
+        self._positions = _positions
 
     def _update_live(self) -> None:
         balances = self._exchange.get_balances()
@@ -109,6 +140,23 @@ class Wallets:
             if currency not in balances:
                 del self._wallets[currency]
 
+        positions = self._exchange.fetch_positions()
+        self._positions = {}
+        for position in positions:
+            symbol = position['symbol']
+            if position['side'] is None or position['collateral'] == 0.0:
+                # Position is not open ...
+                continue
+            size = self._exchange._contracts_to_amount(symbol, position['contracts'])
+            collateral = position['collateral']
+            leverage = position['leverage']
+            self._positions[symbol] = PositionWallet(
+                symbol, position=size,
+                leverage=leverage,
+                collateral=collateral,
+                side=position['side']
+            )
+
     def update(self, require_update: bool = True) -> None:
         """
         Updates wallets from the configured version.
@@ -126,9 +174,12 @@ class Wallets:
                 logger.info('Wallets synced.')
             self._last_wallet_refresh = arrow.utcnow().int_timestamp
 
-    def get_all_balances(self) -> Dict[str, Any]:
+    def get_all_balances(self) -> Dict[str, Wallet]:
         return self._wallets
 
+    def get_all_positions(self) -> Dict[str, PositionWallet]:
+        return self._positions
+
     def get_starting_balance(self) -> float:
         """
         Retrieves starting balance - based on either available capital,
@@ -211,7 +262,7 @@ class Wallets:
 
         return stake_amount
 
-    def get_trade_stake_amount(self, pair: str, edge=None) -> float:
+    def get_trade_stake_amount(self, pair: str, edge=None, update: bool = True) -> float:
         """
         Calculate stake amount for the trade
         :return: float: Stake amount
@@ -219,7 +270,8 @@ class Wallets:
         """
         stake_amount: float
         # Ensure wallets are uptodate.
-        self.update()
+        if update:
+            self.update()
         val_tied_up = Trade.total_open_trades_stakes()
         available_amount = self.get_available_stake_amount()
 
@@ -238,29 +290,40 @@ class Wallets:
 
         return self._check_available_stake_amount(stake_amount, available_amount)
 
-    def _validate_stake_amount(self, pair, stake_amount, min_stake_amount):
+    def validate_stake_amount(self, pair: str, stake_amount: Optional[float],
+                              min_stake_amount: Optional[float], max_stake_amount: float):
         if not stake_amount:
             logger.debug(f"Stake amount is {stake_amount}, ignoring possible trade for {pair}.")
             return 0
 
-        max_stake_amount = self.get_available_stake_amount()
+        max_stake_amount = min(max_stake_amount, self.get_available_stake_amount())
 
-        if min_stake_amount > max_stake_amount:
+        if min_stake_amount is not None and min_stake_amount > max_stake_amount:
             if self._log:
                 logger.warning("Minimum stake amount > available balance.")
             return 0
         if min_stake_amount is not None and stake_amount < min_stake_amount:
-            stake_amount = min_stake_amount
             if self._log:
                 logger.info(
                     f"Stake amount for pair {pair} is too small "
                     f"({stake_amount} < {min_stake_amount}), adjusting to {min_stake_amount}."
                 )
+            if stake_amount * 1.3 < min_stake_amount:
+                # Top-cap stake-amount adjustments to +30%.
+                if self._log:
+                    logger.info(
+                        f"Adjusted stake amount for pair {pair} is more than 30% bigger than "
+                        f"the desired stake amount of ({stake_amount:.8f} * 1.3 = "
+                        f"{stake_amount * 1.3:.8f}) < {min_stake_amount}), ignoring trade."
+                    )
+                return 0
+            stake_amount = min_stake_amount
+
         if stake_amount > max_stake_amount:
-            stake_amount = max_stake_amount
             if self._log:
                 logger.info(
                     f"Stake amount for pair {pair} is too big "
                     f"({stake_amount} > {max_stake_amount}), adjusting to {max_stake_amount}."
                 )
+            stake_amount = max_stake_amount
         return stake_amount
diff --git a/freqtrade/worker.py b/freqtrade/worker.py
index 5c0de86ff..66f718af0 100755
--- a/freqtrade/worker.py
+++ b/freqtrade/worker.py
@@ -85,9 +85,12 @@ class Worker:
 
         # Log state transition
         if state != old_state:
-            self.freqtrade.notify_status(f'{state.name.lower()}')
 
-            logger.info(f"Changing state to: {state.name}")
+            if old_state != State.RELOAD_CONFIG:
+                self.freqtrade.notify_status(f'{state.name.lower()}')
+
+            logger.info(
+                f"Changing state{f' from {old_state.name}' if old_state else ''} to: {state.name}")
             if state == State.RUNNING:
                 self.freqtrade.startup()
 
@@ -113,8 +116,12 @@ class Worker:
         if self._heartbeat_interval:
             now = time.time()
             if (now - self._heartbeat_msg) > self._heartbeat_interval:
+                version = __version__
+                strategy_version = self.freqtrade.strategy.version()
+                if (strategy_version is not None):
+                    version += ', strategy_version: ' + strategy_version
                 logger.info(f"Bot heartbeat. PID={getpid()}, "
-                            f"version='{__version__}', state='{state.name}'")
+                            f"version='{version}', state='{state.name}'")
                 self._heartbeat_msg = now
 
         return state
diff --git a/mkdocs.yml b/mkdocs.yml
index 05156168f..8b36ba699 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -11,8 +11,9 @@ nav:
     - Freqtrade Basics: bot-basics.md
     - Configuration: configuration.md
     - Strategy Customization: strategy-customization.md
-    - Plugins: plugins.md
+    - Strategy Callbacks: strategy-callbacks.md
     - Stoploss: stoploss.md
+    - Plugins: plugins.md
     - Start the bot: bot-usage.md
     - Control the bot:
         - Telegram: telegram-usage.md
@@ -21,6 +22,7 @@ nav:
     - Data Downloading: data-download.md
     - Backtesting: backtesting.md
     - Hyperopt: hyperopt.md
+    - Short / Leverage: leverage.md
     - Utility Sub-commands: utils.md
     - Plotting: plotting.md
     - Exchange-specific Notes: exchanges.md
@@ -35,29 +37,30 @@ nav:
         - Sandbox Testing: sandbox-testing.md
     - FAQ: faq.md
     - SQL Cheat-sheet: sql_cheatsheet.md
+    - Strategy migration: strategy_migration.md
     - Updating Freqtrade: updating.md
     - Deprecated Features: deprecated.md
     - Contributors Guide: developer.md
 theme:
   name: material
-  logo: 'images/logo.png'
-  favicon: 'images/logo.png'
-  custom_dir: 'docs/overrides'
+  logo: "images/logo.png"
+  favicon: "images/logo.png"
+  custom_dir: "docs/overrides"
   palette:
     - scheme: default
-      primary: 'blue grey'
-      accent: 'tear'
+      primary: "blue grey"
+      accent: "tear"
       toggle:
         icon: material/toggle-switch-off-outline
         name: Switch to dark mode
     - scheme: slate
-      primary: 'blue grey'
-      accent: 'tear'
+      primary: "blue grey"
+      accent: "tear"
       toggle:
-        icon: material/toggle-switch-off-outline
-        name: Switch to dark mode
+        icon: material/toggle-switch
+        name: Switch to light mode
 extra_css:
-  - 'stylesheets/ft.extra.css'
+  - "stylesheets/ft.extra.css"
 extra_javascript:
   - javascripts/config.js
   - https://polyfill.io/v3/polyfill.min.js?features=es6
@@ -80,8 +83,10 @@ markdown_extensions:
   - pymdownx.snippets:
       base_path: docs
       check_paths: true
-  - pymdownx.tabbed
   - pymdownx.superfences
+  - pymdownx.tabbed:
+      alternate_style: true
   - pymdownx.tasklist:
       custom_checkbox: true
+  - pymdownx.tilde
   - mdx_truly_sane_lists
diff --git a/pyproject.toml b/pyproject.toml
index f0637d8c6..50f0242a8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,6 +23,10 @@ exclude = '''
 line_length = 100
 multi_line_output=0
 lines_after_imports=2
+skip_glob = ["**/.env*", "**/env/*", "**/.venv/*", "**/docs/*"]
+
+[tool.pytest.ini_options]
+asyncio_mode = "auto"
 
 [build-system]
 requires = ["setuptools >= 46.4.0", "wheel"]
diff --git a/requirements-dev.txt b/requirements-dev.txt
index d8d8ce916..03bb5e72d 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -2,26 +2,30 @@
 -r requirements.txt
 -r requirements-plot.txt
 -r requirements-hyperopt.txt
+-r docs/requirements-docs.txt
 
-coveralls==3.2.0
-flake8==3.9.2
-flake8-type-annotations==0.1.0
-flake8-tidy-imports==4.4.1
-mypy==0.910
-pytest==6.2.5
-pytest-asyncio==0.15.1
-pytest-cov==2.12.1
-pytest-mock==3.6.1
+coveralls==3.3.1
+flake8==4.0.1
+flake8-tidy-imports==4.6.0
+mypy==0.942
+pre-commit==2.18.1
+pytest==7.1.1
+pytest-asyncio==0.18.3
+pytest-cov==3.0.0
+pytest-mock==3.7.0
 pytest-random-order==1.0.4
-isort==5.9.3
+isort==5.10.1
 # For datetime mocking
-time-machine==2.4.0
+time-machine==2.6.0
 
 # Convert jupyter notebooks to markdown documents
-nbconvert==6.1.0
+nbconvert==6.4.5
 
 # mypy types
-types-cachetools==4.2.0
-types-filelock==0.1.5
-types-requests==2.25.8
-types-tabulate==0.8.2
+types-cachetools==5.0.0
+types-filelock==3.2.5
+types-requests==2.27.16
+types-tabulate==0.8.6
+
+# Extensions to datetime library
+types-python-dateutil==2.8.10
diff --git a/requirements-hyperopt.txt b/requirements-hyperopt.txt
index 9feec80f1..aeb7be035 100644
--- a/requirements-hyperopt.txt
+++ b/requirements-hyperopt.txt
@@ -2,10 +2,9 @@
 -r requirements.txt
 
 # Required for hyperopt
-scipy==1.7.1
-scikit-learn==0.24.2
-scikit-optimize==0.8.1
-filelock==3.0.12
-joblib==1.0.1
-psutil==5.8.0
-progressbar2==3.53.3
+scipy==1.8.0
+scikit-learn==1.0.2
+scikit-optimize==0.9.0
+filelock==3.6.0
+joblib==1.1.0
+progressbar2==4.0.0
diff --git a/requirements-plot.txt b/requirements-plot.txt
index 8e17232b0..9eb6a10a3 100644
--- a/requirements-plot.txt
+++ b/requirements-plot.txt
@@ -1,5 +1,5 @@
 # Include all requirements to run the bot.
 -r requirements.txt
 
-plotly==5.3.1
+plotly==5.7.0
 
diff --git a/requirements.txt b/requirements.txt
index d1d10dd1d..3f2d1b351 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,44 +1,49 @@
-numpy==1.21.2
-pandas==1.3.3
+numpy==1.22.3
+pandas==1.4.2
 pandas-ta==0.3.14b
 
-ccxt==1.56.86
+ccxt==1.78.62
 # Pin cryptography for now due to rust build errors with piwheels
-cryptography==3.4.8
-aiohttp==3.7.4.post0
-SQLAlchemy==1.4.25
-python-telegram-bot==13.7
-arrow==1.1.1
+cryptography==36.0.2
+aiohttp==3.8.1
+SQLAlchemy==1.4.35
+python-telegram-bot==13.11
+arrow==1.2.2
 cachetools==4.2.2
-requests==2.26.0
-urllib3==1.26.7
-wrapt==1.12.1
-jsonschema==3.2.0
-TA-Lib==0.4.21
+requests==2.27.1
+urllib3==1.26.9
+jsonschema==4.4.0
+TA-Lib==0.4.24
 technical==1.3.0
 tabulate==0.8.9
 pycoingecko==2.2.0
-jinja2==3.0.1
-tables==3.6.1
-blosc==1.10.4
+jinja2==3.1.1
+tables==3.7.0
+blosc==1.10.6
 
 # find first, C search in arrays
 py_find_1st==1.1.5
 
 # Load ticker files 30% faster
-python-rapidjson==1.4
+python-rapidjson==1.6
 
 # Notify systemd
 sdnotify==0.3.2
 
 # API Server
-fastapi==0.68.1
-uvicorn==0.15.0
-pyjwt==2.1.0
-aiofiles==0.7.0
+fastapi==0.75.1
+uvicorn==0.17.6
+pyjwt==2.3.0
+aiofiles==0.8.0
+psutil==5.9.0
 
 # Support for colorized terminal output
 colorama==0.4.4
 # Building config files interactively
 questionary==1.10.0
-prompt-toolkit==3.0.20
+prompt-toolkit==3.0.29
+# Extensions to datetime library
+python-dateutil==2.8.2
+
+#Futures
+schedule==1.1.0
diff --git a/scripts/rest_client.py b/scripts/rest_client.py
index ece0a253e..ecbb65253 100755
--- a/scripts/rest_client.py
+++ b/scripts/rest_client.py
@@ -39,7 +39,7 @@ class FtRestClient():
     def _call(self, method, apipath, params: dict = None, data=None, files=None):
 
         if str(method).upper() not in ('GET', 'POST', 'PUT', 'DELETE'):
-            raise ValueError('invalid method <{0}>'.format(method))
+            raise ValueError(f'invalid method <{method}>')
         basepath = f"{self._serverurl}/api/v1/{apipath}"
 
         hd = {"Accept": "application/json",
@@ -124,7 +124,7 @@ class FtRestClient():
         :param lock_id: ID for the lock to delete
         :return: json object
         """
-        return self._delete("locks/{}".format(lock_id))
+        return self._delete(f"locks/{lock_id}")
 
     def daily(self, days=None):
         """Return the profits for each day, and amount of trades.
@@ -220,7 +220,7 @@ class FtRestClient():
         :param trade_id: Specify which trade to get.
         :return: json object
         """
-        return self._get("trade/{}".format(trade_id))
+        return self._get(f"trade/{trade_id}")
 
     def delete_trade(self, trade_id):
         """Delete trade from the database.
@@ -229,7 +229,7 @@ class FtRestClient():
         :param trade_id: Deletes the trade with this ID from the database.
         :return: json object
         """
-        return self._delete("trades/{}".format(trade_id))
+        return self._delete(f"trades/{trade_id}")
 
     def whitelist(self):
         """Show the current whitelist.
@@ -261,14 +261,28 @@ class FtRestClient():
                 }
         return self._post("forcebuy", data=data)
 
-    def forcesell(self, tradeid):
-        """Force-sell a trade.
+    def force_enter(self, pair, side, price=None):
+        """Force entering a trade
+
+        :param pair: Pair to buy (ETH/BTC)
+        :param side: 'long' or 'short'
+        :param price: Optional - price to buy
+        :return: json object of the trade
+        """
+        data = {"pair": pair,
+                "side": side,
+                "price": price,
+                }
+        return self._post("force_enter", data=data)
+
+    def forceexit(self, tradeid):
+        """Force-exit a trade.
 
         :param tradeid: Id of the trade (can be received via status command)
         :return: json object
         """
 
-        return self._post("forcesell", data={"tradeid": tradeid})
+        return self._post("forceexit", data={"tradeid": tradeid})
 
     def strategies(self):
         """Lists available strategies
@@ -312,7 +326,7 @@ class FtRestClient():
         :param limit: Limit result to the last n candles.
         :return: json object
         """
-        return self._get("available_pairs", params={
+        return self._get("pair_candles", params={
             "pair": pair,
             "timeframe": timeframe,
             "limit": limit,
@@ -334,6 +348,13 @@ class FtRestClient():
             "timerange": timerange if timerange else '',
         })
 
+    def sysinfo(self):
+        """Provides system information (CPU, RAM usage)
+
+        :return: json object
+        """
+        return self._get("sysinfo")
+
 
 def add_arguments():
     parser = argparse.ArgumentParser()
diff --git a/setup.cfg b/setup.cfg
index b311c94da..f4a90bda7 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -14,9 +14,9 @@ classifiers =
     Environment :: Console
     Intended Audience :: Science/Research
     License :: OSI Approved :: GNU General Public License v3 (GPLv3)
-    Programming Language :: Python :: 3.7
     Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
+    Programming Language :: Python :: 3.10
     Operating System :: MacOS
     Operating System :: Unix
     Topic :: Office/Business :: Financial :: Investment
@@ -39,7 +39,9 @@ console_scripts =
     freqtrade = freqtrade.main:main
 
 [flake8]
-#ignore =
+# Default from https://flake8.pycqa.org/en/latest/user/options.html#cmdoption-flake8-ignore
+# minus E226
+ignore = E121,E123,E126,E24,E704,W503,W504
 max-line-length = 100
 max-complexity = 12
 exclude =
diff --git a/setup.py b/setup.py
index cf381bdd3..640c8cc7b 100644
--- a/setup.py
+++ b/setup.py
@@ -10,13 +10,11 @@ hyperopt = [
     'filelock',
     'joblib',
     'progressbar2',
-    'psutil',
-    ]
+]
 
 develop = [
     'coveralls',
     'flake8',
-    'flake8-type-annotations',
     'flake8-tidy-imports',
     'mypy',
     'pytest',
@@ -31,7 +29,7 @@ jupyter = [
     'nbstripout',
     'ipykernel',
     'nbconvert',
-    ]
+]
 
 all_extra = plot + develop + jupyter + hyperopt
 
@@ -41,17 +39,16 @@ setup(
         'pytest-asyncio',
         'pytest-cov',
         'pytest-mock',
-        ],
+    ],
     install_requires=[
         # from requirements.txt
-        'ccxt>=1.50.48',
+        'ccxt>=1.77.29',
         'SQLAlchemy',
         'python-telegram-bot>=13.4',
         'arrow>=0.17.0',
         'cachetools',
         'requests',
         'urllib3',
-        'wrapt',
         'jsonschema',
         'TA-Lib',
         'pandas-ta',
@@ -71,8 +68,10 @@ setup(
         'blosc',
         'fastapi',
         'uvicorn',
+        'psutil',
         'pyjwt',
-        'aiofiles'
+        'aiofiles',
+        'schedule'
     ],
     extras_require={
         'dev': all_extra,
diff --git a/setup.sh b/setup.sh
index aee7c80b5..5cde1a589 100755
--- a/setup.sh
+++ b/setup.sh
@@ -1,12 +1,16 @@
 #!/usr/bin/env bash
 #encoding=utf8
 
+function echo_block() {
+    echo "----------------------------"
+    echo $1
+    echo "----------------------------"
+}
+
 function check_installed_pip() {
    ${PYTHON} -m pip > /dev/null
    if [ $? -ne 0 ]; then
-        echo "-----------------------------"
-        echo "Installing Pip for ${PYTHON}"
-        echo "-----------------------------"
+        echo_block "Installing Pip for ${PYTHON}"
         curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
         ${PYTHON} get-pip.py
         rm get-pip.py
@@ -21,7 +25,7 @@ function check_installed_python() {
         exit 2
     fi
 
-    for v in 9 8 7
+    for v in 9 10 8
     do
         PYTHON="python3.${v}"
         which $PYTHON
@@ -30,16 +34,14 @@ function check_installed_python() {
             check_installed_pip
             return
         fi
-    done 
+    done
 
-    echo "No usable python found. Please make sure to have python3.7 or newer installed"
+    echo "No usable python found. Please make sure to have python3.8 or newer installed."
     exit 1
 }
 
 function updateenv() {
-    echo "-------------------------"
-    echo "Updating your virtual env"
-    echo "-------------------------"
+    echo_block "Updating your virtual env"
     if [ ! -f .env/bin/activate ]; then
         echo "Something went wrong, no virtual environment found."
         exit 1
@@ -49,6 +51,7 @@ function updateenv() {
     echo "pip install in-progress. Please wait..."
     ${PYTHON} -m pip install --upgrade pip
     read -p "Do you want to install dependencies for dev [y/N]? "
+    dev=$REPLY
     if [[ $REPLY =~ ^[Yy]$ ]]
     then
         REQUIREMENTS=requirements-dev.txt
@@ -86,6 +89,13 @@ function updateenv() {
     fi
     echo "pip install completed"
     echo
+    if [[ $dev =~ ^[Yy]$ ]]; then
+        ${PYTHON} -m pre-commit install
+        if [ $? -ne 0 ]; then
+            echo "Failed installing pre-commit"
+            exit 1
+        fi
+    fi
 }
 
 # Install tab lib
@@ -95,27 +105,31 @@ function install_talib() {
         return
     fi
 
-    cd build_helpers && ./install_ta-lib.sh && cd ..
+    cd build_helpers && ./install_ta-lib.sh
+
+    if [ $? -ne 0 ]; then
+        echo "Quitting. Please fix the above error before continuing."
+        cd ..
+        exit 1
+    fi;
+
+    cd ..
 }
 
-function install_mac_newer_python_dependencies() {    
-    
+function install_mac_newer_python_dependencies() {
+
     if [ ! $(brew --prefix --installed hdf5 2>/dev/null) ]
     then
-        echo "-------------------------"
-        echo "Installing hdf5"
-        echo "-------------------------"
+        echo_block "Installing hdf5"
         brew install hdf5
     fi
     export HDF5_DIR=$(brew --prefix)
 
     if [ ! $(brew --prefix --installed c-blosc 2>/dev/null) ]
     then
-        echo "-------------------------"
-        echo "Installing c-blosc"
-        echo "-------------------------"
+        echo_block "Installing c-blosc"
         brew install c-blosc
-    fi    
+    fi
     export CBLOSC_DIR=$(brew --prefix)
 }
 
@@ -123,14 +137,15 @@ function install_mac_newer_python_dependencies() {
 function install_macos() {
     if [ ! -x "$(command -v brew)" ]
     then
-        echo "-------------------------"
-        echo "Installing Brew"
-        echo "-------------------------"
+        echo_block "Installing Brew"
         /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
     fi
+
+    brew install gettext
+
     #Gets number after decimal in python version
     version=$(egrep -o 3.\[0-9\]+ <<< $PYTHON | sed 's/3.//g')
-    
+
     if [[ $version -ge 9 ]]; then               #Checks if python version >= 3.9
         install_mac_newer_python_dependencies
     fi
@@ -140,7 +155,14 @@ function install_macos() {
 # Install bot Debian_ubuntu
 function install_debian() {
     sudo apt-get update
-    sudo apt-get install -y build-essential autoconf libtool pkg-config make wget git $(echo lib${PYTHON}-dev ${PYTHON}-venv)
+    sudo apt-get install -y gcc build-essential autoconf libtool pkg-config make wget git $(echo lib${PYTHON}-dev ${PYTHON}-venv)
+    install_talib
+}
+
+# Install bot RedHat_CentOS
+function install_redhat() {
+    sudo yum update
+    sudo yum install -y gcc gcc-c++ make autoconf libtool pkg-config wget git $(echo ${PYTHON}-devel | sed 's/\.//g')
     install_talib
 }
 
@@ -152,9 +174,7 @@ function update() {
 
 # Reset Develop or Stable branch
 function reset() {
-    echo "----------------------------"
-    echo "Resetting branch and virtual env"
-    echo "----------------------------"
+    echo_block "Resetting branch and virtual env"
 
     if [ "1" == $(git branch -vv |grep -cE "\* develop|\* stable") ]
     then
@@ -192,48 +212,39 @@ function reset() {
 }
 
 function config() {
-
-    echo "-------------------------"
-    echo "Please use 'freqtrade new-config -c config.json' to generate a new configuration file."
-    echo "-------------------------"
+    echo_block "Please use 'freqtrade new-config -c config.json' to generate a new configuration file."
 }
 
 function install() {
-    echo "-------------------------"
-    echo "Installing mandatory dependencies"
-    echo "-------------------------"
 
-    if [ "$(uname -s)" == "Darwin" ]
-    then
+    echo_block "Installing mandatory dependencies"
+
+    if [ "$(uname -s)" == "Darwin" ]; then
         echo "macOS detected. Setup for this system in-progress"
         install_macos
-    elif [ -x "$(command -v apt-get)" ]
-    then
+    elif [ -x "$(command -v apt-get)" ]; then
         echo "Debian/Ubuntu detected. Setup for this system in-progress"
         install_debian
+    elif [ -x "$(command -v yum)" ]; then
+        echo "Red Hat/CentOS detected. Setup for this system in-progress"
+        install_redhat
     else
         echo "This script does not support your OS."
-        echo "If you have Python3.6 or Python3.7, pip, virtualenv, ta-lib you can continue."
+        echo "If you have Python version 3.8 - 3.10, pip, virtualenv, ta-lib you can continue."
         echo "Wait 10 seconds to continue the next install steps or use ctrl+c to interrupt this shell."
         sleep 10
     fi
     echo
     reset
     config
-    echo "-------------------------"
-    echo "Run the bot !"
-    echo "-------------------------"
+    echo_block "Run the bot !"
     echo "You can now use the bot by executing 'source .env/bin/activate; freqtrade <subcommand>'."
     echo "You can see the list of available bot sub-commands by executing 'source .env/bin/activate; freqtrade --help'."
     echo "You verify that freqtrade is installed successfully by running 'source .env/bin/activate; freqtrade --version'."
 }
 
 function plot() {
-    echo "
-    -----------------------------------------
-    Installing dependencies for Plotting scripts
-    -----------------------------------------
-    "
+    echo_block "Installing dependencies for Plotting scripts"
     ${PYTHON} -m pip install plotly --upgrade
 }
 
@@ -246,7 +257,7 @@ function help() {
     echo "	-p,--plot       Install dependencies for Plotting scripts."
 }
 
-# Verify if 3.7 or 3.8 is installed
+# Verify if 3.8+ is installed
 check_installed_python
 
 case $* in
diff --git a/tests/commands/test_build_config.py b/tests/commands/test_build_config.py
index 66c750e79..e30d5bf94 100644
--- a/tests/commands/test_build_config.py
+++ b/tests/commands/test_build_config.py
@@ -44,6 +44,8 @@ def test_start_new_config(mocker, caplog, exchange):
         'fiat_display_currency': 'EUR',
         'timeframe': '15m',
         'dry_run': True,
+        'trading_mode': 'spot',
+        'margin_mode': '',
         'exchange_name': exchange,
         'exchange_key': 'sampleKey',
         'exchange_secret': 'Samplesecret',
diff --git a/tests/commands/test_commands.py b/tests/commands/test_commands.py
index 135510b38..1431bd22a 100644
--- a/tests/commands/test_commands.py
+++ b/tests/commands/test_commands.py
@@ -8,19 +8,19 @@ from zipfile import ZipFile
 import arrow
 import pytest
 
-from freqtrade.commands import (start_convert_data, start_create_userdir, start_download_data,
-                                start_hyperopt_list, start_hyperopt_show, start_install_ui,
-                                start_list_data, start_list_exchanges, start_list_markets,
-                                start_list_strategies, start_list_timeframes, start_new_strategy,
-                                start_show_trades, start_test_pairlist, start_trading,
-                                start_webserver)
+from freqtrade.commands import (start_backtesting_show, start_convert_data, start_convert_trades,
+                                start_create_userdir, start_download_data, start_hyperopt_list,
+                                start_hyperopt_show, start_install_ui, start_list_data,
+                                start_list_exchanges, start_list_markets, start_list_strategies,
+                                start_list_timeframes, start_new_strategy, start_show_trades,
+                                start_test_pairlist, start_trading, start_webserver)
 from freqtrade.commands.deploy_commands import (clean_ui_subdir, download_and_install_ui,
                                                 get_ui_download_url, read_ui_version)
 from freqtrade.configuration import setup_utils_configuration
 from freqtrade.enums import RunMode
 from freqtrade.exceptions import OperationalException
-from tests.conftest import (create_mock_trades, get_args, log_has, log_has_re, patch_exchange,
-                            patched_configuration_load_config_file)
+from tests.conftest import (CURRENT_TEST_STRATEGY, create_mock_trades, get_args, log_has,
+                            log_has_re, patch_exchange, patched_configuration_load_config_file)
 from tests.conftest_trades import MOCK_TRADE_COUNT
 
 
@@ -208,11 +208,10 @@ def test_list_timeframes(mocker, capsys):
     assert re.search(r"^1d$", captured.out, re.MULTILINE)
 
 
-def test_list_markets(mocker, markets, capsys):
+def test_list_markets(mocker, markets_static, capsys):
 
     api_mock = MagicMock()
-    api_mock.markets = markets
-    patch_exchange(mocker, api_mock=api_mock, id='bittrex')
+    patch_exchange(mocker, api_mock=api_mock, id='bittrex', mock_markets=markets_static)
 
     # Test with no --config
     args = [
@@ -232,12 +231,12 @@ def test_list_markets(mocker, markets, capsys):
     ]
     start_list_markets(get_args(args), False)
     captured = capsys.readouterr()
-    assert ("Exchange Bittrex has 10 active markets: "
-            "BLK/BTC, ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, NEO/BTC, "
-            "TKN/BTC, XLTCUSDT, XRP/BTC.\n"
+    assert ("Exchange Bittrex has 12 active markets: "
+            "ADA/USDT:USDT, BLK/BTC, ETH/BTC, ETH/USDT, ETH/USDT:USDT, LTC/BTC, "
+            "LTC/ETH, LTC/USD, NEO/BTC, TKN/BTC, XLTCUSDT, XRP/BTC.\n"
             in captured.out)
 
-    patch_exchange(mocker, api_mock=api_mock, id="binance")
+    patch_exchange(mocker, api_mock=api_mock, id="binance", mock_markets=markets_static)
     # Test with --exchange
     args = [
         "list-markets",
@@ -247,10 +246,10 @@ def test_list_markets(mocker, markets, capsys):
     pargs['config'] = None
     start_list_markets(pargs, False)
     captured = capsys.readouterr()
-    assert re.match("\nExchange Binance has 10 active markets:\n",
+    assert re.match("\nExchange Binance has 12 active markets:\n",
                     captured.out)
 
-    patch_exchange(mocker, api_mock=api_mock, id="bittrex")
+    patch_exchange(mocker, api_mock=api_mock, id="bittrex", mock_markets=markets_static)
     # Test with --all: all markets
     args = [
         "list-markets", "--all",
@@ -259,9 +258,9 @@ def test_list_markets(mocker, markets, capsys):
     ]
     start_list_markets(get_args(args), False)
     captured = capsys.readouterr()
-    assert ("Exchange Bittrex has 12 markets: "
-            "BLK/BTC, BTT/BTC, ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, LTC/USDT, NEO/BTC, "
-            "TKN/BTC, XLTCUSDT, XRP/BTC.\n"
+    assert ("Exchange Bittrex has 14 markets: "
+            "ADA/USDT:USDT, BLK/BTC, BTT/BTC, ETH/BTC, ETH/USDT, ETH/USDT:USDT, "
+            "LTC/BTC, LTC/ETH, LTC/USD, LTC/USDT, NEO/BTC, TKN/BTC, XLTCUSDT, XRP/BTC.\n"
             in captured.out)
 
     # Test list-pairs subcommand: active pairs
@@ -298,8 +297,8 @@ def test_list_markets(mocker, markets, capsys):
     ]
     start_list_markets(get_args(args), False)
     captured = capsys.readouterr()
-    assert ("Exchange Bittrex has 6 active markets with ETH, LTC as base currencies: "
-            "ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, XLTCUSDT.\n"
+    assert ("Exchange Bittrex has 7 active markets with ETH, LTC as base currencies: "
+            "ETH/BTC, ETH/USDT, ETH/USDT:USDT, LTC/BTC, LTC/ETH, LTC/USD, XLTCUSDT.\n"
             in captured.out)
 
     # active markets, base=LTC
@@ -324,8 +323,8 @@ def test_list_markets(mocker, markets, capsys):
     ]
     start_list_markets(get_args(args), False)
     captured = capsys.readouterr()
-    assert ("Exchange Bittrex has 3 active markets with USDT, USD as quote currencies: "
-            "ETH/USDT, LTC/USD, XLTCUSDT.\n"
+    assert ("Exchange Bittrex has 5 active markets with USDT, USD as quote currencies: "
+            "ADA/USDT:USDT, ETH/USDT, ETH/USDT:USDT, LTC/USD, XLTCUSDT.\n"
             in captured.out)
 
     # active markets, quote=USDT
@@ -337,8 +336,8 @@ def test_list_markets(mocker, markets, capsys):
     ]
     start_list_markets(get_args(args), False)
     captured = capsys.readouterr()
-    assert ("Exchange Bittrex has 2 active markets with USDT as quote currency: "
-            "ETH/USDT, XLTCUSDT.\n"
+    assert ("Exchange Bittrex has 4 active markets with USDT as quote currency: "
+            "ADA/USDT:USDT, ETH/USDT, ETH/USDT:USDT, XLTCUSDT.\n"
             in captured.out)
 
     # active markets, base=LTC, quote=USDT
@@ -400,7 +399,7 @@ def test_list_markets(mocker, markets, capsys):
     ]
     start_list_markets(get_args(args), False)
     captured = capsys.readouterr()
-    assert ("Exchange Bittrex has 10 active markets:\n"
+    assert ("Exchange Bittrex has 12 active markets:\n"
             in captured.out)
 
     # Test tabular output, no markets found
@@ -423,8 +422,8 @@ def test_list_markets(mocker, markets, capsys):
     ]
     start_list_markets(get_args(args), False)
     captured = capsys.readouterr()
-    assert ('["BLK/BTC","ETH/BTC","ETH/USDT","LTC/BTC","LTC/ETH","LTC/USD","NEO/BTC",'
-            '"TKN/BTC","XLTCUSDT","XRP/BTC"]'
+    assert ('["ADA/USDT:USDT","BLK/BTC","ETH/BTC","ETH/USDT","ETH/USDT:USDT",'
+            '"LTC/BTC","LTC/ETH","LTC/USD","NEO/BTC","TKN/BTC","XLTCUSDT","XRP/BTC"]'
             in captured.out)
 
     # Test --print-csv
@@ -435,9 +434,9 @@ def test_list_markets(mocker, markets, capsys):
     ]
     start_list_markets(get_args(args), False)
     captured = capsys.readouterr()
-    assert ("Id,Symbol,Base,Quote,Active,Is pair" in captured.out)
-    assert ("blkbtc,BLK/BTC,BLK,BTC,True,True" in captured.out)
-    assert ("USD-LTC,LTC/USD,LTC,USD,True,True" in captured.out)
+    assert ("Id,Symbol,Base,Quote,Active,Spot,Margin,Future,Leverage" in captured.out)
+    assert ("blkbtc,BLK/BTC,BLK,BTC,True,Spot" in captured.out)
+    assert ("USD-LTC,LTC/USD,LTC,USD,True,Spot" in captured.out)
 
     # Test --one-column
     args = [
@@ -606,16 +605,33 @@ def test_get_ui_download_url(mocker):
 def test_get_ui_download_url_direct(mocker):
     response = MagicMock()
     response.json = MagicMock(
-        side_effect=[[{
-            'assets_url': 'http://whatever.json',
-            'name': '0.0.1',
-            'assets': [{'browser_download_url': 'http://download11.zip'}]}]])
+        return_value=[
+            {
+                'assets_url': 'http://whatever.json',
+                'name': '0.0.2',
+                'assets': [{'browser_download_url': 'http://download22.zip'}]
+            },
+            {
+                'assets_url': 'http://whatever.json',
+                'name': '0.0.1',
+                'assets': [{'browser_download_url': 'http://download1.zip'}]
+            },
+        ])
     get_mock = mocker.patch("freqtrade.commands.deploy_commands.requests.get",
                             return_value=response)
     x, last_version = get_ui_download_url()
     assert get_mock.call_count == 1
+    assert last_version == '0.0.2'
+    assert x == 'http://download22.zip'
+    get_mock.reset_mock()
+    response.json.reset_mock()
+
+    x, last_version = get_ui_download_url('0.0.1')
     assert last_version == '0.0.1'
-    assert x == 'http://download11.zip'
+    assert x == 'http://download1.zip'
+
+    with pytest.raises(ValueError, match="UI-Version not found."):
+        x, last_version = get_ui_download_url('0.0.3')
 
 
 def test_download_data_keyboardInterrupt(mocker, caplog, markets):
@@ -738,6 +754,46 @@ def test_download_data_no_pairs(mocker, caplog):
         start_download_data(pargs)
 
 
+def test_download_data_all_pairs(mocker, markets):
+
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+
+    dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
+                           MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
+    patch_exchange(mocker)
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets)
+    )
+    args = [
+        "download-data",
+        "--exchange",
+        "binance",
+        "--pairs",
+        ".*/USDT"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_download_data(pargs)
+    expected = set(['ETH/USDT', 'XRP/USDT', 'NEO/USDT', 'TKN/USDT'])
+    assert set(dl_mock.call_args_list[0][1]['pairs']) == expected
+    assert dl_mock.call_count == 1
+
+    dl_mock.reset_mock()
+    args = [
+        "download-data",
+        "--exchange",
+        "binance",
+        "--pairs",
+        ".*/USDT",
+        "--include-inactive-pairs",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_download_data(pargs)
+    expected = set(['ETH/USDT', 'LTC/USDT', 'XRP/USDT', 'NEO/USDT', 'TKN/USDT'])
+    assert set(dl_mock.call_args_list[0][1]['pairs']) == expected
+
+
 def test_download_data_trades(mocker, caplog):
     dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_trades_data',
                            MagicMock(return_value=[]))
@@ -754,10 +810,41 @@ def test_download_data_trades(mocker, caplog):
         "--days", "20",
         "--dl-trades"
     ]
-    start_download_data(get_args(args))
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_download_data(pargs)
     assert dl_mock.call_args[1]['timerange'].starttype == "date"
     assert dl_mock.call_count == 1
     assert convert_mock.call_count == 1
+    args = [
+        "download-data",
+        "--exchange", "kraken",
+        "--pairs", "ETH/BTC", "XRP/BTC",
+        "--days", "20",
+        "--trading-mode", "futures",
+        "--dl-trades"
+    ]
+    with pytest.raises(OperationalException,
+                       match="Trade download not supported for futures."):
+        pargs = get_args(args)
+        pargs['config'] = None
+        start_download_data(pargs)
+
+
+def test_start_convert_trades(mocker, caplog):
+    convert_mock = mocker.patch('freqtrade.commands.data_commands.convert_trades_to_ohlcv',
+                                MagicMock(return_value=[]))
+    patch_exchange(mocker)
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value={})
+    )
+    args = [
+        "trades-to-ohlcv",
+        "--exchange", "kraken",
+        "--pairs", "ETH/BTC", "XRP/BTC",
+    ]
+    start_convert_trades(get_args(args))
+    assert convert_mock.call_count == 1
 
 
 def test_start_list_strategies(mocker, caplog, capsys):
@@ -774,7 +861,7 @@ def test_start_list_strategies(mocker, caplog, capsys):
     captured = capsys.readouterr()
     assert "TestStrategyLegacyV1" in captured.out
     assert "legacy_strategy_v1.py" not in captured.out
-    assert "StrategyTestV2" in captured.out
+    assert CURRENT_TEST_STRATEGY in captured.out
 
     # Test regular output
     args = [
@@ -789,7 +876,7 @@ def test_start_list_strategies(mocker, caplog, capsys):
     captured = capsys.readouterr()
     assert "TestStrategyLegacyV1" in captured.out
     assert "legacy_strategy_v1.py" in captured.out
-    assert "StrategyTestV2" in captured.out
+    assert CURRENT_TEST_STRATEGY in captured.out
 
     # Test color output
     args = [
@@ -803,7 +890,7 @@ def test_start_list_strategies(mocker, caplog, capsys):
     captured = capsys.readouterr()
     assert "TestStrategyLegacyV1" in captured.out
     assert "legacy_strategy_v1.py" in captured.out
-    assert "StrategyTestV2" in captured.out
+    assert CURRENT_TEST_STRATEGY in captured.out
     assert "LOAD FAILED" in captured.out
 
 
@@ -871,7 +958,7 @@ def test_hyperopt_list(mocker, capsys, caplog, saved_hyperopt_results, tmpdir):
     mocker.patch(
         'freqtrade.optimize.hyperopt_tools.HyperoptTools._test_hyperopt_results_exist',
         return_value=True
-        )
+    )
 
     def fake_iterator(*args, **kwargs):
         yield from [saved_hyperopt_results]
@@ -1255,8 +1342,8 @@ def test_start_list_data(testdatadir, capsys):
     start_list_data(pargs)
     captured = capsys.readouterr()
     assert "Found 17 pair / timeframe combinations." in captured.out
-    assert "\n|         Pair |       Timeframe |\n" in captured.out
-    assert "\n| UNITTEST/BTC | 1m, 5m, 8m, 30m |\n" in captured.out
+    assert "\n|         Pair |       Timeframe |   Type |\n" in captured.out
+    assert "\n| UNITTEST/BTC | 1m, 5m, 8m, 30m |   spot |\n" in captured.out
 
     args = [
         "list-data",
@@ -1271,15 +1358,33 @@ def test_start_list_data(testdatadir, capsys):
     start_list_data(pargs)
     captured = capsys.readouterr()
     assert "Found 2 pair / timeframe combinations." in captured.out
-    assert "\n|    Pair |   Timeframe |\n" in captured.out
+    assert "\n|    Pair |   Timeframe |   Type |\n" in captured.out
     assert "UNITTEST/BTC" not in captured.out
-    assert "\n| XRP/ETH |      1m, 5m |\n" in captured.out
+    assert "\n| XRP/ETH |      1m, 5m |   spot |\n" in captured.out
+
+    args = [
+        "list-data",
+        "--data-format-ohlcv",
+        "json",
+        "--trading-mode", "futures",
+        "--datadir",
+        str(testdatadir),
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_list_data(pargs)
+    captured = capsys.readouterr()
+
+    assert "Found 5 pair / timeframe combinations." in captured.out
+    assert "\n|          Pair |   Timeframe |         Type |\n" in captured.out
+    assert "\n|      XRP/USDT |          1h |      futures |\n" in captured.out
+    assert "\n|      XRP/USDT |      1h, 8h |         mark |\n" in captured.out
 
 
 @pytest.mark.usefixtures("init_persistence")
 def test_show_trades(mocker, fee, capsys, caplog):
     mocker.patch("freqtrade.persistence.init_db")
-    create_mock_trades(fee)
+    create_mock_trades(fee, False)
     args = [
         "show-trades",
         "--db-url",
@@ -1317,3 +1422,19 @@ def test_show_trades(mocker, fee, capsys, caplog):
 
     with pytest.raises(OperationalException, match=r"--db-url is required for this command."):
         start_show_trades(pargs)
+
+
+def test_backtesting_show(mocker, testdatadir, capsys):
+    sbr = mocker.patch('freqtrade.optimize.optimize_reports.show_backtest_results')
+    args = [
+        "backtesting-show",
+        "--export-filename",
+        f"{testdatadir / 'backtest_results/backtest-result_new.json'}",
+        "--show-pair-list"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_backtesting_show(pargs)
+    assert sbr.call_count == 1
+    out, err = capsys.readouterr()
+    assert "Pairs for Strategy" in out
diff --git a/tests/conftest.py b/tests/conftest.py
index 5e08e7097..9cbb95531 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -4,8 +4,8 @@ import logging
 import re
 from copy import deepcopy
 from datetime import datetime, timedelta
-from functools import reduce
 from pathlib import Path
+from typing import Optional
 from unittest.mock import MagicMock, Mock, PropertyMock
 
 import arrow
@@ -16,15 +16,18 @@ from telegram import Chat, Message, Update
 from freqtrade import constants
 from freqtrade.commands import Arguments
 from freqtrade.data.converter import ohlcv_to_dataframe
-from freqtrade.edge import Edge, PairInfo
-from freqtrade.enums import RunMode
+from freqtrade.edge import PairInfo
+from freqtrade.enums import CandleType, MarginMode, RunMode, SignalDirection, TradingMode
 from freqtrade.exchange import Exchange
 from freqtrade.freqtradebot import FreqtradeBot
-from freqtrade.persistence import LocalTrade, Trade, init_db
+from freqtrade.persistence import LocalTrade, Order, Trade, init_db
 from freqtrade.resolvers import ExchangeResolver
 from freqtrade.worker import Worker
-from tests.conftest_trades import (mock_trade_1, mock_trade_2, mock_trade_3, mock_trade_4,
-                                   mock_trade_5, mock_trade_6)
+from tests.conftest_trades import (leverage_trade, mock_trade_1, mock_trade_2, mock_trade_3,
+                                   mock_trade_4, mock_trade_5, mock_trade_6, short_trade)
+from tests.conftest_trades_usdt import (mock_trade_usdt_1, mock_trade_usdt_2, mock_trade_usdt_3,
+                                        mock_trade_usdt_4, mock_trade_usdt_5, mock_trade_usdt_6,
+                                        mock_trade_usdt_7)
 
 
 logging.getLogger('').setLevel(logging.INFO)
@@ -33,6 +36,9 @@ logging.getLogger('').setLevel(logging.INFO)
 # Do not mask numpy errors as warnings that no one read, raise the exсeption
 np.seterr(all='raise')
 
+CURRENT_TEST_STRATEGY = 'StrategyTestV3'
+TRADE_SIDES = ('long', 'short')
+
 
 def pytest_addoption(parser):
     parser.addoption('--longrun', action='store_true', dest="longrun",
@@ -48,17 +54,23 @@ def pytest_configure(config):
 
 
 def log_has(line, logs):
-    # caplog mocker returns log as a tuple: ('freqtrade.something', logging.WARNING, 'foobar')
-    # and we want to match line against foobar in the tuple
-    return reduce(lambda a, b: a or b,
-                  filter(lambda x: x[2] == line, logs.record_tuples),
-                  False)
+    """Check if line is found on some caplog's message."""
+    return any(line == message for message in logs.messages)
 
 
 def log_has_re(line, logs):
-    return reduce(lambda a, b: a or b,
-                  filter(lambda x: re.match(line, x[2]), logs.record_tuples),
-                  False)
+    """Check if line matches some caplog's message."""
+    return any(re.match(line, message) for message in logs.messages)
+
+
+def num_log_has(line, logs):
+    """Check how many times line is found in caplog's messages."""
+    return sum(line == message for message in logs.messages)
+
+
+def num_log_has_re(line, logs):
+    """Check how many times line matches caplog's messages."""
+    return sum(bool(re.match(line, message)) for message in logs.messages)
 
 
 def get_args(args):
@@ -75,33 +87,56 @@ def get_mock_coro(return_value):
 
 def patched_configuration_load_config_file(mocker, config) -> None:
     mocker.patch(
-        'freqtrade.configuration.configuration.load_config_file',
+        'freqtrade.configuration.load_config.load_config_file',
         lambda *args, **kwargs: config
     )
 
 
-def patch_exchange(mocker, api_mock=None, id='binance', mock_markets=True) -> None:
+def patch_exchange(
+    mocker,
+    api_mock=None,
+    id='binance',
+    mock_markets=True,
+    mock_supported_modes=True
+) -> None:
     mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock(return_value={}))
     mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
     mocker.patch('freqtrade.exchange.Exchange.validate_ordertypes', MagicMock())
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency', MagicMock())
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     mocker.patch('freqtrade.exchange.Exchange.id', PropertyMock(return_value=id))
     mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value=id.title()))
     mocker.patch('freqtrade.exchange.Exchange.precisionMode', PropertyMock(return_value=2))
+
     if mock_markets:
+        if isinstance(mock_markets, bool):
+            mock_markets = get_markets()
         mocker.patch('freqtrade.exchange.Exchange.markets',
-                     PropertyMock(return_value=get_markets()))
+                     PropertyMock(return_value=mock_markets))
+
+    if mock_supported_modes:
+        mocker.patch(
+            f'freqtrade.exchange.{id.capitalize()}._supported_trading_mode_margin_pairs',
+            PropertyMock(return_value=[
+                (TradingMode.MARGIN, MarginMode.CROSS),
+                (TradingMode.MARGIN, MarginMode.ISOLATED),
+                (TradingMode.FUTURES, MarginMode.CROSS),
+                (TradingMode.FUTURES, MarginMode.ISOLATED)
+            ])
+        )
 
     if api_mock:
         mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
     else:
         mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock())
+        mocker.patch('freqtrade.exchange.Exchange.timeframes', PropertyMock(
+                return_value=['5m', '15m', '1h', '1d']))
 
 
 def get_patched_exchange(mocker, config, api_mock=None, id='binance',
-                         mock_markets=True) -> Exchange:
-    patch_exchange(mocker, api_mock, id, mock_markets)
+                         mock_markets=True, mock_supported_modes=True) -> Exchange:
+    patch_exchange(mocker, api_mock, id, mock_markets, mock_supported_modes)
     config['exchange']['name'] = id
     try:
         exchange = ExchangeResolver.load_exchange(id, config)
@@ -136,11 +171,6 @@ def patch_edge(mocker) -> None:
     mocker.patch('freqtrade.edge.Edge.calculate', MagicMock(return_value=True))
 
 
-def get_patched_edge(mocker, config) -> Edge:
-    patch_edge(mocker)
-    edge = Edge(config)
-    return edge
-
 # Functions for recurrent object patching
 
 
@@ -152,7 +182,6 @@ def patch_freqtradebot(mocker, config) -> None:
     :return: None
     """
     mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
-    init_db(config['db_url'])
     patch_exchange(mocker)
     mocker.patch('freqtrade.freqtradebot.RPCManager._init', MagicMock())
     mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock())
@@ -182,17 +211,121 @@ def get_patched_worker(mocker, config) -> Worker:
     return Worker(args=None, config=config)
 
 
-def patch_get_signal(freqtrade: FreqtradeBot, value=(True, False, None)) -> None:
+def patch_get_signal(
+    freqtrade: FreqtradeBot,
+    enter_long=True,
+    exit_long=False,
+    enter_short=False,
+    exit_short=False,
+    enter_tag: Optional[str] = None,
+    exit_tag: Optional[str] = None,
+) -> None:
     """
     :param mocker: mocker to patch IStrategy class
-    :param value: which value IStrategy.get_signal() must return
     :return: None
     """
-    freqtrade.strategy.get_signal = lambda e, s, x: value
+    # returns (Signal-direction, signaname)
+    def patched_get_entry_signal(*args, **kwargs):
+        direction = None
+        if enter_long and not any([exit_long, enter_short]):
+            direction = SignalDirection.LONG
+        if enter_short and not any([exit_short, enter_long]):
+            direction = SignalDirection.SHORT
+
+        return direction, enter_tag
+
+    freqtrade.strategy.get_entry_signal = patched_get_entry_signal
+
+    def patched_get_exit_signal(pair, timeframe, dataframe, is_short):
+        if is_short:
+            return enter_short, exit_short, exit_tag
+        else:
+            return enter_long, exit_long, exit_tag
+
+    # returns (enter, exit)
+    freqtrade.strategy.get_exit_signal = patched_get_exit_signal
+
     freqtrade.exchange.refresh_latest_ohlcv = lambda p: None
 
 
-def create_mock_trades(fee, use_db: bool = True):
+def create_mock_trades(fee, is_short: Optional[bool] = False, use_db: bool = True):
+    """
+    Create some fake trades ...
+    :param is_short: Optional bool, None creates a mix of long and short trades.
+    """
+    def add_trade(trade):
+        if use_db:
+            Trade.query.session.add(trade)
+        else:
+            LocalTrade.add_bt_trade(trade)
+    is_short1 = is_short if is_short is not None else True
+    is_short2 = is_short if is_short is not None else False
+    # Simulate dry_run entries
+    trade = mock_trade_1(fee, is_short1)
+    add_trade(trade)
+
+    trade = mock_trade_2(fee, is_short1)
+    add_trade(trade)
+
+    trade = mock_trade_3(fee, is_short2)
+    add_trade(trade)
+
+    trade = mock_trade_4(fee, is_short2)
+    add_trade(trade)
+
+    trade = mock_trade_5(fee, is_short2)
+    add_trade(trade)
+
+    trade = mock_trade_6(fee, is_short1)
+    add_trade(trade)
+
+    if use_db:
+        Trade.commit()
+
+
+def create_mock_trades_with_leverage(fee, use_db: bool = True):
+    """
+    Create some fake trades ...
+    """
+    if use_db:
+        Trade.query.session.rollback()
+
+    def add_trade(trade):
+        if use_db:
+            Trade.query.session.add(trade)
+        else:
+            LocalTrade.add_bt_trade(trade)
+
+    # Simulate dry_run entries
+    trade = mock_trade_1(fee, False)
+    add_trade(trade)
+
+    trade = mock_trade_2(fee, False)
+    add_trade(trade)
+
+    trade = mock_trade_3(fee, False)
+    add_trade(trade)
+
+    trade = mock_trade_4(fee, False)
+    add_trade(trade)
+
+    trade = mock_trade_5(fee, False)
+    add_trade(trade)
+
+    trade = mock_trade_6(fee, False)
+    add_trade(trade)
+
+    trade = short_trade(fee)
+    add_trade(trade)
+
+    trade = leverage_trade(fee)
+    add_trade(trade)
+
+    if use_db:
+        Trade.query.session.flush()
+
+
+def create_mock_trades_usdt(fee, use_db: bool = True):
     """
     Create some fake trades ...
     """
@@ -203,26 +336,28 @@ def create_mock_trades(fee, use_db: bool = True):
             LocalTrade.add_bt_trade(trade)
 
     # Simulate dry_run entries
-    trade = mock_trade_1(fee)
+    trade = mock_trade_usdt_1(fee)
     add_trade(trade)
 
-    trade = mock_trade_2(fee)
+    trade = mock_trade_usdt_2(fee)
     add_trade(trade)
 
-    trade = mock_trade_3(fee)
+    trade = mock_trade_usdt_3(fee)
     add_trade(trade)
 
-    trade = mock_trade_4(fee)
+    trade = mock_trade_usdt_4(fee)
     add_trade(trade)
 
-    trade = mock_trade_5(fee)
+    trade = mock_trade_usdt_5(fee)
     add_trade(trade)
 
-    trade = mock_trade_6(fee)
+    trade = mock_trade_usdt_6(fee)
     add_trade(trade)
 
+    trade = mock_trade_usdt_7(fee)
+    add_trade(trade)
     if use_db:
-        Trade.query.session.flush()
+        Trade.commit()
 
 
 @pytest.fixture(autouse=True)
@@ -257,6 +392,11 @@ def default_conf(testdatadir):
     return get_default_conf(testdatadir)
 
 
+@pytest.fixture(scope="function")
+def default_conf_usdt(testdatadir):
+    return get_default_conf_usdt(testdatadir)
+
+
 def get_default_conf(testdatadir):
     """ Returns validated configuration suitable for most tests """
     configuration = {
@@ -276,11 +416,11 @@ def get_default_conf(testdatadir):
         "dry_run_wallet": 1000,
         "stoploss": -0.10,
         "unfilledtimeout": {
-            "buy": 10,
-            "sell": 30
+            "entry": 10,
+            "exit": 30
         },
-        "bid_strategy": {
-            "ask_last_balance": 0.0,
+        "entry_pricing": {
+            "price_last_balance": 0.0,
             "use_order_book": False,
             "order_book_top": 1,
             "check_depth_of_market": {
@@ -288,7 +428,7 @@ def get_default_conf(testdatadir):
                 "bids_to_ask_delta": 1
             }
         },
-        "ask_strategy": {
+        "exit_pricing": {
             "use_order_book": False,
             "order_book_top": 1,
         },
@@ -323,14 +463,41 @@ def get_default_conf(testdatadir):
         "user_data_dir": Path("user_data"),
         "verbosity": 3,
         "strategy_path": str(Path(__file__).parent / "strategy" / "strats"),
-        "strategy": "StrategyTestV2",
+        "strategy": CURRENT_TEST_STRATEGY,
         "disableparamexport": True,
         "internals": {},
         "export": "none",
+        "candle_type_def": CandleType.SPOT,
     }
     return configuration
 
 
+def get_default_conf_usdt(testdatadir):
+    configuration = get_default_conf(testdatadir)
+    configuration.update({
+        "stake_amount": 60.0,
+        "stake_currency": "USDT",
+        "exchange": {
+            "name": "binance",
+            "enabled": True,
+            "key": "key",
+            "secret": "secret",
+            "pair_whitelist": [
+                "ETH/USDT",
+                "LTC/USDT",
+                "XRP/USDT",
+                "NEO/USDT",
+                "TKN/USDT",
+            ],
+            "pair_blacklist": [
+                "DOGE/USDT",
+                "HOT/USDT",
+            ]
+        },
+    })
+    return configuration
+
+
 @pytest.fixture
 def update():
     _update = Update(0)
@@ -370,12 +537,41 @@ def ticker_sell_down():
     })
 
 
+@pytest.fixture
+def ticker_usdt():
+    return MagicMock(return_value={
+        'bid': 2.0,
+        'ask': 2.02,
+        'last': 2.0,
+    })
+
+
+@pytest.fixture
+def ticker_usdt_sell_up():
+    return MagicMock(return_value={
+        'bid': 2.2,
+        'ask': 2.3,
+        'last': 2.2,
+    })
+
+
+@pytest.fixture
+def ticker_usdt_sell_down():
+    return MagicMock(return_value={
+        'bid': 2.01,
+        'ask': 2.0,
+        'last': 2.01,
+    })
+
+
 @pytest.fixture
 def markets():
     return get_markets()
 
 
 def get_markets():
+    # See get_markets_static() for immutable markets and do not modify them unless absolutely
+    # necessary!
     return {
         'ETH/BTC': {
             'id': 'ethbtc',
@@ -383,24 +579,35 @@ def get_markets():
             'base': 'ETH',
             'quote': 'BTC',
             'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
             'precision': {
                 'price': 8,
                 'amount': 8,
                 'cost': 8,
             },
             'lot': 0.00000001,
+            'contractSize': None,
             'limits': {
                 'amount': {
                     'min': 0.01,
-                    'max': 1000,
+                    'max': 100000000,
+                },
+                'price': {
+                    'min': None,
+                    'max': 500000,
                 },
-                'price': 500000,
                 'cost': {
                     'min': 0.0001,
                     'max': 500000,
                 },
+                'leverage': {
+                    'min': 1.0,
+                    'max': 2.0
+                }
             },
-            'info': {},
         },
         'TKN/BTC': {
             'id': 'tknbtc',
@@ -409,24 +616,35 @@ def get_markets():
             'quote': 'BTC',
             # According to ccxt, markets without active item set are also active
             # 'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
             'precision': {
                 'price': 8,
                 'amount': 8,
                 'cost': 8,
             },
             'lot': 0.00000001,
+            'contractSize': None,
             'limits': {
                 'amount': {
                     'min': 0.01,
-                    'max': 1000,
+                    'max': 100000000,
+                },
+                'price': {
+                    'min': None,
+                    'max': 500000,
                 },
-                'price': 500000,
                 'cost': {
                     'min': 0.0001,
                     'max': 500000,
                 },
+                'leverage': {
+                    'min': 1.0,
+                    'max': 5.0
+                }
             },
-            'info': {},
         },
         'BLK/BTC': {
             'id': 'blkbtc',
@@ -434,24 +652,35 @@ def get_markets():
             'base': 'BLK',
             'quote': 'BTC',
             'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
             'precision': {
                 'price': 8,
                 'amount': 8,
                 'cost': 8,
             },
             'lot': 0.00000001,
+            'contractSize': None,
             'limits': {
                 'amount': {
                     'min': 0.01,
                     'max': 1000,
                 },
-                'price': 500000,
+                'price': {
+                    'min': None,
+                    'max': 500000,
+                },
                 'cost': {
                     'min': 0.0001,
                     'max': 500000,
                 },
+                'leverage': {
+                    'min': 1.0,
+                    'max': 3.0
+                },
             },
-            'info': {},
         },
         'LTC/BTC': {
             'id': 'ltcbtc',
@@ -459,22 +688,34 @@ def get_markets():
             'base': 'LTC',
             'quote': 'BTC',
             'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
             'precision': {
                 'price': 8,
                 'amount': 8,
                 'cost': 8,
             },
             'lot': 0.00000001,
+            'contractSize': None,
             'limits': {
                 'amount': {
                     'min': 0.01,
-                    'max': 1000,
+                    'max': 100000000,
+                },
+                'price': {
+                    'min': None,
+                    'max': 500000,
                 },
-                'price': 500000,
                 'cost': {
                     'min': 0.0001,
                     'max': 500000,
                 },
+                'leverage': {
+                    'min': None,
+                    'max': None
+                },
             },
             'info': {},
         },
@@ -484,22 +725,34 @@ def get_markets():
             'base': 'XRP',
             'quote': 'BTC',
             'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
             'precision': {
                 'price': 8,
                 'amount': 8,
                 'cost': 8,
             },
             'lot': 0.00000001,
+            'contractSize': None,
             'limits': {
                 'amount': {
                     'min': 0.01,
-                    'max': 1000,
+                    'max': 100000000,
+                },
+                'price': {
+                    'min': None,
+                    'max': 500000,
                 },
-                'price': 500000,
                 'cost': {
                     'min': 0.0001,
                     'max': 500000,
                 },
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
             },
             'info': {},
         },
@@ -509,22 +762,34 @@ def get_markets():
             'base': 'NEO',
             'quote': 'BTC',
             'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
             'precision': {
                 'price': 8,
                 'amount': 8,
                 'cost': 8,
             },
             'lot': 0.00000001,
+            'contractSize': None,
             'limits': {
                 'amount': {
                     'min': 0.01,
-                    'max': 1000,
+                    'max': 100000000,
+                },
+                'price': {
+                    'min': None,
+                    'max': 500000,
                 },
-                'price': 500000,
                 'cost': {
                     'min': 0.0001,
                     'max': 500000,
                 },
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
             },
             'info': {},
         },
@@ -534,6 +799,11 @@ def get_markets():
             'base': 'BTT',
             'quote': 'BTC',
             'active': False,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
+            'contractSize': None,
             'precision': {
                 'base': 8,
                 'quote': 8,
@@ -552,7 +822,11 @@ def get_markets():
                 'cost': {
                     'min': 0.0001,
                     'max': None
-                }
+                },
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
             },
             'info': {},
         },
@@ -561,22 +835,52 @@ def get_markets():
             'symbol': 'ETH/USDT',
             'base': 'ETH',
             'quote': 'USDT',
+            'settle': None,
+            'baseId': 'ETH',
+            'quoteId': 'USDT',
+            'settleId': None,
+            'type': 'spot',
+            'spot': True,
+            'margin': True,
+            'swap': True,
+            'future': True,
+            'option': False,
+            'active': True,
+            'contract': None,
+            'linear': None,
+            'inverse': None,
+            'taker': 0.0006,
+            'maker': 0.0002,
+            'contractSize': None,
+            'expiry': None,
+            'expiryDateTime': None,
+            'strike': None,
+            'optionType': None,
             'precision': {
                 'amount': 8,
-                'price': 8
+                'price': 8,
             },
             'limits': {
+                'leverage': {
+                    'min': 1,
+                    'max': 100,
+                },
                 'amount': {
                     'min': 0.02214286,
-                    'max': None
+                    'max': None,
                 },
                 'price': {
                     'min': 1e-08,
-                    'max': None
-                }
+                    'max': None,
+                },
+                'cost': {
+                    'min': None,
+                    'max': None,
+                },
+            },
+            'info': {
+                'maintenance_rate': '0.005',
             },
-            'active': True,
-            'info': {},
         },
         'LTC/USDT': {
             'id': 'USDT-LTC',
@@ -584,6 +888,16 @@ def get_markets():
             'base': 'LTC',
             'quote': 'USDT',
             'active': False,
+            'spot': True,
+            'future': True,
+            'swap': True,
+            'margin': True,
+            'linear': None,
+            'inverse': False,
+            'type': 'spot',
+            'contractSize': None,
+            'taker': 0.0006,
+            'maker': 0.0002,
             'precision': {
                 'amount': 8,
                 'price': 8
@@ -596,7 +910,143 @@ def get_markets():
                 'price': {
                     'min': 1e-08,
                     'max': None
-                }
+                },
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
+                'cost': {
+                    'min': None,
+                    'max': None,
+                },
+            },
+            'info': {},
+        },
+        'XRP/USDT': {
+            'id': 'xrpusdt',
+            'symbol': 'XRP/USDT',
+            'base': 'XRP',
+            'quote': 'USDT',
+            'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
+            'taker': 0.0006,
+            'maker': 0.0002,
+            'precision': {
+                'price': 8,
+                'amount': 8,
+                'cost': 8,
+            },
+            'lot': 0.00000001,
+            'contractSize': None,
+            'limits': {
+                'amount': {
+                    'min': 0.01,
+                    'max': 1000,
+                },
+                'price': {
+                    'min': None,
+                    'max': 500000,
+                },
+                'cost': {
+                    'min': 0.0001,
+                    'max': 500000,
+                },
+            },
+            'info': {},
+        },
+        'NEO/USDT': {
+            'id': 'neousdt',
+            'symbol': 'NEO/USDT',
+            'base': 'NEO',
+            'quote': 'USDT',
+            'settle': '',
+            'baseId': 'NEO',
+            'quoteId': 'USDT',
+            'settleId': '',
+            'type': 'spot',
+            'spot': True,
+            'margin': True,
+            'swap': False,
+            'futures': False,
+            'option': False,
+            'active': True,
+            'contract': False,
+            'linear': None,
+            'inverse': None,
+            'taker': 0.0006,
+            'maker': 0.0002,
+            'contractSize': None,
+            'expiry': None,
+            'expiryDatetime': None,
+            'strike': None,
+            'optionType': None,
+            'tierBased': None,
+            'percentage': None,
+            'lot': 0.00000001,
+            'precision': {
+                'price': 8,
+                'amount': 8,
+                'cost': 8,
+            },
+            'limits': {
+                "leverage": {
+                    'min': 1,
+                    'max': 10
+                },
+                'amount': {
+                    'min': 0.01,
+                    'max': 1000,
+                },
+                'price': {
+                    'min': None,
+                    'max': 500000,
+                },
+                'cost': {
+                    'min': 0.0001,
+                    'max': 500000,
+                },
+            },
+            'info': {},
+        },
+        'TKN/USDT': {
+            'id': 'tknusdt',
+            'symbol': 'TKN/USDT',
+            'base': 'TKN',
+            'quote': 'USDT',
+            'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
+            'contractSize': None,
+            'taker': 0.0006,
+            'maker': 0.0002,
+            'precision': {
+                'price': 8,
+                'amount': 8,
+                'cost': 8,
+            },
+            'lot': 0.00000001,
+            'limits': {
+                'amount': {
+                    'min': 0.01,
+                    'max': 100000000000,
+                },
+                'price': {
+                    'min': None,
+                    'max': 500000
+                },
+                'cost': {
+                    'min': 0.0001,
+                    'max': 500000,
+                },
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
             },
             'info': {},
         },
@@ -606,6 +1056,11 @@ def get_markets():
             'base': 'LTC',
             'quote': 'USD',
             'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
+            'contractSize': None,
             'precision': {
                 'amount': 8,
                 'price': 8
@@ -618,7 +1073,15 @@ def get_markets():
                 'price': {
                     'min': 1e-08,
                     'max': None
-                }
+                },
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
+                'cost': {
+                    'min': None,
+                    'max': None,
+                },
             },
             'info': {},
         },
@@ -628,11 +1091,22 @@ def get_markets():
             'base': 'LTC',
             'quote': 'USDT',
             'active': True,
+            'spot': False,
+            'type': 'swap',
+            'contractSize': 0.01,
+            'swap': False,
+            'linear': False,
+            'taker': 0.0006,
+            'maker': 0.0002,
             'precision': {
                 'amount': 8,
                 'price': 8
             },
             'limits': {
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
                 'amount': {
                     'min': 0.06646786,
                     'max': None
@@ -640,7 +1114,11 @@ def get_markets():
                 'price': {
                     'min': 1e-08,
                     'max': None
-                }
+                },
+                'cost': {
+                    'min': None,
+                    'max': None,
+                },
             },
             'info': {},
         },
@@ -650,6 +1128,11 @@ def get_markets():
             'base': 'LTC',
             'quote': 'ETH',
             'active': True,
+            'spot': True,
+            'swap': False,
+            'linear': None,
+            'type': 'spot',
+            'contractSize': None,
             'precision': {
                 'base': 8,
                 'quote': 8,
@@ -657,6 +1140,10 @@ def get_markets():
                 'price': 5
             },
             'limits': {
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
                 'amount': {
                     'min': 0.001,
                     'max': 10000000.0
@@ -670,16 +1157,261 @@ def get_markets():
                     'max': None
                 }
             },
+            'info': {
+            }
+        },
+        'ETH/USDT:USDT': {
+            'id': 'ETH_USDT',
+            'symbol': 'ETH/USDT:USDT',
+            'base': 'ETH',
+            'quote': 'USDT',
+            'settle': 'USDT',
+            'baseId': 'ETH',
+            'quoteId': 'USDT',
+            'settleId': 'USDT',
+            'type': 'swap',
+            'spot': False,
+            'margin': False,
+            'swap': True,
+            'future': True,  # Binance mode ...
+            'option': False,
+            'contract': True,
+            'linear': True,
+            'inverse': False,
+            'tierBased': False,
+            'percentage': True,
+            'taker': 0.0006,
+            'maker': 0.0002,
+            'contractSize': 10,
+            'active': True,
+            'expiry': None,
+            'expiryDatetime': None,
+            'strike': None,
+            'optionType': None,
+            'limits': {
+                'leverage': {
+                    'min': 1,
+                    'max': 100
+                },
+                'amount': {
+                    'min': 1,
+                    'max': 300000
+                },
+                'price': {
+                    'min': None,
+                    'max': None,
+                },
+                'cost': {
+                    'min': None,
+                    'max': None,
+                }
+            },
+            'precision': {
+                'price': 0.05,
+                'amount': 1
+            },
+            'info': {}
+        },
+        'ADA/USDT:USDT': {
+            'limits': {
+                'leverage': {
+                    'min': 1,
+                    'max': 20,
+                },
+                'amount': {
+                    'min': 1,
+                    'max': 1000000,
+                },
+                'price': {
+                    'min': 0.52981,
+                    'max': 1.58943,
+                },
+                'cost': {
+                    'min': None,
+                    'max': None,
+                }
+            },
+            'precision': {
+                'amount': 1,
+                'price': 0.00001
+            },
+            'tierBased': True,
+            'percentage': True,
+            'taker': 0.0000075,
+            'maker': -0.0000025,
+            'feeSide': 'get',
+            'tiers': {
+                'maker': [
+                    [0, 0.002],       [1.5, 0.00185],
+                    [3, 0.00175],     [6, 0.00165],
+                    [12.5, 0.00155],  [25, 0.00145],
+                    [75, 0.00135],    [200, 0.00125],
+                    [500, 0.00115],   [1250, 0.00105],
+                    [2500, 0.00095],  [3000, 0.00085],
+                    [6000, 0.00075],  [11000, 0.00065],
+                    [20000, 0.00055], [40000, 0.00055],
+                    [75000, 0.00055]
+                ],
+                'taker': [
+                    [0, 0.002],       [1.5, 0.00195],
+                    [3, 0.00185],     [6, 0.00175],
+                    [12.5, 0.00165],  [25, 0.00155],
+                    [75, 0.00145],    [200, 0.00135],
+                    [500, 0.00125],   [1250, 0.00115],
+                    [2500, 0.00105],  [3000, 0.00095],
+                    [6000, 0.00085],  [11000, 0.00075],
+                    [20000, 0.00065], [40000, 0.00065],
+                    [75000, 0.00065]
+                ]
+            },
+            'id': 'ADA_USDT',
+            'symbol': 'ADA/USDT:USDT',
+            'base': 'ADA',
+            'quote': 'USDT',
+            'settle': 'USDT',
+            'baseId': 'ADA',
+            'quoteId': 'USDT',
+            'settleId': 'usdt',
+            'type': 'swap',
+            'spot': False,
+            'margin': False,
+            'swap': True,
+            'future': True,  # Binance mode ...
+            'option': False,
+            'active': True,
+            'contract': True,
+            'linear': True,
+            'inverse': False,
+            'contractSize': 0.01,
+            'expiry': None,
+            'expiryDatetime': None,
+            'strike': None,
+            'optionType': None,
+            'info': {}
+        },
+        'SOL/BUSD:BUSD': {
+            'limits': {
+                'leverage': {'min': None, 'max': None},
+                'amount': {'min': 1, 'max': 1000000},
+                'price': {'min': 0.04, 'max': 100000},
+                'cost': {'min': 5, 'max': None},
+                'market': {'min': 1, 'max': 1500}
+            },
+            'precision': {'amount': 0, 'price': 2, 'base': 8, 'quote': 8},
+            'tierBased': False,
+            'percentage': True,
+            'taker': 0.0004,
+            'maker': 0.0002,
+            'feeSide': 'get',
+            'id': 'SOLBUSD',
+            'lowercaseId': 'solbusd',
+            'symbol': 'SOL/BUSD',
+            'base': 'SOL',
+            'quote': 'BUSD',
+            'settle': 'BUSD',
+            'baseId': 'SOL',
+            'quoteId': 'BUSD',
+            'settleId': 'BUSD',
+            'type': 'future',
+            'spot': False,
+            'margin': False,
+            'future': True,
+            'delivery': False,
+            'option': False,
+            'active': True,
+            'contract': True,
+            'linear': True,
+            'inverse': False,
+            'contractSize': 1,
+            'expiry': None,
+            'expiryDatetime': None,
+            'strike': None,
+            'optionType': None,
+            'info': {
+                'symbol': 'SOLBUSD',
+                'pair': 'SOLBUSD',
+                'contractType': 'PERPETUAL',
+                'deliveryDate': '4133404800000',
+                'onboardDate': '1630566000000',
+                'status': 'TRADING',
+                'maintMarginPercent': '2.5000',
+                'requiredMarginPercent': '5.0000',
+                'baseAsset': 'SOL',
+                'quoteAsset': 'BUSD',
+                'marginAsset': 'BUSD',
+                'pricePrecision': '4',
+                'quantityPrecision': '0',
+                'baseAssetPrecision': '8',
+                'quotePrecision': '8',
+                'underlyingType': 'COIN',
+                'underlyingSubType': [],
+                'settlePlan': '0',
+                'triggerProtect': '0.0500',
+                'liquidationFee': '0.005000',
+                'marketTakeBound': '0.05',
+                'filters': [
+                    {
+                        'minPrice': '0.0400',
+                        'maxPrice': '100000',
+                        'filterType': 'PRICE_FILTER',
+                        'tickSize': '0.0100'
+                    },
+                    {
+                        'stepSize': '1',
+                        'filterType': 'LOT_SIZE',
+                        'maxQty': '1000000',
+                        'minQty': '1'
+                    },
+                    {
+                        'stepSize': '1',
+                        'filterType': 'MARKET_LOT_SIZE',
+                        'maxQty': '1500',
+                        'minQty': '1'
+                    },
+                    {'limit': '200', 'filterType': 'MAX_NUM_ORDERS'},
+                    {'limit': '10', 'filterType': 'MAX_NUM_ALGO_ORDERS'},
+                    {'notional': '5', 'filterType': 'MIN_NOTIONAL'},
+                    {
+                        'multiplierDown': '0.9500',
+                        'multiplierUp': '1.0500',
+                        'multiplierDecimal': '4',
+                        'filterType': 'PERCENT_PRICE'
+                    }
+                ],
+                'orderTypes': [
+                    'LIMIT',
+                    'MARKET',
+                    'STOP',
+                    'STOP_MARKET',
+                    'TAKE_PROFIT',
+                    'TAKE_PROFIT_MARKET',
+                    'TRAILING_STOP_MARKET'
+                ],
+                'timeInForce': ['GTC', 'IOC', 'FOK', 'GTX']
+            }
         },
     }
 
 
 @pytest.fixture
-def shitcoinmarkets(markets):
+def markets_static():
+    # These markets are used in some tests that would need adaptation should anything change in
+    # market list. Do not modify this list without a good reason! Do not modify market parameters
+    # of listed pairs in get_markets() without a good reason either!
+    static_markets = ['BLK/BTC', 'BTT/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD',
+                      'LTC/USDT', 'NEO/BTC', 'TKN/BTC', 'XLTCUSDT', 'XRP/BTC',
+                      'ADA/USDT:USDT', 'ETH/USDT:USDT',
+                      ]
+    all_markets = get_markets()
+    return {m: all_markets[m] for m in static_markets}
+
+
+@pytest.fixture
+def shitcoinmarkets(markets_static):
     """
     Fixture with shitcoin markets - used to test filters in pairlists
     """
-    shitmarkets = deepcopy(markets)
+    shitmarkets = deepcopy(markets_static)
     shitmarkets.update({
         'HOT/BTC': {
             'id': 'HOTBTC',
@@ -687,6 +1419,8 @@ def shitcoinmarkets(markets):
             'base': 'HOT',
             'quote': 'BTC',
             'active': True,
+            'spot': True,
+            'type': 'spot',
             'precision': {
                 'base': 8,
                 'quote': 8,
@@ -715,6 +1449,8 @@ def shitcoinmarkets(markets):
             'base': 'FUEL',
             'quote': 'BTC',
             'active': True,
+            'spot': True,
+            'type': 'spot',
             'precision': {
                 'base': 8,
                 'quote': 8,
@@ -749,6 +1485,22 @@ def shitcoinmarkets(markets):
                 "price": 4
             },
             "limits": {
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
+                'amount': {
+                    'min': None,
+                    'max': None,
+                },
+                'price': {
+                    'min': None,
+                    'max': None,
+                },
+                'cost': {
+                    'min': None,
+                    'max': None,
+                },
             },
             "id": "NANOUSDT",
             "symbol": "NANO/USDT",
@@ -774,6 +1526,22 @@ def shitcoinmarkets(markets):
                 "price": 4
             },
             "limits": {
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
+                'amount': {
+                    'min': None,
+                    'max': None,
+                },
+                'price': {
+                    'min': None,
+                    'max': None,
+                },
+                'cost': {
+                    'min': None,
+                    'max': None,
+                },
             },
             "id": "ADAHALFUSDT",
             "symbol": "ADAHALF/USDT",
@@ -799,6 +1567,22 @@ def shitcoinmarkets(markets):
                 "price": 4
             },
             "limits": {
+                'leverage': {
+                    'min': None,
+                    'max': None,
+                },
+                'amount': {
+                    'min': None,
+                    'max': None,
+                },
+                'price': {
+                    'min': None,
+                    'max': None,
+                },
+                'cost': {
+                    'min': None,
+                    'max': None,
+                },
             },
             "id": "ADADOUBLEUSDT",
             "symbol": "ADADOUBLE/USDT",
@@ -828,8 +1612,8 @@ def limit_buy_order_open():
         'type': 'limit',
         'side': 'buy',
         'symbol': 'mocked',
+        'timestamp': arrow.utcnow().int_timestamp * 1000,
         'datetime': arrow.utcnow().isoformat(),
-        'timestamp': arrow.utcnow().int_timestamp,
         'price': 0.00001099,
         'amount': 90.99181073,
         'filled': 0.0,
@@ -855,6 +1639,7 @@ def market_buy_order():
         'type': 'market',
         'side': 'buy',
         'symbol': 'mocked',
+        'timestamp': arrow.utcnow().int_timestamp * 1000,
         'datetime': arrow.utcnow().isoformat(),
         'price': 0.00004099,
         'amount': 91.99181073,
@@ -871,6 +1656,7 @@ def market_sell_order():
         'type': 'market',
         'side': 'sell',
         'symbol': 'mocked',
+        'timestamp': arrow.utcnow().int_timestamp * 1000,
         'datetime': arrow.utcnow().isoformat(),
         'price': 0.00004173,
         'amount': 91.99181073,
@@ -887,7 +1673,8 @@ def limit_buy_order_old():
         'type': 'limit',
         'side': 'buy',
         'symbol': 'mocked',
-        'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
+        'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
+        'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
         'price': 0.00001099,
         'amount': 90.99181073,
         'filled': 0.0,
@@ -903,6 +1690,7 @@ def limit_sell_order_old():
         'type': 'limit',
         'side': 'sell',
         'symbol': 'ETH/BTC',
+        'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
         'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
         'price': 0.00001099,
         'amount': 90.99181073,
@@ -919,6 +1707,7 @@ def limit_buy_order_old_partial():
         'type': 'limit',
         'side': 'buy',
         'symbol': 'ETH/BTC',
+        'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
         'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
         'price': 0.00001099,
         'amount': 90.99181073,
@@ -948,7 +1737,7 @@ def limit_buy_order_canceled_empty(request):
             'info': {},
             'id': '1234512345',
             'clientOrderId': None,
-            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
+            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
             'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
             'lastTradeTimestamp': None,
             'symbol': 'LTC/USDT',
@@ -969,7 +1758,7 @@ def limit_buy_order_canceled_empty(request):
             'info': {},
             'id': 'AZNPFF-4AC4N-7MKTAT',
             'clientOrderId': None,
-            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
+            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
             'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
             'lastTradeTimestamp': None,
             'status': 'canceled',
@@ -990,7 +1779,7 @@ def limit_buy_order_canceled_empty(request):
             'info': {},
             'id': '1234512345',
             'clientOrderId': 'alb1234123',
-            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
+            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
             'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
             'lastTradeTimestamp': None,
             'symbol': 'LTC/USDT',
@@ -1011,7 +1800,7 @@ def limit_buy_order_canceled_empty(request):
             'info': {},
             'id': '1234512345',
             'clientOrderId': 'alb1234123',
-            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
+            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
             'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
             'lastTradeTimestamp': None,
             'symbol': 'LTC/USDT',
@@ -1035,9 +1824,9 @@ def limit_sell_order_open():
         'id': 'mocked_limit_sell',
         'type': 'limit',
         'side': 'sell',
-        'pair': 'mocked',
+        'symbol': 'mocked',
         'datetime': arrow.utcnow().isoformat(),
-        'timestamp': arrow.utcnow().int_timestamp,
+        'timestamp': arrow.utcnow().int_timestamp * 1000,
         'price': 0.00001173,
         'amount': 90.99181073,
         'filled': 0.0,
@@ -1203,7 +1992,7 @@ def tickers():
         'BLK/BTC': {
             'symbol': 'BLK/BTC',
             'timestamp': 1522014806072,
-            'datetime': '2018-03-25T21:53:26.720Z',
+            'datetime': '2018-03-25T21:53:26.072Z',
             'high': 0.007745,
             'low': 0.007512,
             'bid': 0.007729,
@@ -1521,27 +2310,34 @@ def result(testdatadir):
 
 @pytest.fixture(scope="function")
 def trades_for_order():
-    return [{'info': {'id': 34567,
-                      'orderId': 123456,
-                      'price': '0.24544100',
-                      'qty': '8.00000000',
-                      'commission': '0.00800000',
-                      'commissionAsset': 'LTC',
-                      'time': 1521663363189,
-                      'isBuyer': True,
-                      'isMaker': False,
-                      'isBestMatch': True},
-             'timestamp': 1521663363189,
-             'datetime': '2018-03-21T20:16:03.189Z',
-             'symbol': 'LTC/ETH',
-             'id': '34567',
-             'order': '123456',
-             'type': None,
-             'side': 'buy',
-             'price': 0.245441,
-             'cost': 1.963528,
-             'amount': 8.0,
-             'fee': {'cost': 0.008, 'currency': 'LTC'}}]
+    return [{
+        'info': {
+            'id': 34567,
+            'orderId': 123456,
+            'price': '2.0',
+            'qty': '8.00000000',
+            'commission': '0.00800000',
+            'commissionAsset': 'LTC',
+            'time': 1521663363189,
+            'isBuyer': True,
+            'isMaker': False,
+            'isBestMatch': True
+        },
+        'timestamp': 1521663363189,
+        'datetime': '2018-03-21T20:16:03.189Z',
+        'symbol': 'LTC/USDT',
+        'id': '34567',
+        'order': '123456',
+        'type': None,
+        'side': 'buy',
+        'price': 2.0,
+        'cost': 16.0,
+        'amount': 8.0,
+        'fee': {
+            'cost': 0.008,
+            'currency': 'LTC'
+        }
+    }]
 
 
 @pytest.fixture(scope="function")
@@ -1685,14 +2481,6 @@ def trades_for_order2():
              'fee': {'cost': 0.004, 'currency': 'LTC'}}]
 
 
-@pytest.fixture(scope="function")
-def trades_for_order3(trades_for_order2):
-    # Different fee currencies for each trade
-    trades_for_order = deepcopy(trades_for_order2)
-    trades_for_order[0]['fee'] = {'cost': 0.02, 'currency': 'BNB'}
-    return trades_for_order
-
-
 @pytest.fixture
 def buy_order_fee():
     return {
@@ -1700,7 +2488,8 @@ def buy_order_fee():
         'type': 'limit',
         'side': 'buy',
         'symbol': 'mocked',
-        'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
+        'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp * 1000,
+        'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
         'price': 0.245441,
         'amount': 8.0,
         'cost': 1.963528,
@@ -1800,7 +2589,7 @@ def import_fails() -> None:
 
 @pytest.fixture(scope="function")
 def open_trade():
-    return Trade(
+    trade = Trade(
         pair='ETH/BTC',
         open_rate=0.00001099,
         exchange='binance',
@@ -1812,6 +2601,62 @@ def open_trade():
         open_date=arrow.utcnow().shift(minutes=-601).datetime,
         is_open=True
     )
+    trade.orders = [
+        Order(
+            ft_order_side='buy',
+            ft_pair=trade.pair,
+            ft_is_open=False,
+            order_id='123456789',
+            status="closed",
+            symbol=trade.pair,
+            order_type="market",
+            side="buy",
+            price=trade.open_rate,
+            average=trade.open_rate,
+            filled=trade.amount,
+            remaining=0,
+            cost=trade.open_rate * trade.amount,
+            order_date=trade.open_date,
+            order_filled_date=trade.open_date,
+        )
+    ]
+    return trade
+
+
+@pytest.fixture(scope="function")
+def open_trade_usdt():
+    trade = Trade(
+        pair='ADA/USDT',
+        open_rate=2.0,
+        exchange='binance',
+        open_order_id='123456789',
+        amount=30.0,
+        fee_open=0.0,
+        fee_close=0.0,
+        stake_amount=60.0,
+        open_date=arrow.utcnow().shift(minutes=-601).datetime,
+        is_open=True
+    )
+    trade.orders = [
+        Order(
+            ft_order_side='buy',
+            ft_pair=trade.pair,
+            ft_is_open=False,
+            order_id='123456789',
+            status="closed",
+            symbol=trade.pair,
+            order_type="market",
+            side="buy",
+            price=trade.open_rate,
+            average=trade.open_rate,
+            filled=trade.amount,
+            remaining=0,
+            cost=trade.open_rate * trade.amount,
+            order_date=trade.open_date,
+            order_filled_date=trade.open_date,
+        )
+    ]
+    return trade
 
 
 @pytest.fixture
@@ -1822,7 +2667,7 @@ def saved_hyperopt_results():
             'params_dict': {
                 'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1190, 'roi_t2': 541, 'roi_t3': 408, 'roi_p1': 0.026035863879169705, 'roi_p2': 0.12508730043628782, 'roi_p3': 0.27766427921605896, 'stoploss': -0.2562930402099556},  # noqa: E501
             'params_details': {'buy': {'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.4287874435315165, 408: 0.15112316431545753, 949: 0.026035863879169705, 2139: 0}, 'stoploss': {'stoploss': -0.2562930402099556}},  # noqa: E501
-            'results_metrics': {'total_trades': 2, 'wins': 0, 'draws': 0, 'losses': 2, 'profit_mean': -0.01254995, 'profit_median': -0.012222, 'profit_total': -0.00125625, 'profit_total_abs': -2.50999, 'holding_avg': timedelta(minutes=3930.0), 'stake_currency': 'BTC', 'strategy_name': 'SampleStrategy'},  # noqa: E501
+            'results_metrics': {'total_trades': 2, 'wins': 0, 'draws': 0, 'losses': 2, 'profit_mean': -0.01254995, 'profit_median': -0.012222, 'profit_total': -0.00125625,  'profit_total_abs': -2.50999, 'max_drawdown': 0.23, 'max_drawdown_abs': -0.00125625,  'holding_avg': timedelta(minutes=3930.0), 'stake_currency': 'BTC', 'strategy_name': 'SampleStrategy'},  # noqa: E501
             'results_explanation': '     2 trades. Avg profit  -1.25%. Total profit -0.00125625 BTC (  -2.51Σ%). Avg duration 3930.0 min.',  # noqa: E501
             'total_profit': -0.00125625,
             'current_epoch': 1,
@@ -1838,7 +2683,7 @@ def saved_hyperopt_results():
                 'sell': {'sell-mfi-value': 96, 'sell-fastd-value': 68, 'sell-adx-value': 63, 'sell-rsi-value': 81, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal'},  # noqa: E501
                 'roi': {0: 0.4449309386008759, 140: 0.11955965746663, 823: 0.06403981740598495, 1157: 0},  # noqa: E501
                 'stoploss': {'stoploss': -0.338070047333259}},
-            'results_metrics': {'total_trades': 1, 'wins': 0, 'draws': 0, 'losses': 1, 'profit_mean': 0.012357, 'profit_median': -0.012222, 'profit_total': 6.185e-05, 'profit_total_abs': 0.12357, 'holding_avg': timedelta(minutes=1200.0)},  # noqa: E501
+            'results_metrics': {'total_trades': 1, 'wins': 0, 'draws': 0, 'losses': 1, 'profit_mean': 0.012357, 'profit_median': -0.012222, 'profit_total': 6.185e-05, 'profit_total_abs': 0.12357, 'max_drawdown': 0.23, 'max_drawdown_abs': -0.00125625, 'holding_avg': timedelta(minutes=1200.0)},  # noqa: E501
             'results_explanation': '     1 trades. Avg profit   0.12%. Total profit  0.00006185 BTC (   0.12Σ%). Avg duration 1200.0 min.',  # noqa: E501
             'total_profit': 6.185e-05,
             'current_epoch': 2,
@@ -1848,7 +2693,7 @@ def saved_hyperopt_results():
             'loss': 14.241196856510731,
             'params_dict': {'mfi-value': 25, 'fastd-value': 16, 'adx-value': 29, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 98, 'sell-fastd-value': 72, 'sell-adx-value': 51, 'sell-rsi-value': 82, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 889, 'roi_t2': 533, 'roi_t3': 263, 'roi_p1': 0.04759065393663096, 'roi_p2': 0.1488819964638463, 'roi_p3': 0.4102801822104605, 'stoploss': -0.05394588767607611},  # noqa: E501
             'params_details': {'buy': {'mfi-value': 25, 'fastd-value': 16, 'adx-value': 29, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 98, 'sell-fastd-value': 72, 'sell-adx-value': 51, 'sell-rsi-value': 82, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.6067528326109377, 263: 0.19647265040047726, 796: 0.04759065393663096, 1685: 0}, 'stoploss': {'stoploss': -0.05394588767607611}},  # noqa: E501
-            'results_metrics': {'total_trades': 621, 'wins': 320, 'draws': 0, 'losses': 301, 'profit_mean': -0.043883302093397747, 'profit_median': -0.012222, 'profit_total': -0.13639474, 'profit_total_abs': -272.515306, 'holding_avg': timedelta(minutes=1691.207729468599)},  # noqa: E501
+            'results_metrics': {'total_trades': 621, 'wins': 320, 'draws': 0, 'losses': 301, 'profit_mean': -0.043883302093397747, 'profit_median': -0.012222, 'profit_total': -0.13639474, 'profit_total_abs': -272.515306, 'max_drawdown': 0.25, 'max_drawdown_abs': -272.515306, 'holding_avg': timedelta(minutes=1691.207729468599)},  # noqa: E501
             'results_explanation': '   621 trades. Avg profit  -0.44%. Total profit -0.13639474 BTC (-272.52Σ%). Avg duration 1691.2 min.',  # noqa: E501
             'total_profit': -0.13639474,
             'current_epoch': 3,
@@ -1865,7 +2710,7 @@ def saved_hyperopt_results():
             'loss': 0.22195522184191518,
             'params_dict': {'mfi-value': 17, 'fastd-value': 21, 'adx-value': 38, 'rsi-value': 33, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 87, 'sell-fastd-value': 82, 'sell-adx-value': 78, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 1269, 'roi_t2': 601, 'roi_t3': 444, 'roi_p1': 0.07280999507931168, 'roi_p2': 0.08946698095898986, 'roi_p3': 0.1454876733325284, 'stoploss': -0.18181041180901014},   # noqa: E501
             'params_details': {'buy': {'mfi-value': 17, 'fastd-value': 21, 'adx-value': 38, 'rsi-value': 33, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 87, 'sell-fastd-value': 82, 'sell-adx-value': 78, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.3077646493708299, 444: 0.16227697603830155, 1045: 0.07280999507931168, 2314: 0}, 'stoploss': {'stoploss': -0.18181041180901014}},  # noqa: E501
-            'results_metrics': {'total_trades': 14, 'wins': 6, 'draws': 0, 'losses': 8, 'profit_mean': -0.003539515, 'profit_median': -0.012222, 'profit_total': -0.002480140000000001, 'profit_total_abs': -4.955321, 'holding_avg': timedelta(minutes=3402.8571428571427)},  # noqa: E501
+            'results_metrics': {'total_trades': 14, 'wins': 6, 'draws': 0, 'losses': 8, 'profit_mean': -0.003539515, 'profit_median': -0.012222, 'profit_total': -0.002480140000000001, 'profit_total_abs': -4.955321, 'max_drawdown': 0.34, 'max_drawdown_abs': -4.955321, 'holding_avg': timedelta(minutes=3402.8571428571427)},  # noqa: E501
             'results_explanation': '    14 trades. Avg profit  -0.35%. Total profit -0.00248014 BTC (  -4.96Σ%). Avg duration 3402.9 min.',  # noqa: E501
             'total_profit': -0.002480140000000001,
             'current_epoch': 5,
@@ -1875,7 +2720,7 @@ def saved_hyperopt_results():
             'loss': 0.545315889154162,
             'params_dict': {'mfi-value': 22, 'fastd-value': 43, 'adx-value': 46, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'bb_lower', 'sell-mfi-value': 87, 'sell-fastd-value': 65, 'sell-adx-value': 94, 'sell-rsi-value': 63, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 319, 'roi_t2': 556, 'roi_t3': 216, 'roi_p1': 0.06251955472249589, 'roi_p2': 0.11659519602202795, 'roi_p3': 0.0953744132197762, 'stoploss': -0.024551752215582423},  # noqa: E501
             'params_details': {'buy': {'mfi-value': 22, 'fastd-value': 43, 'adx-value': 46, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'bb_lower'}, 'sell': {'sell-mfi-value': 87, 'sell-fastd-value': 65, 'sell-adx-value': 94, 'sell-rsi-value': 63, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.2744891639643, 216: 0.17911475074452382, 772: 0.06251955472249589, 1091: 0}, 'stoploss': {'stoploss': -0.024551752215582423}},  # noqa: E501
-            'results_metrics': {'total_trades': 39, 'wins': 20, 'draws': 0, 'losses': 19, 'profit_mean': -0.0021400679487179478, 'profit_median': -0.012222, 'profit_total': -0.0041773, 'profit_total_abs': -8.346264999999997, 'holding_avg': timedelta(minutes=636.9230769230769)},  # noqa: E501
+            'results_metrics': {'total_trades': 39, 'wins': 20, 'draws': 0, 'losses': 19, 'profit_mean': -0.0021400679487179478, 'profit_median': -0.012222, 'profit_total': -0.0041773, 'profit_total_abs': -8.346264999999997, 'max_drawdown': 0.45, 'max_drawdown_abs': -4.955321, 'holding_avg': timedelta(minutes=636.9230769230769)},  # noqa: E501
             'results_explanation': '    39 trades. Avg profit  -0.21%. Total profit -0.00417730 BTC (  -8.35Σ%). Avg duration 636.9 min.',  # noqa: E501
             'total_profit': -0.0041773,
             'current_epoch': 6,
@@ -1887,7 +2732,7 @@ def saved_hyperopt_results():
             'params_details': {
                 'buy': {'mfi-value': 13, 'fastd-value': 41, 'adx-value': 21, 'rsi-value': 29, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower'}, 'sell': {'sell-mfi-value': 99, 'sell-fastd-value': 60, 'sell-adx-value': 81, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.4837436938134452, 145: 0.10853310701097472, 765: 0.0586919200378493, 1536: 0},  # noqa: E501
                 'stoploss': {'stoploss': -0.14613268022709905}},  # noqa: E501
-            'results_metrics': {'total_trades': 318, 'wins': 100, 'draws': 0, 'losses': 218, 'profit_mean': -0.0039833954716981146, 'profit_median': -0.012222, 'profit_total': -0.06339929, 'profit_total_abs': -126.67197600000004, 'holding_avg': timedelta(minutes=3140.377358490566)},  # noqa: E501
+            'results_metrics': {'total_trades': 318, 'wins': 100, 'draws': 0, 'losses': 218, 'profit_mean': -0.0039833954716981146, 'profit_median': -0.012222, 'profit_total': -0.06339929, 'profit_total_abs': -126.67197600000004, 'max_drawdown': 0.50, 'max_drawdown_abs': -200.955321, 'holding_avg': timedelta(minutes=3140.377358490566)},  # noqa: E501
             'results_explanation': '   318 trades. Avg profit  -0.40%. Total profit -0.06339929 BTC (-126.67Σ%). Avg duration 3140.4 min.',  # noqa: E501
             'total_profit': -0.06339929,
             'current_epoch': 7,
@@ -1897,7 +2742,7 @@ def saved_hyperopt_results():
             'loss': 20.0,  # noqa: E501
             'params_dict': {'mfi-value': 24, 'fastd-value': 43, 'adx-value': 33, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'sar_reversal', 'sell-mfi-value': 89, 'sell-fastd-value': 74, 'sell-adx-value': 70, 'sell-rsi-value': 70, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': False, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal', 'roi_t1': 1149, 'roi_t2': 375, 'roi_t3': 289, 'roi_p1': 0.05571820757172588, 'roi_p2': 0.0606240398618907, 'roi_p3': 0.1729012220156157, 'stoploss': -0.1588514289110401},  # noqa: E501
             'params_details': {'buy': {'mfi-value': 24, 'fastd-value': 43, 'adx-value': 33, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'sar_reversal'}, 'sell': {'sell-mfi-value': 89, 'sell-fastd-value': 74, 'sell-adx-value': 70, 'sell-rsi-value': 70, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': False, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal'}, 'roi': {0: 0.2892434694492323, 289: 0.11634224743361658, 664: 0.05571820757172588, 1813: 0}, 'stoploss': {'stoploss': -0.1588514289110401}},  # noqa: E501
-            'results_metrics': {'total_trades': 1, 'wins': 0, 'draws': 1, 'losses': 0, 'profit_mean': 0.0, 'profit_median': 0.0, 'profit_total': 0.0, 'profit_total_abs': 0.0, 'holding_avg': timedelta(minutes=5340.0)},  # noqa: E501
+            'results_metrics': {'total_trades': 1, 'wins': 0, 'draws': 1, 'losses': 0, 'profit_mean': 0.0, 'profit_median': 0.0, 'profit_total': 0.0, 'profit_total_abs': 0.0, 'max_drawdown': 0.0, 'max_drawdown_abs': 0.52, 'holding_avg': timedelta(minutes=5340.0)},  # noqa: E501
             'results_explanation': '     1 trades. Avg profit   0.00%. Total profit  0.00000000 BTC (   0.00Σ%). Avg duration 5340.0 min.',  # noqa: E501
             'total_profit': 0.0,
             'current_epoch': 8,
@@ -1907,7 +2752,7 @@ def saved_hyperopt_results():
             'loss': 2.4731817780991223,
             'params_dict': {'mfi-value': 22, 'fastd-value': 20, 'adx-value': 29, 'rsi-value': 40, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'sar_reversal', 'sell-mfi-value': 97, 'sell-fastd-value': 65, 'sell-adx-value': 81, 'sell-rsi-value': 64, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1012, 'roi_t2': 584, 'roi_t3': 422, 'roi_p1': 0.036764323603472565, 'roi_p2': 0.10335480573205287, 'roi_p3': 0.10322347377503042, 'stoploss': -0.2780610808108503},  # noqa: E501
             'params_details': {'buy': {'mfi-value': 22, 'fastd-value': 20, 'adx-value': 29, 'rsi-value': 40, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'sar_reversal'}, 'sell': {'sell-mfi-value': 97, 'sell-fastd-value': 65, 'sell-adx-value': 81, 'sell-rsi-value': 64, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.2433426031105559, 422: 0.14011912933552545, 1006: 0.036764323603472565, 2018: 0}, 'stoploss': {'stoploss': -0.2780610808108503}},  # noqa: E501
-            'results_metrics': {'total_trades': 229, 'wins': 150, 'draws': 0, 'losses': 79, 'profit_mean': -0.0038433433624454144, 'profit_median': -0.012222, 'profit_total': -0.044050070000000004, 'profit_total_abs': -88.01256299999999, 'holding_avg': timedelta(minutes=6505.676855895196)},  # noqa: E501
+            'results_metrics': {'total_trades': 229, 'wins': 150, 'draws': 0, 'losses': 79, 'profit_mean': -0.0038433433624454144, 'profit_median': -0.012222, 'profit_total': -0.044050070000000004, 'profit_total_abs': -88.01256299999999, 'max_drawdown': 0.41, 'max_drawdown_abs': -150.955321, 'holding_avg': timedelta(minutes=6505.676855895196)},  # noqa: E501
             'results_explanation': '   229 trades. Avg profit  -0.38%. Total profit -0.04405007 BTC ( -88.01Σ%). Avg duration 6505.7 min.',  # noqa: E501
             'total_profit': -0.044050070000000004,  # noqa: E501
             'current_epoch': 9,
@@ -1917,7 +2762,7 @@ def saved_hyperopt_results():
             'loss': -0.2604606005845212,  # noqa: E501
             'params_dict': {'mfi-value': 23, 'fastd-value': 24, 'adx-value': 22, 'rsi-value': 24, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 97, 'sell-fastd-value': 70, 'sell-adx-value': 64, 'sell-rsi-value': 80, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal', 'roi_t1': 792, 'roi_t2': 464, 'roi_t3': 215, 'roi_p1': 0.04594053535385903, 'roi_p2': 0.09623192684243963, 'roi_p3': 0.04428219070850663, 'stoploss': -0.16992287161634415},  # noqa: E501
             'params_details': {'buy': {'mfi-value': 23, 'fastd-value': 24, 'adx-value': 22, 'rsi-value': 24, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 97, 'sell-fastd-value': 70, 'sell-adx-value': 64, 'sell-rsi-value': 80, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal'}, 'roi': {0: 0.18645465290480528, 215: 0.14217246219629864, 679: 0.04594053535385903, 1471: 0}, 'stoploss': {'stoploss': -0.16992287161634415}},  # noqa: E501
-            'results_metrics': {'total_trades': 4, 'wins': 0, 'draws': 0, 'losses': 4, 'profit_mean': 0.001080385, 'profit_median': -0.012222, 'profit_total': 0.00021629, 'profit_total_abs': 0.432154, 'holding_avg': timedelta(minutes=2850.0)},  # noqa: E501
+            'results_metrics': {'total_trades': 4, 'wins': 0, 'draws': 0, 'losses': 4, 'profit_mean': 0.001080385, 'profit_median': -0.012222, 'profit_total': 0.00021629, 'profit_total_abs': 0.432154, 'max_drawdown': 0.13, 'max_drawdown_abs': -4.955321, 'holding_avg': timedelta(minutes=2850.0)},  # noqa: E501
             'results_explanation': '     4 trades. Avg profit   0.11%. Total profit  0.00021629 BTC (   0.43Σ%). Avg duration 2850.0 min.',  # noqa: E501
             'total_profit': 0.00021629,
             'current_epoch': 10,
@@ -1928,7 +2773,7 @@ def saved_hyperopt_results():
             'params_dict': {'mfi-value': 20, 'fastd-value': 32, 'adx-value': 49, 'rsi-value': 23, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower', 'sell-mfi-value': 75, 'sell-fastd-value': 56, 'sell-adx-value': 61, 'sell-rsi-value': 62, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 579, 'roi_t2': 614, 'roi_t3': 273, 'roi_p1': 0.05307643172744114, 'roi_p2': 0.1352282078262871, 'roi_p3': 0.1913307406325751, 'stoploss': -0.25728526022513887},  # noqa: E501
             'params_details': {'buy': {'mfi-value': 20, 'fastd-value': 32, 'adx-value': 49, 'rsi-value': 23, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower'}, 'sell': {'sell-mfi-value': 75, 'sell-fastd-value': 56, 'sell-adx-value': 61, 'sell-rsi-value': 62, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.3796353801863034, 273: 0.18830463955372825, 887: 0.05307643172744114, 1466: 0}, 'stoploss': {'stoploss': -0.25728526022513887}},  # noqa: E501
             # New Hyperopt mode!
-            'results_metrics': {'total_trades': 117, 'wins': 67, 'draws': 0, 'losses': 50, 'profit_mean': -0.012698609145299145, 'profit_median': -0.012222, 'profit_total': -0.07436117, 'profit_total_abs': -148.573727, 'holding_avg': timedelta(minutes=4282.5641025641025)},  # noqa: E501
+            'results_metrics': {'total_trades': 117, 'wins': 67, 'draws': 0, 'losses': 50, 'profit_mean': -0.012698609145299145, 'profit_median': -0.012222, 'profit_total': -0.07436117, 'profit_total_abs': -148.573727, 'max_drawdown': 0.52, 'max_drawdown_abs': -224.955321, 'holding_avg': timedelta(minutes=4282.5641025641025)},  # noqa: E501
             'results_explanation': '   117 trades. Avg profit  -1.27%. Total profit -0.07436117 BTC (-148.57Σ%). Avg duration 4282.6 min.',  # noqa: E501
             'total_profit': -0.07436117,
             'current_epoch': 11,
@@ -1938,7 +2783,7 @@ def saved_hyperopt_results():
             'loss': 100000,
             'params_dict': {'mfi-value': 10, 'fastd-value': 36, 'adx-value': 31, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'sar_reversal', 'sell-mfi-value': 80, 'sell-fastd-value': 71, 'sell-adx-value': 60, 'sell-rsi-value': 85, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1156, 'roi_t2': 581, 'roi_t3': 408, 'roi_p1': 0.06860454019988212, 'roi_p2': 0.12473718444931989, 'roi_p3': 0.2896360635226823, 'stoploss': -0.30889015124682806},  # noqa: E501
             'params_details': {'buy': {'mfi-value': 10, 'fastd-value': 36, 'adx-value': 31, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'sar_reversal'}, 'sell': {'sell-mfi-value': 80, 'sell-fastd-value': 71, 'sell-adx-value': 60, 'sell-rsi-value': 85, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.4829777881718843, 408: 0.19334172464920202, 989: 0.06860454019988212, 2145: 0}, 'stoploss': {'stoploss': -0.30889015124682806}},  # noqa: E501
-            'results_metrics': {'total_trades': 0, 'wins': 0, 'draws': 0, 'losses': 0, 'profit_mean': None, 'profit_median': None, 'profit_total': 0, 'profit_total_abs': 0.0, 'holding_avg': timedelta()},  # noqa: E501
+            'results_metrics': {'total_trades': 0, 'wins': 0, 'draws': 0, 'losses': 0, 'profit_mean': None, 'profit_median': None, 'profit_total': 0, 'profit_total_abs': 0.0, 'max_drawdown': 0.0, 'max_drawdown_abs': 0.0, 'holding_avg': timedelta()},  # noqa: E501
             'results_explanation': '     0 trades. Avg profit    nan%. Total profit  0.00000000 BTC (   0.00Σ%). Avg duration   nan min.',  # noqa: E501
             'total_profit': 0,
             'current_epoch': 12,
@@ -1957,12 +2802,12 @@ def saved_hyperopt_results():
 @pytest.fixture(scope='function')
 def limit_buy_order_usdt_open():
     return {
-        'id': 'mocked_limit_buy',
+        'id': 'mocked_limit_buy_usdt',
         'type': 'limit',
         'side': 'buy',
         'symbol': 'mocked',
         'datetime': arrow.utcnow().isoformat(),
-        'timestamp': arrow.utcnow().int_timestamp,
+        'timestamp': arrow.utcnow().int_timestamp * 1000,
         'price': 2.00,
         'amount': 30.0,
         'filled': 0.0,
@@ -1984,14 +2829,15 @@ def limit_buy_order_usdt(limit_buy_order_usdt_open):
 @pytest.fixture
 def limit_sell_order_usdt_open():
     return {
-        'id': 'mocked_limit_sell',
+        'id': 'mocked_limit_sell_usdt',
         'type': 'limit',
         'side': 'sell',
-        'pair': 'mocked',
+        'symbol': 'mocked',
         'datetime': arrow.utcnow().isoformat(),
-        'timestamp': arrow.utcnow().int_timestamp,
+        'timestamp': arrow.utcnow().int_timestamp * 1000,
         'price': 2.20,
         'amount': 30.0,
+        'cost': 66.0,
         'filled': 0.0,
         'remaining': 30.0,
         'status': 'open'
@@ -2014,6 +2860,7 @@ def market_buy_order_usdt():
         'type': 'market',
         'side': 'buy',
         'symbol': 'mocked',
+        'timestamp': arrow.utcnow().int_timestamp * 1000,
         'datetime': arrow.utcnow().isoformat(),
         'price': 2.00,
         'amount': 30.0,
@@ -2023,6 +2870,46 @@ def market_buy_order_usdt():
     }
 
 
+@pytest.fixture
+def market_buy_order_usdt_doublefee(market_buy_order_usdt):
+    order = deepcopy(market_buy_order_usdt)
+    order['fee'] = None
+    # Market orders filled with 2 trades can have fees in different currencies
+    # assuming the account runs out of BNB.
+    order['fees'] = [
+        {'cost': 0.00025125, 'currency': 'BNB'},
+        {'cost': 0.05030681, 'currency': 'USDT'},
+    ]
+    order['trades'] = [{
+        'timestamp': None,
+        'datetime': None,
+        'symbol': 'ETH/USDT',
+        'id': None,
+        'order': '123',
+        'type': 'market',
+        'side': 'sell',
+        'takerOrMaker': None,
+        'price': 2.01,
+        'amount': 25.0,
+        'cost': 50.25,
+        'fee': {'cost': 0.00025125, 'currency': 'BNB'}
+    }, {
+        'timestamp': None,
+        'datetime': None,
+        'symbol': 'ETH/USDT',
+        'id': None,
+        'order': '123',
+        'type': 'market',
+        'side': 'sell',
+        'takerOrMaker': None,
+        'price': 2.0,
+        'amount': 5,
+        'cost': 10,
+        'fee': {'cost': 0.0100306, 'currency': 'USDT'}
+    }]
+    return order
+
+
 @pytest.fixture
 def market_sell_order_usdt():
     return {
@@ -2030,6 +2917,7 @@ def market_sell_order_usdt():
         'type': 'market',
         'side': 'sell',
         'symbol': 'mocked',
+        'timestamp': arrow.utcnow().int_timestamp * 1000,
         'datetime': arrow.utcnow().isoformat(),
         'price': 2.20,
         'amount': 30.0,
@@ -2037,3 +2925,590 @@ def market_sell_order_usdt():
         'remaining': 0.0,
         'status': 'closed'
     }
+
+
+@pytest.fixture(scope='function')
+def limit_order(limit_buy_order_usdt, limit_sell_order_usdt):
+    return {
+        'buy': limit_buy_order_usdt,
+        'sell': limit_sell_order_usdt
+    }
+
+
+@pytest.fixture(scope='function')
+def market_order(market_buy_order_usdt, market_sell_order_usdt):
+    return {
+        'buy': market_buy_order_usdt,
+        'sell': market_sell_order_usdt
+    }
+
+
+@pytest.fixture(scope='function')
+def limit_order_open(limit_buy_order_usdt_open, limit_sell_order_usdt_open):
+    return {
+        'buy': limit_buy_order_usdt_open,
+        'sell': limit_sell_order_usdt_open
+    }
+
+
+@pytest.fixture(scope='function')
+def mark_ohlcv():
+    return [
+        [1630454400000, 2.77, 2.77, 2.73, 2.73, 0],
+        [1630458000000, 2.73, 2.76, 2.72, 2.74, 0],
+        [1630461600000, 2.74, 2.76, 2.74, 2.76, 0],
+        [1630465200000, 2.76, 2.76, 2.74, 2.76, 0],
+        [1630468800000, 2.76, 2.77, 2.75, 2.77, 0],
+        [1630472400000, 2.77, 2.79, 2.75, 2.78, 0],
+        [1630476000000, 2.78, 2.80, 2.77, 2.77, 0],
+        [1630479600000, 2.78, 2.79, 2.77, 2.77, 0],
+        [1630483200000, 2.77, 2.79, 2.77, 2.78, 0],
+        [1630486800000, 2.77, 2.84, 2.77, 2.84, 0],
+        [1630490400000, 2.84, 2.85, 2.81, 2.81, 0],
+        [1630494000000, 2.81, 2.83, 2.81, 2.81, 0],
+        [1630497600000, 2.81, 2.84, 2.81, 2.82, 0],
+        [1630501200000, 2.82, 2.83, 2.81, 2.81, 0],
+    ]
+
+
+@pytest.fixture(scope='function')
+def funding_rate_history_hourly():
+    return [
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": -0.000008,
+            "timestamp": 1630454400000,
+            "datetime": "2021-09-01T00:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": -0.000004,
+            "timestamp": 1630458000000,
+            "datetime": "2021-09-01T01:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": 0.000012,
+            "timestamp": 1630461600000,
+            "datetime": "2021-09-01T02:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": -0.000003,
+            "timestamp": 1630465200000,
+            "datetime": "2021-09-01T03:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": -0.000007,
+            "timestamp": 1630468800000,
+            "datetime": "2021-09-01T04:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": 0.000003,
+            "timestamp": 1630472400000,
+            "datetime": "2021-09-01T05:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": 0.000019,
+            "timestamp": 1630476000000,
+            "datetime": "2021-09-01T06:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": 0.000003,
+            "timestamp": 1630479600000,
+            "datetime": "2021-09-01T07:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": -0.000003,
+            "timestamp": 1630483200000,
+            "datetime": "2021-09-01T08:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": 0,
+            "timestamp": 1630486800000,
+            "datetime": "2021-09-01T09:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": 0.000013,
+            "timestamp": 1630490400000,
+            "datetime": "2021-09-01T10:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": 0.000077,
+            "timestamp": 1630494000000,
+            "datetime": "2021-09-01T11:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": 0.000072,
+            "timestamp": 1630497600000,
+            "datetime": "2021-09-01T12:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": 0.000097,
+            "timestamp": 1630501200000,
+            "datetime": "2021-09-01T13:00:00.000Z"
+        },
+    ]
+
+
+@pytest.fixture(scope='function')
+def funding_rate_history_octohourly():
+    return [
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": -0.000008,
+            "timestamp": 1630454400000,
+            "datetime": "2021-09-01T00:00:00.000Z"
+        },
+        {
+            "symbol": "ADA/USDT",
+            "fundingRate": -0.000003,
+            "timestamp": 1630483200000,
+            "datetime": "2021-09-01T08:00:00.000Z"
+        }
+    ]
+
+
+@pytest.fixture(scope='function')
+def leverage_tiers():
+    return {
+        "1000SHIB/USDT": [
+            {
+                'min': 0,
+                'max': 50000,
+                'mmr': 0.01,
+                'lev': 50,
+                'maintAmt': 0.0
+            },
+            {
+                'min': 50000,
+                'max': 150000,
+                'mmr': 0.025,
+                'lev': 20,
+                'maintAmt': 750.0
+            },
+            {
+                'min': 150000,
+                'max': 250000,
+                'mmr': 0.05,
+                'lev': 10,
+                'maintAmt': 4500.0
+            },
+            {
+                'min': 250000,
+                'max': 500000,
+                'mmr': 0.1,
+                'lev': 5,
+                'maintAmt': 17000.0
+            },
+            {
+                'min': 500000,
+                'max': 1000000,
+                'mmr': 0.125,
+                'lev': 4,
+                'maintAmt': 29500.0
+            },
+            {
+                'min': 1000000,
+                'max': 2000000,
+                'mmr': 0.25,
+                'lev': 2,
+                'maintAmt': 154500.0
+            },
+            {
+                'min': 2000000,
+                'max': 30000000,
+                'mmr': 0.5,
+                'lev': 1,
+                'maintAmt': 654500.0
+            },
+        ],
+        "1INCH/USDT": [
+            {
+                'min': 0,
+                'max': 5000,
+                'mmr': 0.012,
+                'lev': 50,
+                'maintAmt': 0.0
+            },
+            {
+                'min': 5000,
+                'max': 25000,
+                'mmr': 0.025,
+                'lev': 20,
+                'maintAmt': 65.0
+            },
+            {
+                'min': 25000,
+                'max': 100000,
+                'mmr': 0.05,
+                'lev': 10,
+                'maintAmt': 690.0
+            },
+            {
+                'min': 100000,
+                'max': 250000,
+                'mmr': 0.1,
+                'lev': 5,
+                'maintAmt': 5690.0
+            },
+            {
+                'min': 250000,
+                'max': 1000000,
+                'mmr': 0.125,
+                'lev': 2,
+                'maintAmt': 11940.0
+            },
+            {
+                'min': 1000000,
+                'max': 100000000,
+                'mmr': 0.5,
+                'lev': 1,
+                'maintAmt': 386940.0
+            },
+        ],
+        "AAVE/USDT": [
+            {
+                'min': 0,
+                'max': 50000,
+                'mmr': 0.01,
+                'lev': 50,
+                'maintAmt': 0.0
+            },
+            {
+                'min': 50000,
+                'max': 250000,
+                'mmr': 0.02,
+                'lev': 25,
+                'maintAmt': 500.0
+            },
+            {
+                'min': 250000,
+                'max': 1000000,
+                'mmr': 0.05,
+                'lev': 10,
+                'maintAmt': 8000.0
+            },
+            {
+                'min': 1000000,
+                'max': 2000000,
+                'mmr': 0.1,
+                'lev': 5,
+                'maintAmt': 58000.0
+            },
+            {
+                'min': 2000000,
+                'max': 5000000,
+                'mmr': 0.125,
+                'lev': 4,
+                'maintAmt': 108000.0
+            },
+            {
+                'min': 5000000,
+                'max': 10000000,
+                'mmr': 0.1665,
+                'lev': 3,
+                'maintAmt': 315500.0
+            },
+            {
+                'min': 10000000,
+                'max': 20000000,
+                'mmr': 0.25,
+                'lev': 2,
+                'maintAmt': 1150500.0
+            },
+            {
+                "min": 20000000,
+                "max": 50000000,
+                "mmr": 0.5,
+                "lev": 1,
+                "maintAmt": 6150500.0
+            }
+        ],
+        "ADA/BUSD": [
+            {
+                "min": 0,
+                "max": 100000,
+                "mmr": 0.025,
+                "lev": 20,
+                "maintAmt": 0.0
+            },
+            {
+                "min": 100000,
+                "max": 500000,
+                "mmr": 0.05,
+                "lev": 10,
+                "maintAmt": 2500.0
+            },
+            {
+                "min": 500000,
+                "max": 1000000,
+                "mmr": 0.1,
+                "lev": 5,
+                "maintAmt": 27500.0
+            },
+            {
+                "min": 1000000,
+                "max": 2000000,
+                "mmr": 0.15,
+                "lev": 3,
+                "maintAmt": 77500.0
+            },
+            {
+                "min": 2000000,
+                "max": 5000000,
+                "mmr": 0.25,
+                "lev": 2,
+                "maintAmt": 277500.0
+            },
+            {
+                "min": 5000000,
+                "max": 30000000,
+                "mmr": 0.5,
+                "lev": 1,
+                "maintAmt": 1527500.0
+            },
+        ],
+        'BNB/BUSD': [
+            {
+                "min": 0,       # stake(before leverage) = 0
+                "max": 100000,  # max stake(before leverage) = 5000
+                "mmr": 0.025,
+                "lev": 20,
+                "maintAmt": 0.0
+            },
+            {
+                "min": 100000,  # stake = 10000.0
+                "max": 500000,  # max_stake = 50000.0
+                "mmr": 0.05,
+                "lev": 10,
+                "maintAmt": 2500.0
+            },
+            {
+                "min": 500000,   # stake = 100000.0
+                "max": 1000000,  # max_stake = 200000.0
+                "mmr": 0.1,
+                "lev": 5,
+                "maintAmt": 27500.0
+            },
+            {
+                "min": 1000000,  # stake = 333333.3333333333
+                "max": 2000000,  # max_stake = 666666.6666666666
+                "mmr": 0.15,
+                "lev": 3,
+                "maintAmt": 77500.0
+            },
+            {
+                "min": 2000000,  # stake = 1000000.0
+                "max": 5000000,  # max_stake = 2500000.0
+                "mmr": 0.25,
+                "lev": 2,
+                "maintAmt": 277500.0
+            },
+            {
+                "min": 5000000,   # stake = 5000000.0
+                "max": 30000000,  # max_stake = 30000000.0
+                "mmr": 0.5,
+                "lev": 1,
+                "maintAmt": 1527500.0
+            }
+        ],
+        'BNB/USDT': [
+            {
+                "min": 0,      # stake = 0.0
+                "max": 10000,  # max_stake = 133.33333333333334
+                "mmr": 0.0065,
+                "lev": 75,
+                "maintAmt": 0.0
+            },
+            {
+                "min": 10000,  # stake = 200.0
+                "max": 50000,  # max_stake = 1000.0
+                "mmr": 0.01,
+                "lev": 50,
+                "maintAmt": 35.0
+            },
+            {
+                "min": 50000,   # stake = 2000.0
+                "max": 250000,  # max_stake = 10000.0
+                "mmr": 0.02,
+                "lev": 25,
+                "maintAmt": 535.0
+            },
+            {
+                "min": 250000,   # stake = 25000.0
+                "max": 1000000,  # max_stake = 100000.0
+                "mmr": 0.05,
+                "lev": 10,
+                "maintAmt": 8035.0
+            },
+            {
+                "min": 1000000,  # stake = 200000.0
+                "max": 2000000,  # max_stake = 400000.0
+                "mmr": 0.1,
+                "lev": 5,
+                "maintAmt": 58035.0
+            },
+            {
+                "min": 2000000,  # stake = 500000.0
+                "max": 5000000,  # max_stake = 1250000.0
+                "mmr": 0.125,
+                "lev": 4,
+                "maintAmt": 108035.0
+            },
+            {
+                "min": 5000000,   # stake = 1666666.6666666667
+                "max": 10000000,  # max_stake = 3333333.3333333335
+                "mmr": 0.15,
+                "lev": 3,
+                "maintAmt": 233035.0
+            },
+            {
+                "min": 10000000,  # stake = 5000000.0
+                "max": 20000000,  # max_stake = 10000000.0
+                "mmr": 0.25,
+                "lev": 2,
+                "maintAmt": 1233035.0
+            },
+            {
+                "min": 20000000,  # stake = 20000000.0
+                "max": 50000000,  # max_stake = 50000000.0
+                "mmr": 0.5,
+                "lev": 1,
+                "maintAmt": 6233035.0
+            },
+        ],
+        'BTC/USDT': [
+            {
+                "min": 0,      # stake = 0.0
+                "max": 50000,  # max_stake = 400.0
+                "mmr": 0.004,
+                "lev": 125,
+                "maintAmt": 0.0
+            },
+            {
+                "min": 50000,   # stake = 500.0
+                "max": 250000,  # max_stake = 2500.0
+                "mmr": 0.005,
+                "lev": 100,
+                "maintAmt": 50.0
+            },
+            {
+                "min": 250000,   # stake = 5000.0
+                "max": 1000000,  # max_stake = 20000.0
+                "mmr": 0.01,
+                "lev": 50,
+                "maintAmt": 1300.0
+            },
+            {
+                "min": 1000000,  # stake = 50000.0
+                "max": 7500000,  # max_stake = 375000.0
+                "mmr": 0.025,
+                "lev": 20,
+                "maintAmt": 16300.0
+            },
+            {
+                "min": 7500000,   # stake = 750000.0
+                "max": 40000000,  # max_stake = 4000000.0
+                "mmr": 0.05,
+                "lev": 10,
+                "maintAmt": 203800.0
+            },
+            {
+                "min": 40000000,   # stake = 8000000.0
+                "max": 100000000,  # max_stake = 20000000.0
+                "mmr": 0.1,
+                "lev": 5,
+                "maintAmt": 2203800.0
+            },
+            {
+                "min": 100000000,  # stake = 25000000.0
+                "max": 200000000,  # max_stake = 50000000.0
+                "mmr": 0.125,
+                "lev": 4,
+                "maintAmt": 4703800.0
+            },
+            {
+                "min": 200000000,  # stake = 66666666.666666664
+                "max": 400000000,  # max_stake = 133333333.33333333
+                "mmr": 0.15,
+                "lev": 3,
+                "maintAmt": 9703800.0
+            },
+            {
+                "min": 400000000,  # stake = 200000000.0
+                "max": 600000000,  # max_stake = 300000000.0
+                "mmr": 0.25,
+                "lev": 2,
+                "maintAmt": 4.97038E7
+            },
+            {
+                "min": 600000000,   # stake = 600000000.0
+                "max": 1000000000,  # max_stake = 1000000000.0
+                "mmr": 0.5,
+                "lev": 1,
+                "maintAmt": 1.997038E8
+            },
+        ],
+        "ZEC/USDT": [
+            {
+                'min': 0,
+                'max': 50000,
+                'mmr': 0.01,
+                'lev': 50,
+                'maintAmt': 0.0
+            },
+            {
+                'min': 50000,
+                'max': 150000,
+                'mmr': 0.025,
+                'lev': 20,
+                'maintAmt': 750.0
+            },
+            {
+                'min': 150000,
+                'max': 250000,
+                'mmr': 0.05,
+                'lev': 10,
+                'maintAmt': 4500.0
+            },
+            {
+                'min': 250000,
+                'max': 500000,
+                'mmr': 0.1,
+                'lev': 5,
+                'maintAmt': 17000.0
+            },
+            {
+                'min': 500000,
+                'max': 1000000,
+                'mmr': 0.125,
+                'lev': 4,
+                'maintAmt': 29500.0
+            },
+            {
+                'min': 1000000,
+                'max': 2000000,
+                'mmr': 0.25,
+                'lev': 2,
+                'maintAmt': 154500.0
+            },
+            {
+                'min': 2000000,
+                'max': 30000000,
+                'mmr': 0.5,
+                'lev': 1,
+                'maintAmt': 654500.0
+            },
+        ]
+    }
diff --git a/tests/conftest_trades.py b/tests/conftest_trades.py
index 024803be0..006eab98f 100644
--- a/tests/conftest_trades.py
+++ b/tests/conftest_trades.py
@@ -6,21 +6,34 @@ from freqtrade.persistence.models import Order, Trade
 MOCK_TRADE_COUNT = 6
 
 
-def mock_order_1():
+def entry_side(is_short: bool):
+    return "sell" if is_short else "buy"
+
+
+def exit_side(is_short: bool):
+    return "buy" if is_short else "sell"
+
+
+def direc(is_short: bool):
+    return "short" if is_short else "long"
+
+
+def mock_order_1(is_short: bool):
     return {
-        'id': '1234',
+        'id': f'1234_{direc(is_short)}',
         'symbol': 'ETH/BTC',
         'status': 'closed',
-        'side': 'buy',
+        'side': entry_side(is_short),
         'type': 'limit',
         'price': 0.123,
+        'average': 0.123,
         'amount': 123.0,
         'filled': 123.0,
         'remaining': 0.0,
     }
 
 
-def mock_trade_1(fee):
+def mock_trade_1(fee, is_short: bool):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
@@ -32,21 +45,22 @@ def mock_trade_1(fee):
         open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=17),
         open_rate=0.123,
         exchange='binance',
-        open_order_id='dry_run_buy_12345',
-        strategy='StrategyTestV2',
+        open_order_id=f'dry_run_buy_{direc(is_short)}_12345',
+        strategy='StrategyTestV3',
         timeframe=5,
+        is_short=is_short
     )
-    o = Order.parse_from_ccxt_object(mock_order_1(), 'ETH/BTC', 'buy')
+    o = Order.parse_from_ccxt_object(mock_order_1(is_short), 'ETH/BTC', entry_side(is_short))
     trade.orders.append(o)
     return trade
 
 
-def mock_order_2():
+def mock_order_2(is_short: bool):
     return {
-        'id': '1235',
+        'id': f'1235_{direc(is_short)}',
         'symbol': 'ETC/BTC',
         'status': 'closed',
-        'side': 'buy',
+        'side': entry_side(is_short),
         'type': 'limit',
         'price': 0.123,
         'amount': 123.0,
@@ -55,12 +69,12 @@ def mock_order_2():
     }
 
 
-def mock_order_2_sell():
+def mock_order_2_sell(is_short: bool):
     return {
-        'id': '12366',
+        'id': f'12366_{direc(is_short)}',
         'symbol': 'ETC/BTC',
         'status': 'closed',
-        'side': 'sell',
+        'side': exit_side(is_short),
         'type': 'limit',
         'price': 0.128,
         'amount': 123.0,
@@ -69,7 +83,7 @@ def mock_order_2_sell():
     }
 
 
-def mock_trade_2(fee):
+def mock_trade_2(fee, is_short: bool):
     """
     Closed trade...
     """
@@ -82,30 +96,32 @@ def mock_trade_2(fee):
         fee_close=fee.return_value,
         open_rate=0.123,
         close_rate=0.128,
-        close_profit=0.005,
-        close_profit_abs=0.000584127,
+        close_profit=-0.005 if is_short else 0.005,
+        close_profit_abs=-0.005584127 if is_short else 0.000584127,
         exchange='binance',
         is_open=False,
-        open_order_id='dry_run_sell_12345',
-        strategy='StrategyTestV2',
+        open_order_id=f'dry_run_sell_{direc(is_short)}_12345',
+        strategy='StrategyTestV3',
         timeframe=5,
-        sell_reason='sell_signal',
+        enter_tag='TEST1',
+        exit_reason='sell_signal',
         open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=20),
         close_date=datetime.now(tz=timezone.utc) - timedelta(minutes=2),
+        is_short=is_short
     )
-    o = Order.parse_from_ccxt_object(mock_order_2(), 'ETC/BTC', 'buy')
+    o = Order.parse_from_ccxt_object(mock_order_2(is_short), 'ETC/BTC', entry_side(is_short))
     trade.orders.append(o)
-    o = Order.parse_from_ccxt_object(mock_order_2_sell(), 'ETC/BTC', 'sell')
+    o = Order.parse_from_ccxt_object(mock_order_2_sell(is_short), 'ETC/BTC', exit_side(is_short))
     trade.orders.append(o)
     return trade
 
 
-def mock_order_3():
+def mock_order_3(is_short: bool):
     return {
-        'id': '41231a12a',
+        'id': f'41231a12a_{direc(is_short)}',
         'symbol': 'XRP/BTC',
         'status': 'closed',
-        'side': 'buy',
+        'side': entry_side(is_short),
         'type': 'limit',
         'price': 0.05,
         'amount': 123.0,
@@ -114,12 +130,12 @@ def mock_order_3():
     }
 
 
-def mock_order_3_sell():
+def mock_order_3_sell(is_short: bool):
     return {
-        'id': '41231a666a',
+        'id': f'41231a666a_{direc(is_short)}',
         'symbol': 'XRP/BTC',
         'status': 'closed',
-        'side': 'sell',
+        'side': exit_side(is_short),
         'type': 'stop_loss_limit',
         'price': 0.06,
         'average': 0.06,
@@ -129,7 +145,7 @@ def mock_order_3_sell():
     }
 
 
-def mock_trade_3(fee):
+def mock_trade_3(fee, is_short: bool):
     """
     Closed trade
     """
@@ -142,29 +158,30 @@ def mock_trade_3(fee):
         fee_close=fee.return_value,
         open_rate=0.05,
         close_rate=0.06,
-        close_profit=0.01,
-        close_profit_abs=0.000155,
+        close_profit=-0.01 if is_short else 0.01,
+        close_profit_abs=-0.001155 if is_short else 0.000155,
         exchange='binance',
         is_open=False,
-        strategy='StrategyTestV2',
+        strategy='StrategyTestV3',
         timeframe=5,
-        sell_reason='roi',
+        exit_reason='roi',
         open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=20),
         close_date=datetime.now(tz=timezone.utc),
+        is_short=is_short
     )
-    o = Order.parse_from_ccxt_object(mock_order_3(), 'XRP/BTC', 'buy')
+    o = Order.parse_from_ccxt_object(mock_order_3(is_short), 'XRP/BTC', entry_side(is_short))
     trade.orders.append(o)
-    o = Order.parse_from_ccxt_object(mock_order_3_sell(), 'XRP/BTC', 'sell')
+    o = Order.parse_from_ccxt_object(mock_order_3_sell(is_short), 'XRP/BTC', exit_side(is_short))
     trade.orders.append(o)
     return trade
 
 
-def mock_order_4():
+def mock_order_4(is_short: bool):
     return {
-        'id': 'prod_buy_12345',
+        'id': f'prod_buy_{direc(is_short)}_12345',
         'symbol': 'ETC/BTC',
         'status': 'open',
-        'side': 'buy',
+        'side': entry_side(is_short),
         'type': 'limit',
         'price': 0.123,
         'amount': 123.0,
@@ -173,7 +190,7 @@ def mock_order_4():
     }
 
 
-def mock_trade_4(fee):
+def mock_trade_4(fee, is_short: bool):
     """
     Simulate prod entry
     """
@@ -188,21 +205,22 @@ def mock_trade_4(fee):
         is_open=True,
         open_rate=0.123,
         exchange='binance',
-        open_order_id='prod_buy_12345',
-        strategy='StrategyTestV2',
+        open_order_id=f'prod_buy_{direc(is_short)}_12345',
+        strategy='StrategyTestV3',
         timeframe=5,
+        is_short=is_short
     )
-    o = Order.parse_from_ccxt_object(mock_order_4(), 'ETC/BTC', 'buy')
+    o = Order.parse_from_ccxt_object(mock_order_4(is_short), 'ETC/BTC', entry_side(is_short))
     trade.orders.append(o)
     return trade
 
 
-def mock_order_5():
+def mock_order_5(is_short: bool):
     return {
-        'id': 'prod_buy_3455',
+        'id': f'prod_buy_{direc(is_short)}_3455',
         'symbol': 'XRP/BTC',
         'status': 'closed',
-        'side': 'buy',
+        'side': entry_side(is_short),
         'type': 'limit',
         'price': 0.123,
         'amount': 123.0,
@@ -211,12 +229,12 @@ def mock_order_5():
     }
 
 
-def mock_order_5_stoploss():
+def mock_order_5_stoploss(is_short: bool):
     return {
-        'id': 'prod_stoploss_3455',
+        'id': f'prod_stoploss_{direc(is_short)}_3455',
         'symbol': 'XRP/BTC',
         'status': 'open',
-        'side': 'sell',
+        'side': exit_side(is_short),
         'type': 'stop_loss_limit',
         'price': 0.123,
         'amount': 123.0,
@@ -225,7 +243,7 @@ def mock_order_5_stoploss():
     }
 
 
-def mock_trade_5(fee):
+def mock_trade_5(fee, is_short: bool):
     """
     Simulate prod entry with stoploss
     """
@@ -241,22 +259,24 @@ def mock_trade_5(fee):
         open_rate=0.123,
         exchange='binance',
         strategy='SampleStrategy',
-        stoploss_order_id='prod_stoploss_3455',
+        enter_tag='TEST1',
+        stoploss_order_id=f'prod_stoploss_{direc(is_short)}_3455',
         timeframe=5,
+        is_short=is_short
     )
-    o = Order.parse_from_ccxt_object(mock_order_5(), 'XRP/BTC', 'buy')
+    o = Order.parse_from_ccxt_object(mock_order_5(is_short), 'XRP/BTC', entry_side(is_short))
     trade.orders.append(o)
-    o = Order.parse_from_ccxt_object(mock_order_5_stoploss(), 'XRP/BTC', 'stoploss')
+    o = Order.parse_from_ccxt_object(mock_order_5_stoploss(is_short), 'XRP/BTC', 'stoploss')
     trade.orders.append(o)
     return trade
 
 
-def mock_order_6():
+def mock_order_6(is_short: bool):
     return {
-        'id': 'prod_buy_6',
+        'id': f'prod_buy_{direc(is_short)}_6',
         'symbol': 'LTC/BTC',
         'status': 'closed',
-        'side': 'buy',
+        'side': entry_side(is_short),
         'type': 'limit',
         'price': 0.15,
         'amount': 2.0,
@@ -265,23 +285,23 @@ def mock_order_6():
     }
 
 
-def mock_order_6_sell():
+def mock_order_6_sell(is_short: bool):
     return {
-        'id': 'prod_sell_6',
+        'id': f'prod_sell_{direc(is_short)}_6',
         'symbol': 'LTC/BTC',
         'status': 'open',
-        'side': 'sell',
+        'side': exit_side(is_short),
         'type': 'limit',
-        'price': 0.20,
+        'price': 0.15 if is_short else 0.20,
         'amount': 2.0,
         'filled': 0.0,
         'remaining': 2.0,
     }
 
 
-def mock_trade_6(fee):
+def mock_trade_6(fee, is_short: bool):
     """
-    Simulate prod entry with open sell order
+    Simulate prod entry with open exit order
     """
     trade = Trade(
         pair='LTC/BTC',
@@ -295,11 +315,188 @@ def mock_trade_6(fee):
         open_rate=0.15,
         exchange='binance',
         strategy='SampleStrategy',
-        open_order_id="prod_sell_6",
+        enter_tag='TEST2',
+        open_order_id=f"prod_sell_{direc(is_short)}_6",
         timeframe=5,
+        is_short=is_short
     )
-    o = Order.parse_from_ccxt_object(mock_order_6(), 'LTC/BTC', 'buy')
+    o = Order.parse_from_ccxt_object(mock_order_6(is_short), 'LTC/BTC', entry_side(is_short))
     trade.orders.append(o)
-    o = Order.parse_from_ccxt_object(mock_order_6_sell(), 'LTC/BTC', 'sell')
+    o = Order.parse_from_ccxt_object(mock_order_6_sell(is_short), 'LTC/BTC', exit_side(is_short))
+    trade.orders.append(o)
+    return trade
+
+
+def short_order():
+    return {
+        'id': '1236',
+        'symbol': 'ETC/BTC',
+        'status': 'closed',
+        'side': 'sell',
+        'type': 'limit',
+        'price': 0.123,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+    }
+
+
+def exit_short_order():
+    return {
+        'id': '12367',
+        'symbol': 'ETC/BTC',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 0.128,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+    }
+
+
+def short_trade(fee):
+    """
+        10 minute short limit trade on binance
+
+        Short trade
+        fee: 0.25% base
+        interest_rate: 0.05% per day
+        open_rate: 0.123 base
+        close_rate: 0.128 base
+        amount: 123.0 crypto
+        stake_amount: 15.129 base
+        borrowed: 123.0  crypto
+        time-periods: 10 minutes(rounds up to 1/24 time-period of 1 day)
+        interest: borrowed * interest_rate * time-periods
+                    = 123.0 * 0.0005 * 1/24 = 0.0025625 crypto
+        open_value: (amount * open_rate) - (amount * open_rate * fee)
+            = (123 * 0.123) - (123 * 0.123 * 0.0025)
+            = 15.091177499999999
+        amount_closed: amount + interest = 123 + 0.0025625 = 123.0025625
+        close_value: (amount_closed * close_rate) + (amount_closed * close_rate * fee)
+            = (123.0025625 * 0.128) + (123.0025625 * 0.128 * 0.0025)
+            = 15.78368882
+        total_profit = open_value - close_value
+            = 15.091177499999999 - 15.78368882
+            = -0.6925113200000013
+        total_profit_percentage = total_profit / stake_amount
+            = -0.6925113200000013 / 15.129
+            = -0.04577376693766946
+
+    """
+    trade = Trade(
+        pair='ETC/BTC',
+        stake_amount=15.129,
+        amount=123.0,
+        amount_requested=123.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.123,
+        # close_rate=0.128,
+        # close_profit=-0.04577376693766946,
+        # close_profit_abs=-0.6925113200000013,
+        exchange='binance',
+        is_open=True,
+        open_order_id='dry_run_exit_short_12345',
+        strategy='DefaultStrategy',
+        timeframe=5,
+        exit_reason='sell_signal',
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=20),
+        # close_date=datetime.now(tz=timezone.utc) - timedelta(minutes=2),
+        is_short=True
+    )
+    o = Order.parse_from_ccxt_object(short_order(), 'ETC/BTC', 'sell')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(exit_short_order(), 'ETC/BTC', 'sell')
+    trade.orders.append(o)
+    return trade
+
+
+def leverage_order():
+    return {
+        'id': '1237',
+        'symbol': 'DOGE/BTC',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 0.123,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+        'leverage': 5.0
+    }
+
+
+def leverage_order_sell():
+    return {
+        'id': '12368',
+        'symbol': 'DOGE/BTC',
+        'status': 'closed',
+        'side': 'sell',
+        'type': 'limit',
+        'price': 0.128,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+        'leverage': 5.0
+    }
+
+
+def leverage_trade(fee):
+    """
+    5 hour short limit trade on kraken
+
+        Short trade
+        fee: 0.25% base
+        interest_rate: 0.05% per day
+        open_rate: 0.123 base
+        close_rate: 0.128 base
+        amount: 615 crypto
+        stake_amount: 15.129 base
+        borrowed: 60.516  base
+        leverage: 5
+        hours: 5
+        interest: borrowed * interest_rate * ceil(1 + hours/4)
+                    = 60.516 * 0.0005 * ceil(1 + 5/4) = 0.090774 base
+        open_value: (amount * open_rate) + (amount * open_rate * fee)
+            = (615.0 * 0.123) + (615.0 * 0.123 * 0.0025)
+            = 75.83411249999999
+
+        close_value: (amount_closed * close_rate) - (amount_closed * close_rate * fee) - interest
+            = (615.0 * 0.128) - (615.0 * 0.128 * 0.0025) - 0.090774
+            = 78.432426
+        total_profit = close_value - open_value
+            = 78.432426 - 75.83411249999999
+            = 2.5983135000000175
+        total_profit_percentage = ((close_value/open_value)-1) * leverage
+            = ((78.432426/75.83411249999999)-1) * 5
+            = 0.1713156134055116
+    """
+    trade = Trade(
+        pair='DOGE/BTC',
+        stake_amount=15.129,
+        amount=615.0,
+        leverage=5.0,
+        amount_requested=615.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.123,
+        close_rate=0.128,
+        close_profit=0.1713156134055116,
+        close_profit_abs=2.5983135000000175,
+        exchange='kraken',
+        is_open=False,
+        open_order_id='dry_run_leverage_buy_12368',
+        strategy='DefaultStrategy',
+        timeframe=5,
+        exit_reason='sell_signal',
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=300),
+        close_date=datetime.now(tz=timezone.utc),
+        interest_rate=0.0005
+    )
+    o = Order.parse_from_ccxt_object(leverage_order(), 'DOGE/BTC', 'sell')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(leverage_order_sell(), 'DOGE/BTC', 'sell')
     trade.orders.append(o)
     return trade
diff --git a/tests/conftest_trades_usdt.py b/tests/conftest_trades_usdt.py
new file mode 100644
index 000000000..59e7f0457
--- /dev/null
+++ b/tests/conftest_trades_usdt.py
@@ -0,0 +1,363 @@
+from datetime import datetime, timedelta, timezone
+
+from freqtrade.persistence.models import Order, Trade
+
+
+MOCK_TRADE_COUNT = 6
+
+
+def mock_order_usdt_1():
+    return {
+        'id': '1234',
+        'symbol': 'ADA/USDT',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 2.0,
+        'amount': 10.0,
+        'filled': 10.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_trade_usdt_1(fee):
+    trade = Trade(
+        pair='ADA/USDT',
+        stake_amount=20.0,
+        amount=10.0,
+        amount_requested=10.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        is_open=True,
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=17),
+        open_rate=2.0,
+        exchange='binance',
+        open_order_id='dry_run_buy_12345',
+        strategy='StrategyTestV2',
+        timeframe=5,
+    )
+    o = Order.parse_from_ccxt_object(mock_order_usdt_1(), 'ADA/USDT', 'buy')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_usdt_2():
+    return {
+        'id': '1235',
+        'symbol': 'ETC/USDT',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 2.0,
+        'amount': 100.0,
+        'filled': 100.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_order_usdt_2_sell():
+    return {
+        'id': '12366',
+        'symbol': 'ETC/USDT',
+        'status': 'closed',
+        'side': 'sell',
+        'type': 'limit',
+        'price': 2.05,
+        'amount': 100.0,
+        'filled': 100.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_trade_usdt_2(fee):
+    """
+    Closed trade...
+    """
+    trade = Trade(
+        pair='ETC/USDT',
+        stake_amount=200.0,
+        amount=100.0,
+        amount_requested=100.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=2.0,
+        close_rate=2.05,
+        close_profit=5.0,
+        close_profit_abs=3.9875,
+        exchange='binance',
+        is_open=False,
+        open_order_id='dry_run_sell_12345',
+        strategy='StrategyTestV2',
+        timeframe=5,
+        exit_reason='sell_signal',
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=20),
+        close_date=datetime.now(tz=timezone.utc) - timedelta(minutes=2),
+    )
+    o = Order.parse_from_ccxt_object(mock_order_usdt_2(), 'ETC/USDT', 'buy')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(mock_order_usdt_2_sell(), 'ETC/USDT', 'sell')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_usdt_3():
+    return {
+        'id': '41231a12a',
+        'symbol': 'XRP/USDT',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 1.0,
+        'amount': 30.0,
+        'filled': 30.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_order_usdt_3_sell():
+    return {
+        'id': '41231a666a',
+        'symbol': 'XRP/USDT',
+        'status': 'closed',
+        'side': 'sell',
+        'type': 'stop_loss_limit',
+        'price': 1.1,
+        'average': 1.1,
+        'amount': 30.0,
+        'filled': 30.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_trade_usdt_3(fee):
+    """
+    Closed trade
+    """
+    trade = Trade(
+        pair='XRP/USDT',
+        stake_amount=30.0,
+        amount=30.0,
+        amount_requested=30.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=1.0,
+        close_rate=1.1,
+        close_profit=10.0,
+        close_profit_abs=9.8425,
+        exchange='binance',
+        is_open=False,
+        strategy='StrategyTestV2',
+        timeframe=5,
+        exit_reason='roi',
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=20),
+        close_date=datetime.now(tz=timezone.utc),
+    )
+    o = Order.parse_from_ccxt_object(mock_order_usdt_3(), 'XRP/USDT', 'buy')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(mock_order_usdt_3_sell(), 'XRP/USDT', 'sell')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_usdt_4():
+    return {
+        'id': 'prod_buy_12345',
+        'symbol': 'ETC/USDT',
+        'status': 'open',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 2.0,
+        'amount': 10.0,
+        'filled': 0.0,
+        'remaining': 30.0,
+    }
+
+
+def mock_trade_usdt_4(fee):
+    """
+    Simulate prod entry
+    """
+    trade = Trade(
+        pair='ETC/USDT',
+        stake_amount=20.0,
+        amount=10.0,
+        amount_requested=10.01,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=14),
+        is_open=True,
+        open_rate=2.0,
+        exchange='binance',
+        open_order_id='prod_buy_12345',
+        strategy='StrategyTestV2',
+        timeframe=5,
+    )
+    o = Order.parse_from_ccxt_object(mock_order_usdt_4(), 'ETC/USDT', 'buy')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_usdt_5():
+    return {
+        'id': 'prod_buy_3455',
+        'symbol': 'XRP/USDT',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 2.0,
+        'amount': 10.0,
+        'filled': 10.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_order_usdt_5_stoploss():
+    return {
+        'id': 'prod_stoploss_3455',
+        'symbol': 'XRP/USDT',
+        'status': 'open',
+        'side': 'sell',
+        'type': 'stop_loss_limit',
+        'price': 2.0,
+        'amount': 10.0,
+        'filled': 0.0,
+        'remaining': 30.0,
+    }
+
+
+def mock_trade_usdt_5(fee):
+    """
+    Simulate prod entry with stoploss
+    """
+    trade = Trade(
+        pair='XRP/USDT',
+        stake_amount=20.0,
+        amount=10.0,
+        amount_requested=10.01,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=12),
+        is_open=True,
+        open_rate=2.0,
+        exchange='binance',
+        strategy='SampleStrategy',
+        stoploss_order_id='prod_stoploss_3455',
+        timeframe=5,
+    )
+    o = Order.parse_from_ccxt_object(mock_order_usdt_5(), 'XRP/USDT', 'buy')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(mock_order_usdt_5_stoploss(), 'XRP/USDT', 'stoploss')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_usdt_6():
+    return {
+        'id': 'prod_buy_6',
+        'symbol': 'LTC/USDT',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 10.0,
+        'amount': 2.0,
+        'filled': 2.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_order_usdt_6_sell():
+    return {
+        'id': 'prod_sell_6',
+        'symbol': 'LTC/USDT',
+        'status': 'open',
+        'side': 'sell',
+        'type': 'limit',
+        'price': 12.0,
+        'amount': 2.0,
+        'filled': 0.0,
+        'remaining': 2.0,
+    }
+
+
+def mock_trade_usdt_6(fee):
+    """
+    Simulate prod entry with open sell order
+    """
+    trade = Trade(
+        pair='LTC/USDT',
+        stake_amount=20.0,
+        amount=2.0,
+        amount_requested=2.0,
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=5),
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        is_open=True,
+        open_rate=10.0,
+        exchange='binance',
+        strategy='SampleStrategy',
+        open_order_id="prod_sell_6",
+        timeframe=5,
+    )
+    o = Order.parse_from_ccxt_object(mock_order_usdt_6(), 'LTC/USDT', 'buy')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(mock_order_usdt_6_sell(), 'LTC/USDT', 'sell')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_usdt_7():
+    return {
+        'id': 'prod_buy_7',
+        'symbol': 'LTC/USDT',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 10.0,
+        'amount': 2.0,
+        'filled': 2.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_order_usdt_7_sell():
+    return {
+        'id': 'prod_sell_7',
+        'symbol': 'LTC/USDT',
+        'status': 'closed',
+        'side': 'sell',
+        'type': 'limit',
+        'price': 8.0,
+        'amount': 2.0,
+        'filled': 2.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_trade_usdt_7(fee):
+    """
+    Simulate prod entry with open sell order
+    """
+    trade = Trade(
+        pair='LTC/USDT',
+        stake_amount=20.0,
+        amount=2.0,
+        amount_requested=2.0,
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=20),
+        close_date=datetime.now(tz=timezone.utc) - timedelta(minutes=5),
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        is_open=False,
+        open_rate=10.0,
+        close_rate=8.0,
+        close_profit=-0.2,
+        close_profit_abs=-4.0,
+        exchange='binance',
+        strategy='SampleStrategy',
+        open_order_id="prod_sell_6",
+        timeframe=5,
+    )
+    o = Order.parse_from_ccxt_object(mock_order_usdt_7(), 'LTC/USDT', 'buy')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(mock_order_usdt_7_sell(), 'LTC/USDT', 'sell')
+    trade.orders.append(o)
+    return trade
diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py
index 1dcd04a80..2b53e4900 100644
--- a/tests/data/test_btanalysis.py
+++ b/tests/data/test_btanalysis.py
@@ -8,15 +8,16 @@ from pandas import DataFrame, DateOffset, Timestamp, to_datetime
 
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import LAST_BT_RESULT_FN
-from freqtrade.data.btanalysis import (BT_DATA_COLUMNS, BT_DATA_COLUMNS_MID, BT_DATA_COLUMNS_OLD,
-                                       analyze_trade_parallelism, calculate_csum,
+from freqtrade.data.btanalysis import (BT_DATA_COLUMNS, analyze_trade_parallelism, calculate_csum,
                                        calculate_market_change, calculate_max_drawdown,
-                                       combine_dataframes_with_mean, create_cum_profit,
-                                       extract_trades_of_period, get_latest_backtest_filename,
-                                       get_latest_hyperopt_file, load_backtest_data, load_trades,
+                                       calculate_underwater, combine_dataframes_with_mean,
+                                       create_cum_profit, extract_trades_of_period,
+                                       get_latest_backtest_filename, get_latest_hyperopt_file,
+                                       load_backtest_data, load_backtest_metadata, load_trades,
                                        load_trades_from_db)
 from freqtrade.data.history import load_data, load_pair_history
-from tests.conftest import create_mock_trades
+from freqtrade.exceptions import OperationalException
+from tests.conftest import CURRENT_TEST_STRATEGY, create_mock_trades
 from tests.conftest_trades import MOCK_TRADE_COUNT
 
 
@@ -26,21 +27,22 @@ def test_get_latest_backtest_filename(testdatadir, mocker):
 
     with pytest.raises(ValueError,
                        match=r"Directory .* does not seem to contain .*"):
-        get_latest_backtest_filename(testdatadir.parent)
+        get_latest_backtest_filename(testdatadir)
 
-    res = get_latest_backtest_filename(testdatadir)
+    testdir_bt = testdatadir / "backtest_results"
+    res = get_latest_backtest_filename(testdir_bt)
     assert res == 'backtest-result_new.json'
 
-    res = get_latest_backtest_filename(str(testdatadir))
+    res = get_latest_backtest_filename(str(testdir_bt))
     assert res == 'backtest-result_new.json'
 
     mocker.patch("freqtrade.data.btanalysis.json_load", return_value={})
 
     with pytest.raises(ValueError, match=r"Invalid '.last_result.json' format."):
-        get_latest_backtest_filename(testdatadir)
+        get_latest_backtest_filename(testdir_bt)
 
 
-def test_get_latest_hyperopt_file(testdatadir, mocker):
+def test_get_latest_hyperopt_file(testdatadir):
     res = get_latest_hyperopt_file(testdatadir / 'does_not_exist', 'testfile.pickle')
     assert res == testdatadir / 'does_not_exist/testfile.pickle'
 
@@ -50,29 +52,40 @@ def test_get_latest_hyperopt_file(testdatadir, mocker):
     res = get_latest_hyperopt_file(str(testdatadir.parent))
     assert res == testdatadir.parent / "hyperopt_results.pickle"
 
+    # Test with absolute path
+    with pytest.raises(
+        OperationalException,
+            match="--hyperopt-filename expects only the filename, not an absolute path."):
+        get_latest_hyperopt_file(str(testdatadir.parent), str(testdatadir.parent))
 
-def test_load_backtest_data_old_format(testdatadir):
 
-    filename = testdatadir / "backtest-result_test.json"
-    bt_data = load_backtest_data(filename)
-    assert isinstance(bt_data, DataFrame)
-    assert list(bt_data.columns) == BT_DATA_COLUMNS_OLD + ['profit_abs', 'profit_ratio']
-    assert len(bt_data) == 179
+def test_load_backtest_metadata(mocker, testdatadir):
+    res = load_backtest_metadata(testdatadir / 'nonexistant.file.json')
+    assert res == {}
 
-    # Test loading from string (must yield same result)
-    bt_data2 = load_backtest_data(str(filename))
-    assert bt_data.equals(bt_data2)
+    mocker.patch('freqtrade.data.btanalysis.get_backtest_metadata_filename')
+    mocker.patch('freqtrade.data.btanalysis.json_load', side_effect=Exception())
+    with pytest.raises(OperationalException,
+                       match=r"Unexpected error.*loading backtest metadata\."):
+        load_backtest_metadata(testdatadir / 'nonexistant.file.json')
 
-    with pytest.raises(ValueError, match=r"File .* does not exist\."):
-        load_backtest_data(str("filename") + "nofile")
+
+def test_load_backtest_data_old_format(testdatadir, mocker):
+
+    filename = testdatadir / "backtest-result_test222.json"
+    mocker.patch('freqtrade.data.btanalysis.load_backtest_stats', return_value=[])
+
+    with pytest.raises(OperationalException,
+                       match=r"Backtest-results with only trades data are no longer supported."):
+        load_backtest_data(filename)
 
 
 def test_load_backtest_data_new_format(testdatadir):
 
-    filename = testdatadir / "backtest-result_new.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
     assert isinstance(bt_data, DataFrame)
-    assert set(bt_data.columns) == set(BT_DATA_COLUMNS_MID)
+    assert set(bt_data.columns) == set(BT_DATA_COLUMNS + ['close_timestamp', 'open_timestamp'])
     assert len(bt_data) == 179
 
     # Test loading from string (must yield same result)
@@ -80,23 +93,24 @@ def test_load_backtest_data_new_format(testdatadir):
     assert bt_data.equals(bt_data2)
 
     # Test loading from folder (must yield same result)
-    bt_data3 = load_backtest_data(testdatadir)
+    bt_data3 = load_backtest_data(testdatadir / "backtest_results")
     assert bt_data.equals(bt_data3)
 
     with pytest.raises(ValueError, match=r"File .* does not exist\."):
         load_backtest_data(str("filename") + "nofile")
 
     with pytest.raises(ValueError, match=r"Unknown dataformat."):
-        load_backtest_data(testdatadir / LAST_BT_RESULT_FN)
+        load_backtest_data(testdatadir / "backtest_results" / LAST_BT_RESULT_FN)
 
 
 def test_load_backtest_data_multi(testdatadir):
 
-    filename = testdatadir / "backtest-result_multistrat.json"
+    filename = testdatadir / "backtest_results/backtest-result_multistrat.json"
     for strategy in ('StrategyTestV2', 'TestStrategy'):
         bt_data = load_backtest_data(filename, strategy=strategy)
         assert isinstance(bt_data, DataFrame)
-        assert set(bt_data.columns) == set(BT_DATA_COLUMNS_MID)
+        assert set(bt_data.columns) == set(
+            BT_DATA_COLUMNS + ['close_timestamp', 'open_timestamp'])
         assert len(bt_data) == 179
 
         # Test loading from string (must yield same result)
@@ -111,9 +125,10 @@ def test_load_backtest_data_multi(testdatadir):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_load_trades_from_db(default_conf, fee, mocker):
+@pytest.mark.parametrize('is_short', [False, True])
+def test_load_trades_from_db(default_conf, fee, is_short, mocker):
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short)
     # remove init so it does not init again
     init_mock = mocker.patch('freqtrade.data.btanalysis.init_db', MagicMock())
 
@@ -128,7 +143,7 @@ def test_load_trades_from_db(default_conf, fee, mocker):
     for col in BT_DATA_COLUMNS:
         if col not in ['index', 'open_at_end']:
             assert col in trades.columns
-    trades = load_trades_from_db(db_url=default_conf['db_url'], strategy='StrategyTestV2')
+    trades = load_trades_from_db(db_url=default_conf['db_url'], strategy=CURRENT_TEST_STRATEGY)
     assert len(trades) == 4
     trades = load_trades_from_db(db_url=default_conf['db_url'], strategy='NoneStrategy')
     assert len(trades) == 0
@@ -167,8 +182,8 @@ def test_extract_trades_of_period(testdatadir):
     assert trades1.iloc[-1].close_date == Arrow(2017, 11, 14, 15, 25, 0).datetime
 
 
-def test_analyze_trade_parallelism(default_conf, mocker, testdatadir):
-    filename = testdatadir / "backtest-result_test.json"
+def test_analyze_trade_parallelism(testdatadir):
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
 
     res = analyze_trade_parallelism(bt_data, "5m")
@@ -186,7 +201,7 @@ def test_load_trades(default_conf, mocker):
                 db_url=default_conf.get('db_url'),
                 exportfilename=default_conf.get('exportfilename'),
                 no_trades=False,
-                strategy="StrategyTestV2",
+                strategy=CURRENT_TEST_STRATEGY,
                 )
 
     assert db_mock.call_count == 1
@@ -234,8 +249,15 @@ def test_combine_dataframes_with_mean(testdatadir):
     assert "mean" in df.columns
 
 
+def test_combine_dataframes_with_mean_no_data(testdatadir):
+    pairs = ["ETH/BTC", "ADA/BTC"]
+    data = load_data(datadir=testdatadir, pairs=pairs, timeframe='6m')
+    with pytest.raises(ValueError, match=r"No objects to concatenate"):
+        combine_dataframes_with_mean(data)
+
+
 def test_create_cum_profit(testdatadir):
-    filename = testdatadir / "backtest-result_test.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
     timerange = TimeRange.parse_timerange("20180110-20180112")
 
@@ -251,7 +273,7 @@ def test_create_cum_profit(testdatadir):
 
 
 def test_create_cum_profit1(testdatadir):
-    filename = testdatadir / "backtest-result_test.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
     # Move close-time to "off" the candle, to make sure the logic still works
     bt_data.loc[:, 'close_date'] = bt_data.loc[:, 'close_date'] + DateOffset(seconds=20)
@@ -273,23 +295,31 @@ def test_create_cum_profit1(testdatadir):
 
 
 def test_calculate_max_drawdown(testdatadir):
-    filename = testdatadir / "backtest-result_test.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
-    drawdown, hdate, lowdate, hval, lval = calculate_max_drawdown(bt_data)
+    _, hdate, lowdate, hval, lval, drawdown = calculate_max_drawdown(
+        bt_data, value_col="profit_abs")
     assert isinstance(drawdown, float)
-    assert pytest.approx(drawdown) == 0.21142322
+    assert pytest.approx(drawdown) == 0.12071099
     assert isinstance(hdate, Timestamp)
     assert isinstance(lowdate, Timestamp)
     assert isinstance(hval, float)
     assert isinstance(lval, float)
-    assert hdate == Timestamp('2018-01-24 14:25:00', tz='UTC')
-    assert lowdate == Timestamp('2018-01-30 04:45:00', tz='UTC')
+    assert hdate == Timestamp('2018-01-25 01:30:00', tz='UTC')
+    assert lowdate == Timestamp('2018-01-25 03:50:00', tz='UTC')
+
+    underwater = calculate_underwater(bt_data)
+    assert isinstance(underwater, DataFrame)
+
     with pytest.raises(ValueError, match='Trade dataframe empty.'):
-        drawdown, hdate, lowdate, hval, lval = calculate_max_drawdown(DataFrame())
+        calculate_max_drawdown(DataFrame())
+
+    with pytest.raises(ValueError, match='Trade dataframe empty.'):
+        calculate_underwater(DataFrame())
 
 
 def test_calculate_csum(testdatadir):
-    filename = testdatadir / "backtest-result_test.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
     csum_min, csum_max = calculate_csum(bt_data)
 
@@ -317,12 +347,13 @@ def test_calculate_max_drawdown2():
     # sort by profit and reset index
     df = df.sort_values('profit').reset_index(drop=True)
     df1 = df.copy()
-    drawdown, hdate, ldate, hval, lval = calculate_max_drawdown(
+    drawdown, hdate, ldate, hval, lval, drawdown_rel = calculate_max_drawdown(
         df, date_col='open_date', value_col='profit')
     # Ensure df has not been altered.
     assert df.equals(df1)
 
     assert isinstance(drawdown, float)
+    assert isinstance(drawdown_rel, float)
     # High must be before low
     assert hdate < ldate
     # High value must be higher than low value
diff --git a/tests/data/test_converter.py b/tests/data/test_converter.py
index 6c95a9f18..c6b0059a2 100644
--- a/tests/data/test_converter.py
+++ b/tests/data/test_converter.py
@@ -12,6 +12,8 @@ from freqtrade.data.converter import (convert_ohlcv_format, convert_trades_forma
                                       trades_to_ohlcv, trim_dataframe)
 from freqtrade.data.history import (get_timerange, load_data, load_pair_history,
                                     validate_backtest_data)
+from freqtrade.data.history.idatahandler import IDataHandler
+from freqtrade.enums import CandleType
 from tests.conftest import log_has, log_has_re
 from tests.data.test_history import _clean_test_file
 
@@ -75,7 +77,8 @@ def test_ohlcv_fill_up_missing_data(testdatadir, caplog):
 
 def test_ohlcv_fill_up_missing_data2(caplog):
     timeframe = '5m'
-    ticks = [[
+    ticks = [
+        [
             1511686200000,  # 8:50:00
             8.794e-05,  # open
             8.948e-05,  # high
@@ -106,7 +109,7 @@ def test_ohlcv_fill_up_missing_data2(caplog):
             8.895e-05,
             8.817e-05,
             123551
-    ]
+        ]
     ]
 
     # Generate test-data without filling missing
@@ -133,7 +136,8 @@ def test_ohlcv_fill_up_missing_data2(caplog):
 
 def test_ohlcv_drop_incomplete(caplog):
     timeframe = '1d'
-    ticks = [[
+    ticks = [
+        [
             1559750400000,  # 2019-06-04
             8.794e-05,  # open
             8.948e-05,  # high
@@ -164,7 +168,7 @@ def test_ohlcv_drop_incomplete(caplog):
             8.895e-05,
             8.817e-05,
             123551
-     ]
+        ]
     ]
     caplog.set_level(logging.DEBUG)
     data = ohlcv_to_dataframe(ticks, timeframe, pair="UNITTEST/BTC",
@@ -287,42 +291,56 @@ def test_convert_trades_format(default_conf, testdatadir, tmpdir):
             file['new'].unlink()
 
 
-def test_convert_ohlcv_format(default_conf, testdatadir, tmpdir):
+@pytest.mark.parametrize('file_base,candletype', [
+    (['XRP_ETH-5m', 'XRP_ETH-1m'], CandleType.SPOT),
+    (['UNITTEST_USDT-1h-mark', 'XRP_USDT-1h-mark'], CandleType.MARK),
+    (['XRP_USDT-1h-futures'], CandleType.FUTURES),
+])
+def test_convert_ohlcv_format(default_conf, testdatadir, tmpdir, file_base, candletype):
     tmpdir1 = Path(tmpdir)
+    prependix = '' if candletype == CandleType.SPOT else 'futures/'
+    files_orig = []
+    files_temp = []
+    files_new = []
+    for file in file_base:
+        file_orig = testdatadir / f"{prependix}{file}.json"
+        file_temp = tmpdir1 / f"{prependix}{file}.json"
+        file_new = tmpdir1 / f"{prependix}{file}.json.gz"
+        IDataHandler.create_dir_if_needed(file_temp)
+        copyfile(file_orig, file_temp)
 
-    file1_orig = testdatadir / "XRP_ETH-5m.json"
-    file1 = tmpdir1 / "XRP_ETH-5m.json"
-    file1_new = tmpdir1 / "XRP_ETH-5m.json.gz"
-    file2_orig = testdatadir / "XRP_ETH-1m.json"
-    file2 = tmpdir1 / "XRP_ETH-1m.json"
-    file2_new = tmpdir1 / "XRP_ETH-1m.json.gz"
-
-    copyfile(file1_orig, file1)
-    copyfile(file2_orig, file2)
+        files_orig.append(file_orig)
+        files_temp.append(file_temp)
+        files_new.append(file_new)
 
     default_conf['datadir'] = tmpdir1
-    default_conf['pairs'] = ['XRP_ETH']
-    default_conf['timeframes'] = ['1m', '5m']
+    default_conf['pairs'] = ['XRP_ETH', 'XRP_USDT', 'UNITTEST_USDT']
+    default_conf['timeframes'] = ['1m', '5m', '1h']
 
-    assert not file1_new.exists()
-    assert not file2_new.exists()
+    assert not file_new.exists()
 
-    convert_ohlcv_format(default_conf, convert_from='json',
-                         convert_to='jsongz', erase=False)
-
-    assert file1_new.exists()
-    assert file2_new.exists()
-    assert file1.exists()
-    assert file2.exists()
+    convert_ohlcv_format(
+        default_conf,
+        convert_from='json',
+        convert_to='jsongz',
+        erase=False,
+        candle_type=candletype
+    )
+    for file in (files_temp + files_new):
+        assert file.exists()
 
     # Remove original files
-    file1.unlink()
-    file2.unlink()
+    for file in (files_temp):
+        file.unlink()
     # Convert back
-    convert_ohlcv_format(default_conf, convert_from='jsongz',
-                         convert_to='json', erase=True)
-
-    assert file1.exists()
-    assert file2.exists()
-    assert not file1_new.exists()
-    assert not file2_new.exists()
+    convert_ohlcv_format(
+        default_conf,
+        convert_from='jsongz',
+        convert_to='json',
+        erase=True,
+        candle_type=candletype
+    )
+    for file in (files_temp):
+        assert file.exists()
+    for file in (files_new):
+        assert not file.exists()
diff --git a/tests/data/test_dataprovider.py b/tests/data/test_dataprovider.py
index 0f42068c1..93f82de5d 100644
--- a/tests/data/test_dataprovider.py
+++ b/tests/data/test_dataprovider.py
@@ -5,40 +5,49 @@ import pytest
 from pandas import DataFrame
 
 from freqtrade.data.dataprovider import DataProvider
-from freqtrade.enums import RunMode
+from freqtrade.enums import CandleType, RunMode
 from freqtrade.exceptions import ExchangeError, OperationalException
 from freqtrade.plugins.pairlistmanager import PairListManager
 from tests.conftest import get_patched_exchange
 
 
-def test_ohlcv(mocker, default_conf, ohlcv_history):
+@pytest.mark.parametrize('candle_type', [
+    'mark',
+    '',
+])
+def test_dp_ohlcv(mocker, default_conf, ohlcv_history, candle_type):
     default_conf["runmode"] = RunMode.DRY_RUN
     timeframe = default_conf["timeframe"]
     exchange = get_patched_exchange(mocker, default_conf)
-    exchange._klines[("XRP/BTC", timeframe)] = ohlcv_history
-    exchange._klines[("UNITTEST/BTC", timeframe)] = ohlcv_history
+    candletype = CandleType.from_string(candle_type)
+    exchange._klines[("XRP/BTC", timeframe, candletype)] = ohlcv_history
+    exchange._klines[("UNITTEST/BTC", timeframe, candletype)] = ohlcv_history
 
     dp = DataProvider(default_conf, exchange)
     assert dp.runmode == RunMode.DRY_RUN
-    assert ohlcv_history.equals(dp.ohlcv("UNITTEST/BTC", timeframe))
-    assert isinstance(dp.ohlcv("UNITTEST/BTC", timeframe), DataFrame)
-    assert dp.ohlcv("UNITTEST/BTC", timeframe) is not ohlcv_history
-    assert dp.ohlcv("UNITTEST/BTC", timeframe, copy=False) is ohlcv_history
-    assert not dp.ohlcv("UNITTEST/BTC", timeframe).empty
-    assert dp.ohlcv("NONESENSE/AAA", timeframe).empty
+    assert ohlcv_history.equals(dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candletype))
+    assert isinstance(dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candletype), DataFrame)
+    assert dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candletype) is not ohlcv_history
+    assert dp.ohlcv("UNITTEST/BTC", timeframe, copy=False, candle_type=candletype) is ohlcv_history
+    assert not dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candletype).empty
+    assert dp.ohlcv("NONESENSE/AAA", timeframe, candle_type=candletype).empty
 
     # Test with and without parameter
-    assert dp.ohlcv("UNITTEST/BTC", timeframe).equals(dp.ohlcv("UNITTEST/BTC"))
+    assert dp.ohlcv(
+        "UNITTEST/BTC",
+        timeframe,
+        candle_type=candletype
+    ).equals(dp.ohlcv("UNITTEST/BTC", candle_type=candle_type))
 
     default_conf["runmode"] = RunMode.LIVE
     dp = DataProvider(default_conf, exchange)
     assert dp.runmode == RunMode.LIVE
-    assert isinstance(dp.ohlcv("UNITTEST/BTC", timeframe), DataFrame)
+    assert isinstance(dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candle_type), DataFrame)
 
     default_conf["runmode"] = RunMode.BACKTEST
     dp = DataProvider(default_conf, exchange)
     assert dp.runmode == RunMode.BACKTEST
-    assert dp.ohlcv("UNITTEST/BTC", timeframe).empty
+    assert dp.ohlcv("UNITTEST/BTC", timeframe, candle_type=candle_type).empty
 
 
 def test_historic_ohlcv(mocker, default_conf, ohlcv_history):
@@ -77,37 +86,50 @@ def test_historic_ohlcv_dataformat(mocker, default_conf, ohlcv_history):
     jsonloadmock.assert_not_called()
 
 
-def test_get_pair_dataframe(mocker, default_conf, ohlcv_history):
+@pytest.mark.parametrize('candle_type', [
+    'mark',
+    'futures',
+    '',
+])
+def test_get_pair_dataframe(mocker, default_conf, ohlcv_history, candle_type):
     default_conf["runmode"] = RunMode.DRY_RUN
     timeframe = default_conf["timeframe"]
     exchange = get_patched_exchange(mocker, default_conf)
-    exchange._klines[("XRP/BTC", timeframe)] = ohlcv_history
-    exchange._klines[("UNITTEST/BTC", timeframe)] = ohlcv_history
+    candletype = CandleType.from_string(candle_type)
+    exchange._klines[("XRP/BTC", timeframe, candletype)] = ohlcv_history
+    exchange._klines[("UNITTEST/BTC", timeframe, candletype)] = ohlcv_history
 
     dp = DataProvider(default_conf, exchange)
     assert dp.runmode == RunMode.DRY_RUN
-    assert ohlcv_history.equals(dp.get_pair_dataframe("UNITTEST/BTC", timeframe))
-    assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", timeframe), DataFrame)
-    assert dp.get_pair_dataframe("UNITTEST/BTC", timeframe) is not ohlcv_history
-    assert not dp.get_pair_dataframe("UNITTEST/BTC", timeframe).empty
-    assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty
+    assert ohlcv_history.equals(dp.get_pair_dataframe(
+        "UNITTEST/BTC", timeframe, candle_type=candle_type))
+    assert ohlcv_history.equals(dp.get_pair_dataframe(
+        "UNITTEST/BTC", timeframe, candle_type=candletype))
+    assert isinstance(dp.get_pair_dataframe(
+        "UNITTEST/BTC", timeframe, candle_type=candle_type), DataFrame)
+    assert dp.get_pair_dataframe("UNITTEST/BTC", timeframe,
+                                 candle_type=candle_type) is not ohlcv_history
+    assert not dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type).empty
+    assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe, candle_type=candle_type).empty
 
     # Test with and without parameter
-    assert dp.get_pair_dataframe("UNITTEST/BTC", timeframe)\
-        .equals(dp.get_pair_dataframe("UNITTEST/BTC"))
+    assert dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type)\
+        .equals(dp.get_pair_dataframe("UNITTEST/BTC", candle_type=candle_type))
 
     default_conf["runmode"] = RunMode.LIVE
     dp = DataProvider(default_conf, exchange)
     assert dp.runmode == RunMode.LIVE
-    assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", timeframe), DataFrame)
-    assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty
+    assert isinstance(dp.get_pair_dataframe(
+        "UNITTEST/BTC", timeframe, candle_type=candle_type), DataFrame)
+    assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe, candle_type=candle_type).empty
 
     historymock = MagicMock(return_value=ohlcv_history)
     mocker.patch("freqtrade.data.dataprovider.load_pair_history", historymock)
     default_conf["runmode"] = RunMode.BACKTEST
     dp = DataProvider(default_conf, exchange)
     assert dp.runmode == RunMode.BACKTEST
-    assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", timeframe), DataFrame)
+    assert isinstance(dp.get_pair_dataframe(
+        "UNITTEST/BTC", timeframe, candle_type=candle_type), DataFrame)
     # assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty
 
 
@@ -230,8 +252,8 @@ def test_get_analyzed_dataframe(mocker, default_conf, ohlcv_history):
     exchange = get_patched_exchange(mocker, default_conf)
 
     dp = DataProvider(default_conf, exchange)
-    dp._set_cached_df("XRP/BTC", timeframe, ohlcv_history)
-    dp._set_cached_df("UNITTEST/BTC", timeframe, ohlcv_history)
+    dp._set_cached_df("XRP/BTC", timeframe, ohlcv_history, CandleType.SPOT)
+    dp._set_cached_df("UNITTEST/BTC", timeframe, ohlcv_history, CandleType.SPOT)
 
     assert dp.runmode == RunMode.DRY_RUN
     dataframe, time = dp.get_analyzed_dataframe("UNITTEST/BTC", timeframe)
@@ -276,7 +298,7 @@ def test_no_exchange_mode(default_conf):
         dp.refresh([()])
 
     with pytest.raises(OperationalException, match=message):
-        dp.ohlcv('XRP/USDT', '5m')
+        dp.ohlcv('XRP/USDT', '5m', '')
 
     with pytest.raises(OperationalException, match=message):
         dp.market('XRP/USDT')
diff --git a/tests/data/test_history.py b/tests/data/test_history.py
index 575a590e7..0585fa0d4 100644
--- a/tests/data/test_history.py
+++ b/tests/data/test_history.py
@@ -1,6 +1,7 @@
 # pragma pylint: disable=missing-docstring, protected-access, C0103
 
 import json
+import re
 import uuid
 from pathlib import Path
 from shutil import copyfile
@@ -23,10 +24,12 @@ from freqtrade.data.history.history_utils import (_download_pair_history, _downl
                                                   validate_backtest_data)
 from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler, get_datahandlerclass
 from freqtrade.data.history.jsondatahandler import JsonDataHandler, JsonGzDataHandler
+from freqtrade.enums import CandleType, TradingMode
 from freqtrade.exchange import timeframe_to_minutes
 from freqtrade.misc import file_dump_json
 from freqtrade.resolvers import StrategyResolver
-from tests.conftest import get_patched_exchange, log_has, log_has_re, patch_exchange
+from tests.conftest import (CURRENT_TEST_STRATEGY, get_patched_exchange, log_has, log_has_re,
+                            patch_exchange)
 
 
 # Change this if modifying UNITTEST/BTC testdatafile
@@ -78,7 +81,7 @@ def test_load_data_7min_timeframe(mocker, caplog, default_conf, testdatadir) ->
     assert isinstance(ld, DataFrame)
     assert ld.empty
     assert log_has(
-        'No history data for pair: "UNITTEST/BTC", timeframe: 7m. '
+        'No history for UNITTEST/BTC, spot, 7m found. '
         'Use `freqtrade download-data` to download the data', caplog
     )
 
@@ -94,6 +97,17 @@ def test_load_data_1min_timeframe(ohlcv_history, mocker, caplog, testdatadir) ->
     )
 
 
+def test_load_data_mark(ohlcv_history, mocker, caplog, testdatadir) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=ohlcv_history)
+    file = testdatadir / 'futures/UNITTEST_USDT-1h-mark.json'
+    load_data(datadir=testdatadir, timeframe='1h', pairs=['UNITTEST/BTC'], candle_type='mark')
+    assert file.is_file()
+    assert not log_has(
+        'Download history data for pair: "UNITTEST/USDT", interval: 1m '
+        'and store in None.', caplog
+    )
+
+
 def test_load_data_startup_candles(mocker, caplog, default_conf, testdatadir) -> None:
     ltfmock = mocker.patch(
         'freqtrade.data.history.jsondatahandler.JsonDataHandler._ohlcv_load',
@@ -109,8 +123,9 @@ def test_load_data_startup_candles(mocker, caplog, default_conf, testdatadir) ->
     assert ltfmock.call_args_list[0][1]['timerange'].startts == timerange.startts - 20 * 60
 
 
+@pytest.mark.parametrize('candle_type', ['mark', ''])
 def test_load_data_with_new_pair_1min(ohlcv_history_list, mocker, caplog,
-                                      default_conf, tmpdir) -> None:
+                                      default_conf, tmpdir, candle_type) -> None:
     """
     Test load_pair_history() with 1 min timeframe
     """
@@ -120,21 +135,22 @@ def test_load_data_with_new_pair_1min(ohlcv_history_list, mocker, caplog,
     file = tmpdir1 / 'MEME_BTC-1m.json'
 
     # do not download a new pair if refresh_pairs isn't set
-    load_pair_history(datadir=tmpdir1, timeframe='1m', pair='MEME/BTC')
+    load_pair_history(datadir=tmpdir1, timeframe='1m', pair='MEME/BTC', candle_type=candle_type)
     assert not file.is_file()
     assert log_has(
-        'No history data for pair: "MEME/BTC", timeframe: 1m. '
-        'Use `freqtrade download-data` to download the data', caplog
+        f"No history for MEME/BTC, {candle_type}, 1m found. "
+        "Use `freqtrade download-data` to download the data", caplog
     )
 
     # download a new pair if refresh_pairs is set
     refresh_data(datadir=tmpdir1, timeframe='1m', pairs=['MEME/BTC'],
-                 exchange=exchange)
-    load_pair_history(datadir=tmpdir1, timeframe='1m', pair='MEME/BTC')
+                 exchange=exchange, candle_type=CandleType.SPOT
+                 )
+    load_pair_history(datadir=tmpdir1, timeframe='1m', pair='MEME/BTC', candle_type=candle_type)
     assert file.is_file()
     assert log_has_re(
-        r'Download history data for pair: "MEME/BTC" \(0/1\), timeframe: 1m '
-        r'and store in .*', caplog
+        r'Download history data for pair: "MEME/BTC" \(0/1\), timeframe: 1m, '
+        r'candle type: spot and store in .*', caplog
     )
 
 
@@ -142,19 +158,31 @@ def test_testdata_path(testdatadir) -> None:
     assert str(Path('tests') / 'testdata') in str(testdatadir)
 
 
-@pytest.mark.parametrize("pair,expected_result", [
-    ("ETH/BTC", 'freqtrade/hello/world/ETH_BTC-5m.json'),
-    ("Fabric Token/ETH", 'freqtrade/hello/world/Fabric_Token_ETH-5m.json'),
-    ("ETHH20", 'freqtrade/hello/world/ETHH20-5m.json'),
-    (".XBTBON2H", 'freqtrade/hello/world/_XBTBON2H-5m.json'),
-    ("ETHUSD.d", 'freqtrade/hello/world/ETHUSD_d-5m.json'),
-    ("ACC_OLD/BTC", 'freqtrade/hello/world/ACC_OLD_BTC-5m.json'),
+@pytest.mark.parametrize("pair,expected_result,candle_type", [
+    ("ETH/BTC", 'freqtrade/hello/world/ETH_BTC-5m.json', ""),
+    ("Fabric Token/ETH", 'freqtrade/hello/world/Fabric_Token_ETH-5m.json', ""),
+    ("ETHH20", 'freqtrade/hello/world/ETHH20-5m.json', ""),
+    (".XBTBON2H", 'freqtrade/hello/world/_XBTBON2H-5m.json', ""),
+    ("ETHUSD.d", 'freqtrade/hello/world/ETHUSD_d-5m.json', ""),
+    ("ACC_OLD/BTC", 'freqtrade/hello/world/ACC_OLD_BTC-5m.json', ""),
+    ("ETH/BTC", 'freqtrade/hello/world/futures/ETH_BTC-5m-mark.json', "mark"),
+    ("ACC_OLD/BTC", 'freqtrade/hello/world/futures/ACC_OLD_BTC-5m-index.json', "index"),
 ])
-def test_json_pair_data_filename(pair, expected_result):
-    fn = JsonDataHandler._pair_data_filename(Path('freqtrade/hello/world'), pair, '5m')
+def test_json_pair_data_filename(pair, expected_result, candle_type):
+    fn = JsonDataHandler._pair_data_filename(
+        Path('freqtrade/hello/world'),
+        pair,
+        '5m',
+        CandleType.from_string(candle_type)
+    )
     assert isinstance(fn, Path)
     assert fn == Path(expected_result)
-    fn = JsonGzDataHandler._pair_data_filename(Path('freqtrade/hello/world'), pair, '5m')
+    fn = JsonGzDataHandler._pair_data_filename(
+        Path('freqtrade/hello/world'),
+        pair,
+        '5m',
+        candle_type=CandleType.from_string(candle_type)
+    )
     assert isinstance(fn, Path)
     assert fn == Path(expected_result + '.gz')
 
@@ -195,14 +223,16 @@ def test_load_cached_data_for_updating(mocker, testdatadir) -> None:
     # timeframe starts earlier than the cached data
     # should fully update data
     timerange = TimeRange('date', None, test_data[0][0] / 1000 - 1, 0)
-    data, start_ts = _load_cached_data_for_updating('UNITTEST/BTC', '1m', timerange, data_handler)
+    data, start_ts = _load_cached_data_for_updating(
+        'UNITTEST/BTC', '1m', timerange, data_handler, CandleType.SPOT)
     assert data.empty
     assert start_ts == test_data[0][0] - 1000
 
     # timeframe starts in the center of the cached data
     # should return the cached data w/o the last item
     timerange = TimeRange('date', None, test_data[0][0] / 1000 + 1, 0)
-    data, start_ts = _load_cached_data_for_updating('UNITTEST/BTC', '1m', timerange, data_handler)
+    data, start_ts = _load_cached_data_for_updating(
+        'UNITTEST/BTC', '1m', timerange, data_handler, CandleType.SPOT)
 
     assert_frame_equal(data, test_data_df.iloc[:-1])
     assert test_data[-2][0] <= start_ts < test_data[-1][0]
@@ -210,42 +240,59 @@ def test_load_cached_data_for_updating(mocker, testdatadir) -> None:
     # timeframe starts after the cached data
     # should return the cached data w/o the last item
     timerange = TimeRange('date', None, test_data[-1][0] / 1000 + 100, 0)
-    data, start_ts = _load_cached_data_for_updating('UNITTEST/BTC', '1m', timerange, data_handler)
+    data, start_ts = _load_cached_data_for_updating(
+        'UNITTEST/BTC', '1m', timerange, data_handler, CandleType.SPOT)
     assert_frame_equal(data, test_data_df.iloc[:-1])
     assert test_data[-2][0] <= start_ts < test_data[-1][0]
 
     # no datafile exist
     # should return timestamp start time
     timerange = TimeRange('date', None, now_ts - 10000, 0)
-    data, start_ts = _load_cached_data_for_updating('NONEXIST/BTC', '1m', timerange, data_handler)
+    data, start_ts = _load_cached_data_for_updating(
+        'NONEXIST/BTC', '1m', timerange, data_handler, CandleType.SPOT)
     assert data.empty
     assert start_ts == (now_ts - 10000) * 1000
 
     # no datafile exist, no timeframe is set
     # should return an empty array and None
-    data, start_ts = _load_cached_data_for_updating('NONEXIST/BTC', '1m', None, data_handler)
+    data, start_ts = _load_cached_data_for_updating(
+        'NONEXIST/BTC', '1m', None, data_handler, CandleType.SPOT)
     assert data.empty
     assert start_ts is None
 
 
-def test_download_pair_history(ohlcv_history_list, mocker, default_conf, tmpdir) -> None:
+@pytest.mark.parametrize('candle_type,subdir,file_tail', [
+    ('mark', 'futures/', '-mark'),
+    ('spot', '', ''),
+])
+def test_download_pair_history(
+    ohlcv_history_list,
+    mocker,
+    default_conf,
+    tmpdir,
+    candle_type,
+    subdir,
+    file_tail
+) -> None:
     mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=ohlcv_history_list)
     exchange = get_patched_exchange(mocker, default_conf)
     tmpdir1 = Path(tmpdir)
-    file1_1 = tmpdir1 / 'MEME_BTC-1m.json'
-    file1_5 = tmpdir1 / 'MEME_BTC-5m.json'
-    file2_1 = tmpdir1 / 'CFI_BTC-1m.json'
-    file2_5 = tmpdir1 / 'CFI_BTC-5m.json'
+    file1_1 = tmpdir1 / f'{subdir}MEME_BTC-1m{file_tail}.json'
+    file1_5 = tmpdir1 / f'{subdir}MEME_BTC-5m{file_tail}.json'
+    file2_1 = tmpdir1 / f'{subdir}CFI_BTC-1m{file_tail}.json'
+    file2_5 = tmpdir1 / f'{subdir}CFI_BTC-5m{file_tail}.json'
 
     assert not file1_1.is_file()
     assert not file2_1.is_file()
 
     assert _download_pair_history(datadir=tmpdir1, exchange=exchange,
                                   pair='MEME/BTC',
-                                  timeframe='1m')
+                                  timeframe='1m',
+                                  candle_type=candle_type)
     assert _download_pair_history(datadir=tmpdir1, exchange=exchange,
                                   pair='CFI/BTC',
-                                  timeframe='1m')
+                                  timeframe='1m',
+                                  candle_type=candle_type)
     assert not exchange._pairs_last_refresh_time
     assert file1_1.is_file()
     assert file2_1.is_file()
@@ -259,10 +306,12 @@ def test_download_pair_history(ohlcv_history_list, mocker, default_conf, tmpdir)
 
     assert _download_pair_history(datadir=tmpdir1, exchange=exchange,
                                   pair='MEME/BTC',
-                                  timeframe='5m')
+                                  timeframe='5m',
+                                  candle_type=candle_type)
     assert _download_pair_history(datadir=tmpdir1, exchange=exchange,
                                   pair='CFI/BTC',
-                                  timeframe='5m')
+                                  timeframe='5m',
+                                  candle_type=candle_type)
     assert not exchange._pairs_last_refresh_time
     assert file1_5.is_file()
     assert file2_5.is_file()
@@ -279,10 +328,12 @@ def test_download_pair_history2(mocker, default_conf, testdatadir) -> None:
     mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=tick)
     exchange = get_patched_exchange(mocker, default_conf)
     _download_pair_history(datadir=testdatadir, exchange=exchange, pair="UNITTEST/BTC",
-                           timeframe='1m')
+                           timeframe='1m', candle_type='spot')
     _download_pair_history(datadir=testdatadir, exchange=exchange, pair="UNITTEST/BTC",
-                           timeframe='3m')
-    assert json_dump_mock.call_count == 2
+                           timeframe='3m', candle_type='spot')
+    _download_pair_history(datadir=testdatadir, exchange=exchange, pair="UNITTEST/USDT",
+                           timeframe='1h', candle_type='mark')
+    assert json_dump_mock.call_count == 3
 
 
 def test_download_backtesting_data_exception(mocker, caplog, default_conf, tmpdir) -> None:
@@ -293,7 +344,7 @@ def test_download_backtesting_data_exception(mocker, caplog, default_conf, tmpdi
 
     assert not _download_pair_history(datadir=tmpdir1, exchange=exchange,
                                       pair='MEME/BTC',
-                                      timeframe='1m')
+                                      timeframe='1m', candle_type='spot')
     assert log_has('Failed to download history data for pair: "MEME/BTC", timeframe: 1m.', caplog)
 
 
@@ -310,8 +361,8 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
     td = ((end - start).total_seconds() // 60 // 5) + 1
     assert td != len(data['UNITTEST/BTC'])
     start_real = data['UNITTEST/BTC'].iloc[0, 0]
-    assert log_has(f'Missing data at start for pair '
-                   f'UNITTEST/BTC, data starts at {start_real.strftime("%Y-%m-%d %H:%M:%S")}',
+    assert log_has(f'UNITTEST/BTC, spot, 5m, '
+                   f'data starts at {start_real.strftime("%Y-%m-%d %H:%M:%S")}',
                    caplog)
     # Make sure we start fresh - test missing data at end
     caplog.clear()
@@ -325,8 +376,8 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
 
     # Shift endtime with +5 - as last candle is dropped (partial candle)
     end_real = arrow.get(data['UNITTEST/BTC'].iloc[-1, 0]).shift(minutes=5)
-    assert log_has(f'Missing data at end for pair '
-                   f'UNITTEST/BTC, data ends at {end_real.strftime("%Y-%m-%d %H:%M:%S")}',
+    assert log_has(f'UNITTEST/BTC, spot, 5m, '
+                   f'data ends at {end_real.strftime("%Y-%m-%d %H:%M:%S")}',
                    caplog)
 
 
@@ -344,7 +395,8 @@ def test_init_with_refresh(default_conf, mocker) -> None:
         datadir=Path(''),
         pairs=[],
         timeframe=default_conf['timeframe'],
-        exchange=exchange
+        exchange=exchange,
+        candle_type=CandleType.SPOT
     )
     assert {} == load_data(
         datadir=Path(''),
@@ -380,7 +432,7 @@ def test_file_dump_json_tofile(testdatadir) -> None:
 def test_get_timerange(default_conf, mocker, testdatadir) -> None:
     patch_exchange(mocker)
 
-    default_conf.update({'strategy': 'StrategyTestV2'})
+    default_conf.update({'strategy': CURRENT_TEST_STRATEGY})
     strategy = StrategyResolver.load_strategy(default_conf)
 
     data = strategy.advise_all_indicators(
@@ -398,7 +450,7 @@ def test_get_timerange(default_conf, mocker, testdatadir) -> None:
 def test_validate_backtest_data_warn(default_conf, mocker, caplog, testdatadir) -> None:
     patch_exchange(mocker)
 
-    default_conf.update({'strategy': 'StrategyTestV2'})
+    default_conf.update({'strategy': CURRENT_TEST_STRATEGY})
     strategy = StrategyResolver.load_strategy(default_conf)
 
     data = strategy.advise_all_indicators(
@@ -422,7 +474,7 @@ def test_validate_backtest_data_warn(default_conf, mocker, caplog, testdatadir)
 def test_validate_backtest_data(default_conf, mocker, caplog, testdatadir) -> None:
     patch_exchange(mocker)
 
-    default_conf.update({'strategy': 'StrategyTestV2'})
+    default_conf.update({'strategy': CURRENT_TEST_STRATEGY})
     strategy = StrategyResolver.load_strategy(default_conf)
 
     timerange = TimeRange('index', 'index', 200, 250)
@@ -442,7 +494,13 @@ def test_validate_backtest_data(default_conf, mocker, caplog, testdatadir) -> No
     assert len(caplog.record_tuples) == 0
 
 
-def test_refresh_backtest_ohlcv_data(mocker, default_conf, markets, caplog, testdatadir):
+@pytest.mark.parametrize('trademode,callcount', [
+    ('spot', 4),
+    ('margin', 4),
+    ('futures', 8),  # Called 8 times - 4 normal, 2 funding and 2 mark/index calls
+])
+def test_refresh_backtest_ohlcv_data(
+        mocker, default_conf, markets, caplog, testdatadir, trademode, callcount):
     dl_mock = mocker.patch('freqtrade.data.history.history_utils._download_pair_history',
                            MagicMock())
     mocker.patch(
@@ -455,10 +513,11 @@ def test_refresh_backtest_ohlcv_data(mocker, default_conf, markets, caplog, test
     timerange = TimeRange.parse_timerange("20190101-20190102")
     refresh_backtest_ohlcv_data(exchange=ex, pairs=["ETH/BTC", "XRP/BTC"],
                                 timeframes=["1m", "5m"], datadir=testdatadir,
-                                timerange=timerange, erase=True
+                                timerange=timerange, erase=True,
+                                trading_mode=trademode
                                 )
 
-    assert dl_mock.call_count == 4
+    assert dl_mock.call_count == callcount
     assert dl_mock.call_args[1]['timerange'].starttype == 'date'
 
     assert log_has("Downloading pair ETH/BTC, interval 1m.", caplog)
@@ -476,7 +535,8 @@ def test_download_data_no_markets(mocker, default_conf, caplog, testdatadir):
     unav_pairs = refresh_backtest_ohlcv_data(exchange=ex, pairs=["BTT/BTC", "LTC/USDT"],
                                              timeframes=["1m", "5m"],
                                              datadir=testdatadir,
-                                             timerange=timerange, erase=False
+                                             timerange=timerange, erase=False,
+                                             trading_mode='spot'
                                              )
 
     assert dl_mock.call_count == 0
@@ -604,33 +664,101 @@ def test_convert_trades_to_ohlcv(testdatadir, tmpdir, caplog):
 
 
 def test_datahandler_ohlcv_get_pairs(testdatadir):
-    pairs = JsonDataHandler.ohlcv_get_pairs(testdatadir, '5m')
+    pairs = JsonDataHandler.ohlcv_get_pairs(testdatadir, '5m', candle_type=CandleType.SPOT)
     # Convert to set to avoid failures due to sorting
     assert set(pairs) == {'UNITTEST/BTC', 'XLM/BTC', 'ETH/BTC', 'TRX/BTC', 'LTC/BTC',
                           'XMR/BTC', 'ZEC/BTC', 'ADA/BTC', 'ETC/BTC', 'NXT/BTC',
                           'DASH/BTC', 'XRP/ETH'}
 
-    pairs = JsonGzDataHandler.ohlcv_get_pairs(testdatadir, '8m')
+    pairs = JsonGzDataHandler.ohlcv_get_pairs(testdatadir, '8m', candle_type=CandleType.SPOT)
     assert set(pairs) == {'UNITTEST/BTC'}
 
-    pairs = HDF5DataHandler.ohlcv_get_pairs(testdatadir, '5m')
+    pairs = HDF5DataHandler.ohlcv_get_pairs(testdatadir, '5m', candle_type=CandleType.SPOT)
     assert set(pairs) == {'UNITTEST/BTC'}
 
+    pairs = JsonDataHandler.ohlcv_get_pairs(testdatadir, '1h', candle_type=CandleType.MARK)
+    assert set(pairs) == {'UNITTEST/USDT', 'XRP/USDT'}
+
+    pairs = JsonGzDataHandler.ohlcv_get_pairs(testdatadir, '1h', candle_type=CandleType.FUTURES)
+    assert set(pairs) == {'XRP/USDT'}
+
+    pairs = HDF5DataHandler.ohlcv_get_pairs(testdatadir, '1h', candle_type=CandleType.MARK)
+    assert set(pairs) == {'UNITTEST/USDT:USDT'}
+
+
+@pytest.mark.parametrize('filename,pair,timeframe,candletype', [
+    ('XMR_BTC-5m.json', 'XMR_BTC', '5m', ''),
+    ('XMR_USDT-1h.h5', 'XMR_USDT', '1h', ''),
+    ('BTC-PERP-1h.h5', 'BTC-PERP', '1h', ''),
+    ('BTC_USDT-2h.jsongz', 'BTC_USDT', '2h', ''),
+    ('BTC_USDT-2h-mark.jsongz', 'BTC_USDT', '2h', 'mark'),
+    ('XMR_USDT-1h-mark.h5', 'XMR_USDT', '1h', 'mark'),
+    ('XMR_USDT-1h-random.h5', 'XMR_USDT', '1h', 'random'),
+    ('BTC-PERP-1h-index.h5', 'BTC-PERP', '1h', 'index'),
+    ('XMR_USDT_USDT-1h-mark.h5', 'XMR_USDT_USDT', '1h', 'mark'),
+])
+def test_datahandler_ohlcv_regex(filename, pair, timeframe, candletype):
+    regex = JsonDataHandler._OHLCV_REGEX
+
+    match = re.search(regex, filename)
+    assert len(match.groups()) > 1
+    assert match[1] == pair
+    assert match[2] == timeframe
+    assert match[3] == candletype
+
+
+@pytest.mark.parametrize('input,expected', [
+    ('XMR_USDT', 'XMR/USDT'),
+    ('BTC_USDT', 'BTC/USDT'),
+    ('USDT_BUSD', 'USDT/BUSD'),
+    ('BTC_USDT_USDT', 'BTC/USDT:USDT'),  # Futures
+    ('XRP_USDT_USDT', 'XRP/USDT:USDT'),  # futures
+    ('BTC-PERP', 'BTC-PERP'),
+    ('BTC-PERP_USDT', 'BTC-PERP:USDT'),  # potential FTX case
+    ('UNITTEST_USDT', 'UNITTEST/USDT'),
+])
+def test_rebuild_pair_from_filename(input, expected):
+
+    assert IDataHandler.rebuild_pair_from_filename(input) == expected
+
 
 def test_datahandler_ohlcv_get_available_data(testdatadir):
-    paircombs = JsonDataHandler.ohlcv_get_available_data(testdatadir)
+    paircombs = JsonDataHandler.ohlcv_get_available_data(testdatadir, TradingMode.SPOT)
     # Convert to set to avoid failures due to sorting
-    assert set(paircombs) == {('UNITTEST/BTC', '5m'), ('ETH/BTC', '5m'), ('XLM/BTC', '5m'),
-                              ('TRX/BTC', '5m'), ('LTC/BTC', '5m'), ('XMR/BTC', '5m'),
-                              ('ZEC/BTC', '5m'), ('UNITTEST/BTC', '1m'), ('ADA/BTC', '5m'),
-                              ('ETC/BTC', '5m'), ('NXT/BTC', '5m'), ('DASH/BTC', '5m'),
-                              ('XRP/ETH', '1m'), ('XRP/ETH', '5m'), ('UNITTEST/BTC', '30m'),
-                              ('UNITTEST/BTC', '8m'), ('NOPAIR/XXX', '4m')}
+    assert set(paircombs) == {
+        ('UNITTEST/BTC', '5m', CandleType.SPOT),
+        ('ETH/BTC', '5m', CandleType.SPOT),
+        ('XLM/BTC', '5m', CandleType.SPOT),
+        ('TRX/BTC', '5m', CandleType.SPOT),
+        ('LTC/BTC', '5m', CandleType.SPOT),
+        ('XMR/BTC', '5m', CandleType.SPOT),
+        ('ZEC/BTC', '5m', CandleType.SPOT),
+        ('UNITTEST/BTC', '1m', CandleType.SPOT),
+        ('ADA/BTC', '5m', CandleType.SPOT),
+        ('ETC/BTC', '5m', CandleType.SPOT),
+        ('NXT/BTC', '5m', CandleType.SPOT),
+        ('DASH/BTC', '5m', CandleType.SPOT),
+        ('XRP/ETH', '1m', CandleType.SPOT),
+        ('XRP/ETH', '5m', CandleType.SPOT),
+        ('UNITTEST/BTC', '30m', CandleType.SPOT),
+        ('UNITTEST/BTC', '8m', CandleType.SPOT),
+        ('NOPAIR/XXX', '4m', CandleType.SPOT),
+    }
 
-    paircombs = JsonGzDataHandler.ohlcv_get_available_data(testdatadir)
-    assert set(paircombs) == {('UNITTEST/BTC', '8m')}
-    paircombs = HDF5DataHandler.ohlcv_get_available_data(testdatadir)
-    assert set(paircombs) == {('UNITTEST/BTC', '5m')}
+    paircombs = JsonDataHandler.ohlcv_get_available_data(testdatadir, TradingMode.FUTURES)
+    # Convert to set to avoid failures due to sorting
+    assert set(paircombs) == {
+        ('UNITTEST/USDT', '1h', 'mark'),
+        ('XRP/USDT', '1h', 'futures'),
+        ('XRP/USDT', '1h', 'mark'),
+        ('XRP/USDT', '8h', 'mark'),
+        ('XRP/USDT', '8h', 'funding_rate'),
+    }
+
+    paircombs = JsonGzDataHandler.ohlcv_get_available_data(testdatadir, TradingMode.SPOT)
+    assert set(paircombs) == {('UNITTEST/BTC', '8m', CandleType.SPOT)}
+    paircombs = HDF5DataHandler.ohlcv_get_available_data(testdatadir, TradingMode.SPOT)
+    assert set(paircombs) == {('UNITTEST/BTC', '5m', CandleType.SPOT)}
 
 
 def test_jsondatahandler_trades_get_pairs(testdatadir):
@@ -643,21 +771,29 @@ def test_jsondatahandler_ohlcv_purge(mocker, testdatadir):
     mocker.patch.object(Path, "exists", MagicMock(return_value=False))
     unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
     dh = JsonGzDataHandler(testdatadir)
-    assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m')
+    assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
+    assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
     assert unlinkmock.call_count == 0
 
     mocker.patch.object(Path, "exists", MagicMock(return_value=True))
-    assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m')
-    assert unlinkmock.call_count == 1
+    assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
+    assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
+    assert unlinkmock.call_count == 2
 
 
 def test_jsondatahandler_ohlcv_load(testdatadir, caplog):
     dh = JsonDataHandler(testdatadir)
-    df = dh.ohlcv_load('XRP/ETH', '5m')
+    df = dh.ohlcv_load('XRP/ETH', '5m', 'spot')
     assert len(df) == 711
 
+    df_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', candle_type="mark")
+    assert len(df_mark) == 99
+
+    df_no_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', 'spot')
+    assert len(df_no_mark) == 0
+
     # Failure case (empty array)
-    df1 = dh.ohlcv_load('NOPAIR/XXX', '4m')
+    df1 = dh.ohlcv_load('NOPAIR/XXX', '4m', 'spot')
     assert len(df1) == 0
     assert log_has("Could not load data for NOPAIR/XXX.", caplog)
     assert df.columns.equals(df1.columns)
@@ -690,7 +826,9 @@ def test_jsondatahandler_trades_purge(mocker, testdatadir):
 def test_datahandler_ohlcv_append(datahandler, testdatadir, ):
     dh = get_datahandler(testdatadir, datahandler)
     with pytest.raises(NotImplementedError):
-        dh.ohlcv_append('UNITTEST/ETH', '5m', DataFrame())
+        dh.ohlcv_append('UNITTEST/ETH', '5m', DataFrame(), CandleType.SPOT)
+    with pytest.raises(NotImplementedError):
+        dh.ohlcv_append('UNITTEST/ETH', '5m', DataFrame(), CandleType.MARK)
 
 
 @pytest.mark.parametrize('datahandler', AVAILABLE_DATAHANDLERS)
@@ -772,35 +910,52 @@ def test_hdf5datahandler_trades_purge(mocker, testdatadir):
     assert unlinkmock.call_count == 1
 
 
-def test_hdf5datahandler_ohlcv_load_and_resave(testdatadir, tmpdir):
+@pytest.mark.parametrize('pair,timeframe,candle_type,candle_append,startdt,enddt', [
+    # Data goes from 2018-01-10 - 2018-01-30
+    ('UNITTEST/BTC', '5m', 'spot',  '', '2018-01-15', '2018-01-19'),
+    # Mark data goes from to 2021-11-15 2021-11-19
+    ('UNITTEST/USDT:USDT', '1h', 'mark', '-mark', '2021-11-16', '2021-11-18'),
+])
+def test_hdf5datahandler_ohlcv_load_and_resave(
+    testdatadir,
+    tmpdir,
+    pair,
+    timeframe,
+    candle_type,
+    candle_append,
+    startdt, enddt
+):
     tmpdir1 = Path(tmpdir)
+    tmpdir2 = tmpdir1
+    if candle_type not in ('', 'spot'):
+        tmpdir2 = tmpdir1 / 'futures'
+        tmpdir2.mkdir()
     dh = HDF5DataHandler(testdatadir)
-    ohlcv = dh.ohlcv_load('UNITTEST/BTC', '5m')
+    ohlcv = dh._ohlcv_load(pair, timeframe, None, candle_type=candle_type)
     assert isinstance(ohlcv, DataFrame)
     assert len(ohlcv) > 0
 
-    file = tmpdir1 / 'UNITTEST_NEW-5m.h5'
+    file = tmpdir2 / f"UNITTEST_NEW-{timeframe}{candle_append}.h5"
     assert not file.is_file()
 
     dh1 = HDF5DataHandler(tmpdir1)
-    dh1.ohlcv_store('UNITTEST/NEW', '5m', ohlcv)
+    dh1.ohlcv_store('UNITTEST/NEW', timeframe, ohlcv, candle_type=candle_type)
     assert file.is_file()
 
-    assert not ohlcv[ohlcv['date'] < '2018-01-15'].empty
+    assert not ohlcv[ohlcv['date'] < startdt].empty
 
-    # Data gores from 2018-01-10 - 2018-01-30
-    timerange = TimeRange.parse_timerange('20180115-20180119')
+    timerange = TimeRange.parse_timerange(f"{startdt.replace('-', '')}-{enddt.replace('-', '')}")
 
     # Call private function to ensure timerange is filtered in hdf5
-    ohlcv = dh._ohlcv_load('UNITTEST/BTC', '5m', timerange)
-    ohlcv1 = dh1._ohlcv_load('UNITTEST/NEW', '5m', timerange)
+    ohlcv = dh._ohlcv_load(pair, timeframe, timerange, candle_type=candle_type)
+    ohlcv1 = dh1._ohlcv_load('UNITTEST/NEW', timeframe, timerange, candle_type=candle_type)
     assert len(ohlcv) == len(ohlcv1)
     assert ohlcv.equals(ohlcv1)
-    assert ohlcv[ohlcv['date'] < '2018-01-15'].empty
-    assert ohlcv[ohlcv['date'] > '2018-01-19'].empty
+    assert ohlcv[ohlcv['date'] < startdt].empty
+    assert ohlcv[ohlcv['date'] > enddt].empty
 
     # Try loading inexisting file
-    ohlcv = dh.ohlcv_load('UNITTEST/NONEXIST', '5m')
+    ohlcv = dh.ohlcv_load('UNITTEST/NONEXIST', timeframe, candle_type=candle_type)
     assert ohlcv.empty
 
 
@@ -808,12 +963,14 @@ def test_hdf5datahandler_ohlcv_purge(mocker, testdatadir):
     mocker.patch.object(Path, "exists", MagicMock(return_value=False))
     unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
     dh = HDF5DataHandler(testdatadir)
-    assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m')
+    assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
+    assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
     assert unlinkmock.call_count == 0
 
     mocker.patch.object(Path, "exists", MagicMock(return_value=True))
-    assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m')
-    assert unlinkmock.call_count == 1
+    assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
+    assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
+    assert unlinkmock.call_count == 2
 
 
 def test_gethandlerclass():
diff --git a/tests/edge/test_edge.py b/tests/edge/test_edge.py
index 7bdc940df..a43e82b22 100644
--- a/tests/edge/test_edge.py
+++ b/tests/edge/test_edge.py
@@ -12,7 +12,7 @@ from pandas import DataFrame, to_datetime
 
 from freqtrade.data.converter import ohlcv_to_dataframe
 from freqtrade.edge import Edge, PairInfo
-from freqtrade.enums import SellType
+from freqtrade.enums import ExitType
 from freqtrade.exceptions import OperationalException
 from tests.conftest import get_patched_freqtradebot, log_has
 from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
@@ -95,8 +95,8 @@ tc1 = BTContainer(data=[
     [6, 5000, 5025, 4975, 4987, 6172, 0, 0],  # should sell
 ],
     stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
-    trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=2),
-            BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=4, close_tick=6)]
+    trades=[BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=2),
+            BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=4, close_tick=6)]
 )
 
 # 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss
@@ -107,7 +107,7 @@ tc2 = BTContainer(data=[
     [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
 ],
     stop_loss=-0.01, roi={"0": float('inf')}, profit_perc=-0.01,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
 # 4) Entered, sl 3 %, candle drops 4%, recovers to 1 % = > Trade closed, 3 % loss
@@ -118,7 +118,7 @@ tc3 = BTContainer(data=[
     [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
 ],
     stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
 # 5) Stoploss and sell are hit. should sell on stoploss
@@ -129,7 +129,7 @@ tc4 = BTContainer(data=[
     [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
 ],
     stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
 TESTS = [
@@ -162,7 +162,7 @@ def test_edge_results(edge_conf, mocker, caplog, data) -> None:
 
     for c, trade in enumerate(data.trades):
         res = results.iloc[c]
-        assert res.exit_type == trade.sell_reason
+        assert res.exit_type == trade.exit_reason
         assert res.open_date == _get_frame_time_from_offset(trade.open_tick).replace(tzinfo=None)
         assert res.close_date == _get_frame_time_from_offset(trade.close_tick).replace(tzinfo=None)
 
@@ -391,7 +391,7 @@ def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectanc
          'trade_duration': '',
          'open_rate': 17,
          'close_rate': 17,
-         'exit_type': 'sell_signal'},
+         'exit_type': 'exit_signal'},
 
         {'pair': 'TEST/BTC',
          'stoploss': -0.9,
@@ -402,7 +402,7 @@ def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectanc
          'trade_duration': '',
          'open_rate': 20,
          'close_rate': 20,
-         'exit_type': 'sell_signal'},
+         'exit_type': 'exit_signal'},
 
         {'pair': 'TEST/BTC',
          'stoploss': -0.9,
@@ -413,7 +413,7 @@ def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectanc
          'trade_duration': '',
          'open_rate': 26,
          'close_rate': 34,
-         'exit_type': 'sell_signal'}
+         'exit_type': 'exit_signal'}
     ]
 
     trades_df = DataFrame(trades)
diff --git a/tests/exchange/test_binance.py b/tests/exchange/test_binance.py
index dd85c3abe..c3950e459 100644
--- a/tests/exchange/test_binance.py
+++ b/tests/exchange/test_binance.py
@@ -1,24 +1,29 @@
 from datetime import datetime, timezone
 from random import randint
-from unittest.mock import MagicMock
+from unittest.mock import MagicMock, PropertyMock
 
 import ccxt
 import pytest
 
+from freqtrade.enums import MarginMode, TradingMode
 from freqtrade.exceptions import DependencyException, InvalidOrderException, OperationalException
 from tests.conftest import get_mock_coro, get_patched_exchange, log_has_re
 from tests.exchange.test_exchange import ccxt_exceptionhandlers
 
 
-@pytest.mark.parametrize('limitratio,expected', [
-    (None, 220 * 0.99),
-    (0.99, 220 * 0.99),
-    (0.98, 220 * 0.98),
+@pytest.mark.parametrize('trademode', [TradingMode.FUTURES, TradingMode.SPOT])
+@pytest.mark.parametrize('limitratio,expected,side', [
+    (None, 220 * 0.99, "sell"),
+    (0.99, 220 * 0.99, "sell"),
+    (0.98, 220 * 0.98, "sell"),
+    (None, 220 * 1.01, "buy"),
+    (0.99, 220 * 1.01, "buy"),
+    (0.98, 220 * 1.02, "buy"),
 ])
-def test_stoploss_order_binance(default_conf, mocker, limitratio, expected):
+def test_stoploss_order_binance(default_conf, mocker, limitratio, expected, side, trademode):
     api_mock = MagicMock()
     order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
-    order_type = 'stop_loss_limit'
+    order_type = 'stop_loss_limit' if trademode == TradingMode.SPOT else 'stop'
 
     api_mock.create_order = MagicMock(return_value={
         'id': order_id,
@@ -27,45 +32,78 @@ def test_stoploss_order_binance(default_conf, mocker, limitratio, expected):
         }
     })
     default_conf['dry_run'] = False
+    default_conf['margin_mode'] = MarginMode.ISOLATED
+    default_conf['trading_mode'] = trademode
     mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
     mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
 
     with pytest.raises(OperationalException):
-        order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
-                                  order_types={'stoploss_on_exchange_limit_ratio': 1.05})
+        order = exchange.stoploss(
+            pair='ETH/BTC',
+            amount=1,
+            stop_price=190,
+            side=side,
+            order_types={'stoploss_on_exchange_limit_ratio': 1.05},
+            leverage=1.0
+        )
 
     api_mock.create_order.reset_mock()
     order_types = {} if limitratio is None else {'stoploss_on_exchange_limit_ratio': limitratio}
-    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types=order_types)
+    order = exchange.stoploss(
+        pair='ETH/BTC',
+        amount=1,
+        stop_price=220,
+        order_types=order_types,
+        side=side,
+        leverage=1.0
+    )
 
     assert 'id' in order
     assert 'info' in order
     assert order['id'] == order_id
     assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
     assert api_mock.create_order.call_args_list[0][1]['type'] == order_type
-    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['side'] == side
     assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
     # Price should be 1% below stopprice
     assert api_mock.create_order.call_args_list[0][1]['price'] == expected
-    assert api_mock.create_order.call_args_list[0][1]['params'] == {'stopPrice': 220}
+    if trademode == TradingMode.SPOT:
+        params_dict = {'stopPrice': 220}
+    else:
+        params_dict = {'stopPrice': 220, 'reduceOnly': True}
+    assert api_mock.create_order.call_args_list[0][1]['params'] == params_dict
 
     # test exception handling
     with pytest.raises(DependencyException):
         api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
-        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+        exchange.stoploss(
+            pair='ETH/BTC',
+            amount=1,
+            stop_price=220,
+            order_types={},
+            side=side,
+            leverage=1.0)
 
     with pytest.raises(InvalidOrderException):
         api_mock.create_order = MagicMock(
             side_effect=ccxt.InvalidOrder("binance Order would trigger immediately."))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
-        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+        exchange.stoploss(
+            pair='ETH/BTC',
+            amount=1,
+            stop_price=220,
+            order_types={},
+            side=side,
+            leverage=1.0
+        )
 
     ccxt_exceptionhandlers(mocker, default_conf, api_mock, "binance",
                            "stoploss", "create_order", retries=1,
-                           pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+                           pair='ETH/BTC', amount=1, stop_price=220, order_types={},
+                           side=side, leverage=1.0)
 
 
 def test_stoploss_order_dry_run_binance(default_conf, mocker):
@@ -78,12 +116,25 @@ def test_stoploss_order_dry_run_binance(default_conf, mocker):
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
 
     with pytest.raises(OperationalException):
-        order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
-                                  order_types={'stoploss_on_exchange_limit_ratio': 1.05})
+        order = exchange.stoploss(
+            pair='ETH/BTC',
+            amount=1,
+            stop_price=190,
+            side="sell",
+            order_types={'stoploss_on_exchange_limit_ratio': 1.05},
+            leverage=1.0
+        )
 
     api_mock.create_order.reset_mock()
 
-    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+    order = exchange.stoploss(
+        pair='ETH/BTC',
+        amount=1,
+        stop_price=220,
+        order_types={},
+        side="sell",
+        leverage=1.0
+    )
 
     assert 'id' in order
     assert 'info' in order
@@ -94,22 +145,383 @@ def test_stoploss_order_dry_run_binance(default_conf, mocker):
     assert order['amount'] == 1
 
 
-def test_stoploss_adjust_binance(mocker, default_conf):
+@pytest.mark.parametrize('sl1,sl2,sl3,side', [
+    (1501, 1499, 1501, "sell"),
+    (1499, 1501, 1499, "buy")
+])
+def test_stoploss_adjust_binance(mocker, default_conf, sl1, sl2, sl3, side):
     exchange = get_patched_exchange(mocker, default_conf, id='binance')
     order = {
         'type': 'stop_loss_limit',
         'price': 1500,
         'info': {'stopPrice': 1500},
     }
-    assert exchange.stoploss_adjust(1501, order)
-    assert not exchange.stoploss_adjust(1499, order)
+    assert exchange.stoploss_adjust(sl1, order, side=side)
+    assert not exchange.stoploss_adjust(sl2, order, side=side)
     # Test with invalid order case
     order['type'] = 'stop_loss'
-    assert not exchange.stoploss_adjust(1501, order)
+    assert not exchange.stoploss_adjust(sl3, order, side=side)
+
+
+def test_fill_leverage_tiers_binance(default_conf, mocker):
+    api_mock = MagicMock()
+    api_mock.fetch_leverage_tiers = MagicMock(return_value={
+        'ADA/BUSD': [
+            {
+                "tier": 1,
+                "notionalFloor": 0,
+                "notionalCap": 100000,
+                "maintenanceMarginRate": 0.025,
+                "maxLeverage": 20,
+                "info": {
+                    "bracket": "1",
+                    "initialLeverage": "20",
+                    "notionalCap": "100000",
+                    "notionalFloor": "0",
+                    "maintMarginRatio": "0.025",
+                    "cum": "0.0"
+                }
+            },
+            {
+                "tier": 2,
+                "notionalFloor": 100000,
+                "notionalCap": 500000,
+                "maintenanceMarginRate": 0.05,
+                "maxLeverage": 10,
+                "info": {
+                    "bracket": "2",
+                    "initialLeverage": "10",
+                    "notionalCap": "500000",
+                    "notionalFloor": "100000",
+                    "maintMarginRatio": "0.05",
+                    "cum": "2500.0"
+                }
+            },
+            {
+                "tier": 3,
+                "notionalFloor": 500000,
+                "notionalCap": 1000000,
+                "maintenanceMarginRate": 0.1,
+                "maxLeverage": 5,
+                "info": {
+                    "bracket": "3",
+                    "initialLeverage": "5",
+                    "notionalCap": "1000000",
+                    "notionalFloor": "500000",
+                    "maintMarginRatio": "0.1",
+                    "cum": "27500.0"
+                }
+            },
+            {
+                "tier": 4,
+                "notionalFloor": 1000000,
+                "notionalCap": 2000000,
+                "maintenanceMarginRate": 0.15,
+                "maxLeverage": 3,
+                "info": {
+                    "bracket": "4",
+                    "initialLeverage": "3",
+                    "notionalCap": "2000000",
+                    "notionalFloor": "1000000",
+                    "maintMarginRatio": "0.15",
+                    "cum": "77500.0"
+                }
+            },
+            {
+                "tier": 5,
+                "notionalFloor": 2000000,
+                "notionalCap": 5000000,
+                "maintenanceMarginRate": 0.25,
+                "maxLeverage": 2,
+                "info": {
+                    "bracket": "5",
+                    "initialLeverage": "2",
+                    "notionalCap": "5000000",
+                    "notionalFloor": "2000000",
+                    "maintMarginRatio": "0.25",
+                    "cum": "277500.0"
+                }
+            },
+            {
+                "tier": 6,
+                "notionalFloor": 5000000,
+                "notionalCap": 30000000,
+                "maintenanceMarginRate": 0.5,
+                "maxLeverage": 1,
+                "info": {
+                    "bracket": "6",
+                    "initialLeverage": "1",
+                    "notionalCap": "30000000",
+                    "notionalFloor": "5000000",
+                    "maintMarginRatio": "0.5",
+                    "cum": "1527500.0"
+                }
+            }
+        ],
+        "ZEC/USDT": [
+            {
+                "tier": 1,
+                "notionalFloor": 0,
+                "notionalCap": 50000,
+                "maintenanceMarginRate": 0.01,
+                "maxLeverage": 50,
+                "info": {
+                    "bracket": "1",
+                    "initialLeverage": "50",
+                    "notionalCap": "50000",
+                    "notionalFloor": "0",
+                    "maintMarginRatio": "0.01",
+                    "cum": "0.0"
+                }
+            },
+            {
+                "tier": 2,
+                "notionalFloor": 50000,
+                "notionalCap": 150000,
+                "maintenanceMarginRate": 0.025,
+                "maxLeverage": 20,
+                "info": {
+                    "bracket": "2",
+                    "initialLeverage": "20",
+                    "notionalCap": "150000",
+                    "notionalFloor": "50000",
+                    "maintMarginRatio": "0.025",
+                    "cum": "750.0"
+                }
+            },
+            {
+                "tier": 3,
+                "notionalFloor": 150000,
+                "notionalCap": 250000,
+                "maintenanceMarginRate": 0.05,
+                "maxLeverage": 10,
+                "info": {
+                    "bracket": "3",
+                    "initialLeverage": "10",
+                    "notionalCap": "250000",
+                    "notionalFloor": "150000",
+                    "maintMarginRatio": "0.05",
+                    "cum": "4500.0"
+                }
+            },
+            {
+                "tier": 4,
+                "notionalFloor": 250000,
+                "notionalCap": 500000,
+                "maintenanceMarginRate": 0.1,
+                "maxLeverage": 5,
+                "info": {
+                    "bracket": "4",
+                    "initialLeverage": "5",
+                    "notionalCap": "500000",
+                    "notionalFloor": "250000",
+                    "maintMarginRatio": "0.1",
+                    "cum": "17000.0"
+                }
+            },
+            {
+                "tier": 5,
+                "notionalFloor": 500000,
+                "notionalCap": 1000000,
+                "maintenanceMarginRate": 0.125,
+                "maxLeverage": 4,
+                "info": {
+                    "bracket": "5",
+                    "initialLeverage": "4",
+                    "notionalCap": "1000000",
+                    "notionalFloor": "500000",
+                    "maintMarginRatio": "0.125",
+                    "cum": "29500.0"
+                }
+            },
+            {
+                "tier": 6,
+                "notionalFloor": 1000000,
+                "notionalCap": 2000000,
+                "maintenanceMarginRate": 0.25,
+                "maxLeverage": 2,
+                "info": {
+                    "bracket": "6",
+                    "initialLeverage": "2",
+                    "notionalCap": "2000000",
+                    "notionalFloor": "1000000",
+                    "maintMarginRatio": "0.25",
+                    "cum": "154500.0"
+                }
+            },
+            {
+                "tier": 7,
+                "notionalFloor": 2000000,
+                "notionalCap": 30000000,
+                "maintenanceMarginRate": 0.5,
+                "maxLeverage": 1,
+                "info": {
+                    "bracket": "7",
+                    "initialLeverage": "1",
+                    "notionalCap": "30000000",
+                    "notionalFloor": "2000000",
+                    "maintMarginRatio": "0.5",
+                    "cum": "654500.0"
+                }
+            }
+        ],
+    })
+    default_conf['dry_run'] = False
+    default_conf['trading_mode'] = TradingMode.FUTURES
+    default_conf['margin_mode'] = MarginMode.ISOLATED
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance")
+    exchange.fill_leverage_tiers()
+
+    assert exchange._leverage_tiers == {
+        'ADA/BUSD': [
+            {
+                "min": 0,
+                "max": 100000,
+                "mmr": 0.025,
+                "lev": 20,
+                "maintAmt": 0.0
+            },
+            {
+                "min": 100000,
+                "max": 500000,
+                "mmr": 0.05,
+                "lev": 10,
+                "maintAmt": 2500.0
+            },
+            {
+                "min": 500000,
+                "max": 1000000,
+                "mmr": 0.1,
+                "lev": 5,
+                "maintAmt": 27500.0
+            },
+            {
+                "min": 1000000,
+                "max": 2000000,
+                "mmr": 0.15,
+                "lev": 3,
+                "maintAmt": 77500.0
+            },
+            {
+                "min": 2000000,
+                "max": 5000000,
+                "mmr": 0.25,
+                "lev": 2,
+                "maintAmt": 277500.0
+            },
+            {
+                "min": 5000000,
+                "max": 30000000,
+                "mmr": 0.5,
+                "lev": 1,
+                "maintAmt": 1527500.0
+            }
+        ],
+        "ZEC/USDT": [
+            {
+                'min': 0,
+                'max': 50000,
+                'mmr': 0.01,
+                'lev': 50,
+                'maintAmt': 0.0
+            },
+            {
+                'min': 50000,
+                'max': 150000,
+                'mmr': 0.025,
+                'lev': 20,
+                'maintAmt': 750.0
+            },
+            {
+                'min': 150000,
+                'max': 250000,
+                'mmr': 0.05,
+                'lev': 10,
+                'maintAmt': 4500.0
+            },
+            {
+                'min': 250000,
+                'max': 500000,
+                'mmr': 0.1,
+                'lev': 5,
+                'maintAmt': 17000.0
+            },
+            {
+                'min': 500000,
+                'max': 1000000,
+                'mmr': 0.125,
+                'lev': 4,
+                'maintAmt': 29500.0
+            },
+            {
+                'min': 1000000,
+                'max': 2000000,
+                'mmr': 0.25,
+                'lev': 2,
+                'maintAmt': 154500.0
+            },
+            {
+                'min': 2000000,
+                'max': 30000000,
+                'mmr': 0.5,
+                'lev': 1,
+                'maintAmt': 654500.0
+            },
+        ]
+    }
+
+    api_mock = MagicMock()
+    api_mock.load_leverage_tiers = MagicMock()
+    type(api_mock).has = PropertyMock(return_value={'fetchLeverageTiers': True})
+
+    ccxt_exceptionhandlers(
+        mocker,
+        default_conf,
+        api_mock,
+        "binance",
+        "fill_leverage_tiers",
+        "fetch_leverage_tiers",
+    )
+
+
+def test_fill_leverage_tiers_binance_dryrun(default_conf, mocker, leverage_tiers):
+    api_mock = MagicMock()
+    default_conf['trading_mode'] = TradingMode.FUTURES
+    default_conf['margin_mode'] = MarginMode.ISOLATED
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance")
+    exchange.fill_leverage_tiers()
+
+    leverage_tiers = leverage_tiers
+
+    for key, value in leverage_tiers.items():
+        assert exchange._leverage_tiers[key] == value
+
+
+def test__set_leverage_binance(mocker, default_conf):
+
+    api_mock = MagicMock()
+    api_mock.set_leverage = MagicMock()
+    type(api_mock).has = PropertyMock(return_value={'setLeverage': True})
+    default_conf['dry_run'] = False
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+    exchange._set_leverage(3.0, trading_mode=TradingMode.MARGIN)
+
+    ccxt_exceptionhandlers(
+        mocker,
+        default_conf,
+        api_mock,
+        "binance",
+        "_set_leverage",
+        "set_leverage",
+        pair="XRP/USDT",
+        leverage=5.0,
+        trading_mode=TradingMode.FUTURES
+    )
 
 
 @pytest.mark.asyncio
-async def test__async_get_historic_ohlcv_binance(default_conf, mocker, caplog):
+@pytest.mark.parametrize('candle_type', ['mark', ''])
+async def test__async_get_historic_ohlcv_binance(default_conf, mocker, caplog, candle_type):
     ohlcv = [
         [
             int((datetime.now(timezone.utc).timestamp() - 1000) * 1000),
@@ -126,15 +538,55 @@ async def test__async_get_historic_ohlcv_binance(default_conf, mocker, caplog):
     exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
 
     pair = 'ETH/BTC'
-    res = await exchange._async_get_historic_ohlcv(pair, "5m",
-                                                   1500000000000, is_new_pair=False)
+    respair, restf, restype, res = await exchange._async_get_historic_ohlcv(
+        pair, "5m", 1500000000000, is_new_pair=False, candle_type=candle_type)
+    assert respair == pair
+    assert restf == '5m'
+    assert restype == candle_type
     # Call with very old timestamp - causes tons of requests
     assert exchange._api_async.fetch_ohlcv.call_count > 400
     # assert res == ohlcv
     exchange._api_async.fetch_ohlcv.reset_mock()
-    res = await exchange._async_get_historic_ohlcv(pair, "5m", 1500000000000, is_new_pair=True)
+    _, _, _, res = await exchange._async_get_historic_ohlcv(
+        pair, "5m", 1500000000000, is_new_pair=True, candle_type=candle_type)
 
     # Called twice - one "init" call - and one to get the actual data.
     assert exchange._api_async.fetch_ohlcv.call_count == 2
     assert res == ohlcv
     assert log_has_re(r"Candle-data for ETH/BTC available starting with .*", caplog)
+
+
+@pytest.mark.parametrize("trading_mode,margin_mode,config", [
+    ("spot", "", {}),
+    ("margin", "cross", {"options": {"defaultType": "margin"}}),
+    ("futures", "isolated", {"options": {"defaultType": "future"}}),
+])
+def test__ccxt_config(default_conf, mocker, trading_mode, margin_mode, config):
+    default_conf['trading_mode'] = trading_mode
+    default_conf['margin_mode'] = margin_mode
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+    assert exchange._ccxt_config == config
+
+
+@pytest.mark.parametrize('pair,nominal_value,mm_ratio,amt', [
+    ("BNB/BUSD", 0.0, 0.025, 0),
+    ("BNB/USDT", 100.0, 0.0065, 0),
+    ("BTC/USDT", 170.30, 0.004, 0),
+    ("BNB/BUSD", 999999.9, 0.1, 27500.0),
+    ("BNB/USDT", 5000000.0, 0.15, 233035.0),
+    ("BTC/USDT", 600000000, 0.5, 1.997038E8),
+])
+def test_get_maintenance_ratio_and_amt_binance(
+    default_conf,
+    mocker,
+    leverage_tiers,
+    pair,
+    nominal_value,
+    mm_ratio,
+    amt,
+):
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+    exchange._leverage_tiers = leverage_tiers
+    (result_ratio, result_amt) = exchange.get_maintenance_ratio_and_amt(pair, nominal_value)
+    assert (round(result_ratio, 8), round(result_amt, 8)) == (mm_ratio, amt)
diff --git a/tests/exchange/test_bitpanda.py b/tests/exchange/test_bitpanda.py
new file mode 100644
index 000000000..4bd168e7e
--- /dev/null
+++ b/tests/exchange/test_bitpanda.py
@@ -0,0 +1,47 @@
+from datetime import datetime
+from unittest.mock import MagicMock
+
+from tests.conftest import get_patched_exchange
+
+
+def test_get_trades_for_order(default_conf, mocker):
+    exchange_name = 'bitpanda'
+    order_id = 'ABCD-ABCD'
+    since = datetime(2018, 5, 5, 0, 0, 0)
+    default_conf["dry_run"] = False
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    api_mock = MagicMock()
+
+    api_mock.fetch_my_trades = MagicMock(return_value=[{'id': 'TTR67E-3PFBD-76IISV',
+                                                        'order': 'ABCD-ABCD',
+                                                        'info': {'pair': 'XLTCZBTC',
+                                                                 'time': 1519860024.4388,
+                                                                 'type': 'buy',
+                                                                 'ordertype': 'limit',
+                                                                 'price': '20.00000',
+                                                                 'cost': '38.62000',
+                                                                 'fee': '0.06179',
+                                                                 'vol': '5',
+                                                                 'id': 'ABCD-ABCD'},
+                                                        'timestamp': 1519860024438,
+                                                        'datetime': '2018-02-28T23:20:24.438Z',
+                                                        'symbol': 'LTC/BTC',
+                                                        'type': 'limit',
+                                                        'side': 'buy',
+                                                        'price': 165.0,
+                                                        'amount': 0.2340606,
+                                                        'fee': {'cost': 0.06179, 'currency': 'BTC'}
+                                                        }])
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    orders = exchange.get_trades_for_order(order_id, 'LTC/BTC', since)
+    assert len(orders) == 1
+    assert orders[0]['price'] == 165
+    assert api_mock.fetch_my_trades.call_count == 1
+    # since argument should be
+    assert isinstance(api_mock.fetch_my_trades.call_args[0][1], int)
+    assert api_mock.fetch_my_trades.call_args[0][0] == 'LTC/BTC'
+    # Same test twice, hardcoded number and doing the same calculation
+    assert api_mock.fetch_my_trades.call_args[0][1] == 1525478395000
+    # bitpanda requires "to" argument.
+    assert 'to' in api_mock.fetch_my_trades.call_args[1]['params']
diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange/test_ccxt_compat.py
index d71dbe015..14e45c8b0 100644
--- a/tests/exchange/test_ccxt_compat.py
+++ b/tests/exchange/test_ccxt_compat.py
@@ -5,69 +5,141 @@ However, these tests should give a good idea to determine if a new exchange is
 suitable to run with freqtrade.
 """
 
+from copy import deepcopy
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
 
 import pytest
 
+from freqtrade.enums import CandleType
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_prev_date
 from freqtrade.resolvers.exchange_resolver import ExchangeResolver
-from tests.conftest import get_default_conf
+from tests.conftest import get_default_conf_usdt
 
 
 # Exchanges that should be tested
 EXCHANGES = {
     'bittrex': {
         'pair': 'BTC/USDT',
+        'stake_currency': 'USDT',
         'hasQuoteVolume': False,
         'timeframe': '1h',
+        'leverage_tiers_public': False,
+        'leverage_in_spot_market': False,
     },
     'binance': {
         'pair': 'BTC/USDT',
+        'stake_currency': 'USDT',
         'hasQuoteVolume': True,
         'timeframe': '5m',
+        'futures': True,
+        'leverage_tiers_public': False,
+        'leverage_in_spot_market': False,
     },
     'kraken': {
         'pair': 'BTC/USDT',
+        'stake_currency': 'USDT',
         'hasQuoteVolume': True,
         'timeframe': '5m',
+        'leverage_tiers_public': False,
+        'leverage_in_spot_market': True,
     },
     'ftx': {
-        'pair': 'BTC/USDT',
+        'pair': 'BTC/USD',
+        'stake_currency': 'USD',
         'hasQuoteVolume': True,
         'timeframe': '5m',
+        'futures_pair': 'BTC/USD:USD',
+        'futures': False,
+        'leverage_tiers_public': False,  # TODO: Set to True once implemented on CCXT
+        'leverage_in_spot_market': True,
     },
     'kucoin': {
         'pair': 'BTC/USDT',
+        'stake_currency': 'USDT',
         'hasQuoteVolume': True,
         'timeframe': '5m',
+        'leverage_tiers_public': False,
+        'leverage_in_spot_market': True,
     },
     'gateio': {
         'pair': 'BTC/USDT',
+        'stake_currency': 'USDT',
         'hasQuoteVolume': True,
         'timeframe': '5m',
+        'futures': True,
+        'futures_pair': 'BTC/USDT:USDT',
+        'leverage_tiers_public': True,
+        'leverage_in_spot_market': True,
+    },
+    'okx': {
+        'pair': 'BTC/USDT',
+        'stake_currency': 'USDT',
+        'hasQuoteVolume': True,
+        'timeframe': '5m',
+        'futures_pair': 'BTC/USDT:USDT',
+        'futures': True,
+        'leverage_tiers_public': True,
+        'leverage_in_spot_market': True,
+    },
+    'huobi': {
+        'pair': 'BTC/USDT',
+        'stake_currency': 'USDT',
+        'hasQuoteVolume': True,
+        'timeframe': '5m',
+        'futures': False,
+    },
+    'bitvavo': {
+        'pair': 'BTC/EUR',
+        'stake_currency': 'EUR',
+        'hasQuoteVolume': True,
+        'timeframe': '5m',
+        'leverage_tiers_public': False,
+        'leverage_in_spot_market': False,
     },
 }
 
 
 @pytest.fixture(scope="class")
 def exchange_conf():
-    config = get_default_conf((Path(__file__).parent / "testdata").resolve())
+    config = get_default_conf_usdt((Path(__file__).parent / "testdata").resolve())
     config['exchange']['pair_whitelist'] = []
     config['exchange']['key'] = ''
     config['exchange']['secret'] = ''
     config['dry_run'] = False
+    config['entry_pricing']['use_order_book'] = True
+    config['exit_pricing']['use_order_book'] = True
     return config
 
 
 @pytest.fixture(params=EXCHANGES, scope="class")
 def exchange(request, exchange_conf):
     exchange_conf['exchange']['name'] = request.param
+    exchange_conf['stake_currency'] = EXCHANGES[request.param]['stake_currency']
     exchange = ExchangeResolver.load_exchange(request.param, exchange_conf, validate=True)
 
     yield exchange, request.param
 
 
+@pytest.fixture(params=EXCHANGES, scope="class")
+def exchange_futures(request, exchange_conf, class_mocker):
+    if not EXCHANGES[request.param].get('futures') is True:
+        yield None, request.param
+    else:
+        exchange_conf = deepcopy(exchange_conf)
+        exchange_conf['exchange']['name'] = request.param
+        exchange_conf['trading_mode'] = 'futures'
+        exchange_conf['margin_mode'] = 'isolated'
+        exchange_conf['stake_currency'] = EXCHANGES[request.param]['stake_currency']
+
+        class_mocker.patch(
+            'freqtrade.exchange.binance.Binance.fill_leverage_tiers')
+        class_mocker.patch('freqtrade.exchange.exchange.Exchange.fetch_trading_fees')
+        exchange = ExchangeResolver.load_exchange(request.param, exchange_conf, validate=True)
+
+        yield exchange, request.param
+
+
 @pytest.mark.longrun
 class TestCCXTExchange():
 
@@ -77,6 +149,20 @@ class TestCCXTExchange():
         markets = exchange.markets
         assert pair in markets
         assert isinstance(markets[pair], dict)
+        assert exchange.market_is_spot(markets[pair])
+
+    def test_load_markets_futures(self, exchange_futures):
+        exchange, exchangename = exchange_futures
+        if not exchange:
+            # exchange_futures only returns values for supported exchanges
+            return
+        pair = EXCHANGES[exchangename]['pair']
+        pair = EXCHANGES[exchangename].get('futures_pair', pair)
+        markets = exchange.markets
+        assert pair in markets
+        assert isinstance(markets[pair], dict)
+
+        assert exchange.market_is_future(markets[pair])
 
     def test_ccxt_fetch_tickers(self, exchange):
         exchange, exchangename = exchange
@@ -121,7 +207,10 @@ class TestCCXTExchange():
             else:
                 next_limit = exchange.get_next_limit_in_list(
                     val, l2_limit_range, l2_limit_range_required)
-                if next_limit is None or next_limit > 200:
+                if next_limit is None:
+                    assert len(l2['asks']) > 100
+                    assert len(l2['asks']) > 100
+                elif next_limit > 200:
                     # Large orderbook sizes can be a problem for some exchanges (bitrex ...)
                     assert len(l2['asks']) > 200
                     assert len(l2['asks']) > 200
@@ -133,7 +222,9 @@ class TestCCXTExchange():
         exchange, exchangename = exchange
         pair = EXCHANGES[exchangename]['pair']
         timeframe = EXCHANGES[exchangename]['timeframe']
-        pair_tf = (pair, timeframe)
+
+        pair_tf = (pair, timeframe, CandleType.SPOT)
+
         ohlcv = exchange.refresh_latest_ohlcv([pair_tf])
         assert isinstance(ohlcv, dict)
         assert len(ohlcv[pair_tf]) == len(exchange.klines(pair_tf))
@@ -144,6 +235,82 @@ class TestCCXTExchange():
         now = datetime.now(timezone.utc) - timedelta(minutes=(timeframe_to_minutes(timeframe) * 2))
         assert exchange.klines(pair_tf).iloc[-1]['date'] >= timeframe_to_prev_date(timeframe, now)
 
+    def test_ccxt_fetch_funding_rate_history(self, exchange_futures):
+        exchange, exchangename = exchange_futures
+        if not exchange:
+            # exchange_futures only returns values for supported exchanges
+            return
+
+        pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair'])
+        since = int((datetime.now(timezone.utc) - timedelta(days=5)).timestamp() * 1000)
+        timeframe_ff = exchange._ft_has.get('funding_fee_timeframe',
+                                            exchange._ft_has['mark_ohlcv_timeframe'])
+        pair_tf = (pair, timeframe_ff, CandleType.FUNDING_RATE)
+
+        funding_ohlcv = exchange.refresh_latest_ohlcv(
+            [pair_tf],
+            since_ms=since,
+            drop_incomplete=False)
+
+        assert isinstance(funding_ohlcv, dict)
+        rate = funding_ohlcv[pair_tf]
+
+        this_hour = timeframe_to_prev_date(timeframe_ff)
+        hour1 = timeframe_to_prev_date(timeframe_ff, this_hour - timedelta(minutes=1))
+        hour2 = timeframe_to_prev_date(timeframe_ff, hour1 - timedelta(minutes=1))
+        hour3 = timeframe_to_prev_date(timeframe_ff, hour2 - timedelta(minutes=1))
+        val0 = rate[rate['date'] == this_hour].iloc[0]['open']
+        val1 = rate[rate['date'] == hour1].iloc[0]['open']
+        val2 = rate[rate['date'] == hour2].iloc[0]['open']
+        val3 = rate[rate['date'] == hour3].iloc[0]['open']
+
+        # Test For last 4 hours
+        # Avoids random test-failure when funding-fees are 0 for a few hours.
+        assert val0 != 0.0 or val1 != 0.0 or val2 != 0.0 or val3 != 0.0
+        # We expect funding rates to be different from 0.0 - or moving around.
+        assert (
+            rate['open'].max() != 0.0 or rate['open'].min() != 0.0 or
+            (rate['open'].min() != rate['open'].max())
+        )
+
+    def test_ccxt_fetch_mark_price_history(self, exchange_futures):
+        exchange, exchangename = exchange_futures
+        if not exchange:
+            # exchange_futures only returns values for supported exchanges
+            return
+        pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair'])
+        since = int((datetime.now(timezone.utc) - timedelta(days=5)).timestamp() * 1000)
+        pair_tf = (pair, '1h', CandleType.MARK)
+
+        mark_ohlcv = exchange.refresh_latest_ohlcv(
+            [pair_tf],
+            since_ms=since,
+            drop_incomplete=False)
+
+        assert isinstance(mark_ohlcv, dict)
+        expected_tf = '1h'
+        mark_candles = mark_ohlcv[pair_tf]
+
+        this_hour = timeframe_to_prev_date(expected_tf)
+        prev_hour = timeframe_to_prev_date(expected_tf, this_hour - timedelta(minutes=1))
+
+        assert mark_candles[mark_candles['date'] == prev_hour].iloc[0]['open'] != 0.0
+        assert mark_candles[mark_candles['date'] == this_hour].iloc[0]['open'] != 0.0
+
+    def test_ccxt__calculate_funding_fees(self, exchange_futures):
+        exchange, exchangename = exchange_futures
+        if not exchange:
+            # exchange_futures only returns values for supported exchanges
+            return
+        pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair'])
+        since = datetime.now(timezone.utc) - timedelta(days=5)
+
+        funding_fee = exchange._fetch_and_calculate_funding_fees(
+            pair, 20, is_short=False, open_date=since)
+
+        assert isinstance(funding_fee, float)
+        # assert funding_fee > 0
+
     # TODO: tests fetch_trades (?)
 
     def test_ccxt_get_fee(self, exchange):
@@ -154,3 +321,110 @@ class TestCCXTExchange():
         assert 0 < exchange.get_fee(pair, 'limit', 'sell') < threshold
         assert 0 < exchange.get_fee(pair, 'market', 'buy') < threshold
         assert 0 < exchange.get_fee(pair, 'market', 'sell') < threshold
+
+    def test_ccxt_get_max_leverage_spot(self, exchange):
+        spot, spot_name = exchange
+        if spot:
+            leverage_in_market_spot = EXCHANGES[spot_name].get('leverage_in_spot_market')
+            if leverage_in_market_spot:
+                spot_pair = EXCHANGES[spot_name].get('pair', EXCHANGES[spot_name]['pair'])
+                spot_leverage = spot.get_max_leverage(spot_pair, 20)
+                assert (isinstance(spot_leverage, float) or isinstance(spot_leverage, int))
+                assert spot_leverage >= 1.0
+
+    def test_ccxt_get_max_leverage_futures(self, exchange_futures):
+        futures, futures_name = exchange_futures
+        if futures:
+            leverage_tiers_public = EXCHANGES[futures_name].get('leverage_tiers_public')
+            if leverage_tiers_public:
+                futures_pair = EXCHANGES[futures_name].get(
+                    'futures_pair',
+                    EXCHANGES[futures_name]['pair']
+                )
+                futures_leverage = futures.get_max_leverage(futures_pair, 20)
+                assert (isinstance(futures_leverage, float) or isinstance(futures_leverage, int))
+                assert futures_leverage >= 1.0
+
+    def test_ccxt__get_contract_size(self, exchange_futures):
+        futures, futures_name = exchange_futures
+        if futures:
+            futures_pair = EXCHANGES[futures_name].get(
+                'futures_pair',
+                EXCHANGES[futures_name]['pair']
+            )
+            contract_size = futures._get_contract_size(futures_pair)
+            assert (isinstance(contract_size, float) or isinstance(contract_size, int))
+            assert contract_size >= 0.0
+
+    def test_ccxt_load_leverage_tiers(self, exchange_futures):
+        futures, futures_name = exchange_futures
+        if futures and EXCHANGES[futures_name].get('leverage_tiers_public'):
+            leverage_tiers = futures.load_leverage_tiers()
+            futures_pair = EXCHANGES[futures_name].get(
+                'futures_pair',
+                EXCHANGES[futures_name]['pair']
+            )
+            assert (isinstance(leverage_tiers, dict))
+            assert futures_pair in leverage_tiers
+            pair_tiers = leverage_tiers[futures_pair]
+            assert len(pair_tiers) > 0
+            oldLeverage = float('inf')
+            oldMaintenanceMarginRate = oldNotionalFloor = oldNotionalCap = -1
+            for tier in pair_tiers:
+                for key in [
+                    'maintenanceMarginRate',
+                    'notionalFloor',
+                    'notionalCap',
+                    'maxLeverage'
+                ]:
+                    assert key in tier
+                    assert tier[key] >= 0.0
+                assert tier['notionalCap'] > tier['notionalFloor']
+                assert tier['maxLeverage'] <= oldLeverage
+                assert tier['maintenanceMarginRate'] >= oldMaintenanceMarginRate
+                assert tier['notionalFloor'] > oldNotionalFloor
+                assert tier['notionalCap'] > oldNotionalCap
+                oldLeverage = tier['maxLeverage']
+                oldMaintenanceMarginRate = tier['maintenanceMarginRate']
+                oldNotionalFloor = tier['notionalFloor']
+                oldNotionalCap = tier['notionalCap']
+
+    def test_ccxt_dry_run_liquidation_price(self, exchange_futures):
+        futures, futures_name = exchange_futures
+        if futures and EXCHANGES[futures_name].get('leverage_tiers_public'):
+
+            futures_pair = EXCHANGES[futures_name].get(
+                'futures_pair',
+                EXCHANGES[futures_name]['pair']
+            )
+
+            liquidation_price = futures.dry_run_liquidation_price(
+                futures_pair,
+                40000,
+                False,
+                100,
+                100,
+            )
+            assert (isinstance(liquidation_price, float))
+            assert liquidation_price >= 0.0
+
+            liquidation_price = futures.dry_run_liquidation_price(
+                futures_pair,
+                40000,
+                False,
+                100,
+                100,
+            )
+            assert (isinstance(liquidation_price, float))
+            assert liquidation_price >= 0.0
+
+    def test_ccxt_get_max_pair_stake_amount(self, exchange_futures):
+        futures, futures_name = exchange_futures
+        if futures:
+            futures_pair = EXCHANGES[futures_name].get(
+                'futures_pair',
+                EXCHANGES[futures_name]['pair']
+            )
+            max_stake_amount = futures.get_max_pair_stake_amount(futures_pair, 40000)
+            assert (isinstance(max_stake_amount, float))
+            assert max_stake_amount >= 0.0
diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py
index 97bc33429..e99121489 100644
--- a/tests/exchange/test_exchange.py
+++ b/tests/exchange/test_exchange.py
@@ -11,6 +11,7 @@ import ccxt
 import pytest
 from pandas import DataFrame
 
+from freqtrade.enums import CandleType, MarginMode, TradingMode
 from freqtrade.exceptions import (DDosProtection, DependencyException, InvalidOrderException,
                                   OperationalException, PricingError, TemporaryError)
 from freqtrade.exchange import Binance, Bittrex, Exchange, Kraken
@@ -20,11 +21,11 @@ from freqtrade.exchange.exchange import (market_is_active, timeframe_to_minutes,
                                          timeframe_to_next_date, timeframe_to_prev_date,
                                          timeframe_to_seconds)
 from freqtrade.resolvers.exchange_resolver import ExchangeResolver
-from tests.conftest import get_mock_coro, get_patched_exchange, log_has, log_has_re
+from tests.conftest import get_mock_coro, get_patched_exchange, log_has, log_has_re, num_log_has_re
 
 
 # Make sure to always keep one exchange here which is NOT subclassed!!
-EXCHANGES = ['bittrex', 'binance', 'kraken', 'ftx']
+EXCHANGES = ['bittrex', 'binance', 'kraken', 'ftx', 'gateio']
 
 
 def ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
@@ -131,6 +132,7 @@ def test_init_ccxt_kwargs(default_conf, mocker, caplog):
 
     assert log_has("Applying additional ccxt config: {'TestKWARG': 11, 'TestKWARG44': 11}", caplog)
     assert ex._api.headers == {'hello': 'world'}
+    assert ex._ccxt_config == {}
     Exchange._headers = {}
 
 
@@ -165,8 +167,9 @@ def test_exchange_resolver(default_conf, mocker, caplog):
     mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
 
-    exchange = ExchangeResolver.load_exchange('huobi', default_conf)
+    exchange = ExchangeResolver.load_exchange('zaif', default_conf)
     assert isinstance(exchange, Exchange)
     assert log_has_re(r"No .* specific subclass found. Using the generic class instead.", caplog)
     caplog.clear()
@@ -222,27 +225,50 @@ def test_validate_order_time_in_force(default_conf, mocker, caplog):
     ex.validate_order_time_in_force(tif2)
 
 
-@pytest.mark.parametrize("amount,precision_mode,precision,expected", [
-    (2.34559, 2, 4, 2.3455),
-    (2.34559, 2, 5, 2.34559),
-    (2.34559, 2, 3, 2.345),
-    (2.9999, 2, 3, 2.999),
-    (2.9909, 2, 3, 2.990),
+@pytest.mark.parametrize("amount,precision_mode,precision,contract_size,expected,trading_mode", [
+    (2.34559, 2, 4, 1, 2.3455, 'spot'),
+    (2.34559, 2, 5, 1, 2.34559, 'spot'),
+    (2.34559, 2, 3, 1, 2.345, 'spot'),
+    (2.9999, 2, 3, 1, 2.999, 'spot'),
+    (2.9909, 2, 3, 1, 2.990, 'spot'),
+    (2.9909, 2, 0, 1, 2, 'spot'),
+    (29991.5555, 2, 0, 1, 29991, 'spot'),
+    (29991.5555, 2, -1, 1, 29990, 'spot'),
+    (29991.5555, 2, -2, 1, 29900, 'spot'),
     # Tests for Tick-size
-    (2.34559, 4, 0.0001, 2.3455),
-    (2.34559, 4, 0.00001, 2.34559),
-    (2.34559, 4, 0.001, 2.345),
-    (2.9999, 4, 0.001, 2.999),
-    (2.9909, 4, 0.001, 2.990),
-    (2.9909, 4, 0.005, 2.990),
-    (2.9999, 4, 0.005, 2.995),
+    (2.34559, 4, 0.0001, 1, 2.3455, 'spot'),
+    (2.34559, 4, 0.00001, 1, 2.34559, 'spot'),
+    (2.34559, 4, 0.001, 1, 2.345, 'spot'),
+    (2.9999, 4, 0.001, 1, 2.999, 'spot'),
+    (2.9909, 4, 0.001, 1, 2.990, 'spot'),
+    (2.9909, 4, 0.005, 0.01, 2.99, 'futures'),
+    (2.9999, 4, 0.005, 10, 2.995, 'futures'),
 ])
-def test_amount_to_precision(default_conf, mocker, amount, precision_mode, precision, expected):
-    '''
+def test_amount_to_precision(
+    default_conf,
+    mocker,
+    amount,
+    precision_mode,
+    precision,
+    contract_size,
+    expected,
+    trading_mode
+):
+    """
     Test rounds down
-    '''
+    """
 
-    markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'amount': precision}}})
+    markets = PropertyMock(return_value={
+        'ETH/BTC': {
+            'contractSize': contract_size,
+            'precision': {
+                'amount': precision
+            }
+        }
+    })
+
+    default_conf['trading_mode'] = trading_mode
+    default_conf['margin_mode'] = 'isolated'
 
     exchange = get_patched_exchange(mocker, default_conf, id="binance")
     # digits counting mode
@@ -275,12 +301,11 @@ def test_amount_to_precision(default_conf, mocker, amount, precision_mode, preci
     (234.43, 4, 0.5, 234.5),
     (234.53, 4, 0.5, 235.0),
     (0.891534, 4, 0.0001, 0.8916),
+    (64968.89, 4, 0.01, 64968.89),
 
 ])
 def test_price_to_precision(default_conf, mocker, price, precision_mode, precision, expected):
-    '''
-    Test price to precision
-    '''
+    """Test price to precision"""
     markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'price': precision}}})
 
     exchange = get_patched_exchange(mocker, default_conf, id="binance")
@@ -293,7 +318,7 @@ def test_price_to_precision(default_conf, mocker, price, precision_mode, precisi
                  PropertyMock(return_value=precision_mode))
 
     pair = 'ETH/BTC'
-    assert pytest.approx(exchange.price_to_precision(pair, price)) == expected
+    assert exchange.price_to_precision(pair, price) == expected
 
 
 @pytest.mark.parametrize("price,precision_mode,precision,expected", [
@@ -322,7 +347,7 @@ def test_price_get_one_pip(default_conf, mocker, price, precision_mode, precisio
     assert pytest.approx(exchange.price_get_one_pip(pair, price)) == expected
 
 
-def test_get_min_pair_stake_amount(mocker, default_conf) -> None:
+def test__get_stake_amount_limit(mocker, default_conf) -> None:
 
     exchange = get_patched_exchange(mocker, default_conf, id="binance")
     stoploss = -0.05
@@ -336,23 +361,10 @@ def test_get_min_pair_stake_amount(mocker, default_conf) -> None:
     with pytest.raises(ValueError, match=r'.*get market information.*'):
         exchange.get_min_pair_stake_amount('BNB/BTC', 1, stoploss)
 
-    # no 'limits' section
-    result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss)
-    assert result is None
-
-    # empty 'limits' section
-    markets["ETH/BTC"]["limits"] = {}
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss)
-    assert result is None
-
-    # no cost Min
+    # no cost/amount Min
     markets["ETH/BTC"]["limits"] = {
-        'cost': {"min": None},
-        'amount': {}
+        'cost': {'min': None, 'max': None},
+        'amount': {'min': None, 'max': None},
     }
     mocker.patch(
         'freqtrade.exchange.Exchange.markets',
@@ -360,85 +372,131 @@ def test_get_min_pair_stake_amount(mocker, default_conf) -> None:
     )
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss)
     assert result is None
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 1)
+    assert result == float('inf')
 
-    # no amount Min
+    # min/max cost is set
     markets["ETH/BTC"]["limits"] = {
-        'cost': {},
-        'amount': {"min": None}
+        'cost': {'min': 2, 'max': 10000},
+        'amount': {'min': None, 'max': None},
     }
     mocker.patch(
         'freqtrade.exchange.Exchange.markets',
         PropertyMock(return_value=markets)
     )
+    # min
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss)
-    assert result is None
-
-    # empty 'cost'/'amount' section
-    markets["ETH/BTC"]["limits"] = {
-        'cost': {},
-        'amount': {}
-    }
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss)
-    assert result is None
-
-    # min cost is set
-    markets["ETH/BTC"]["limits"] = {
-        'cost': {'min': 2},
-        'amount': {}
-    }
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss)
-    assert isclose(result, 2 * (1+0.05) / (1-abs(stoploss)))
+    expected_result = 2 * (1 + 0.05) / (1 - abs(stoploss))
+    assert isclose(result, expected_result)
+    # With Leverage
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 1, stoploss, 3.0)
+    assert isclose(result, expected_result / 3)
+    # max
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 2)
+    assert result == 10000
 
     # min amount is set
     markets["ETH/BTC"]["limits"] = {
-        'cost': {},
-        'amount': {'min': 2}
+        'cost': {'min': None, 'max': None},
+        'amount': {'min': 2, 'max': 10000},
     }
     mocker.patch(
         'freqtrade.exchange.Exchange.markets',
         PropertyMock(return_value=markets)
     )
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss)
-    assert isclose(result, 2 * 2 * (1+0.05) / (1-abs(stoploss)))
+    expected_result = 2 * 2 * (1 + 0.05) / (1 - abs(stoploss))
+    assert isclose(result, expected_result)
+    # With Leverage
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss, 5.0)
+    assert isclose(result, expected_result / 5)
+    # max
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 2)
+    assert result == 20000
 
     # min amount and cost are set (cost is minimal)
     markets["ETH/BTC"]["limits"] = {
-        'cost': {'min': 2},
-        'amount': {'min': 2}
+        'cost': {'min': 2, 'max': None},
+        'amount': {'min': 2, 'max': None},
     }
     mocker.patch(
         'freqtrade.exchange.Exchange.markets',
         PropertyMock(return_value=markets)
     )
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss)
-    assert isclose(result, max(2, 2 * 2) * (1+0.05) / (1-abs(stoploss)))
+    expected_result = max(2, 2 * 2) * (1 + 0.05) / (1 - abs(stoploss))
+    assert isclose(result, expected_result)
+    # With Leverage
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss, 10)
+    assert isclose(result, expected_result / 10)
 
     # min amount and cost are set (amount is minial)
     markets["ETH/BTC"]["limits"] = {
-        'cost': {'min': 8},
-        'amount': {'min': 2}
+        'cost': {'min': 8, 'max': 10000},
+        'amount': {'min': 2, 'max': 500},
     }
     mocker.patch(
         'freqtrade.exchange.Exchange.markets',
         PropertyMock(return_value=markets)
     )
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss)
-    assert isclose(result, max(8, 2 * 2) * (1+0.05) / (1-abs(stoploss)))
+    expected_result = max(8, 2 * 2) * (1 + 0.05) / (1 - abs(stoploss))
+    assert isclose(result, expected_result)
+    # With Leverage
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, stoploss, 7.0)
+    assert isclose(result, expected_result / 7.0)
+    # Max
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 2)
+    assert result == 1000
 
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -0.4)
-    assert isclose(result, max(8, 2 * 2) * 1.5)
+    expected_result = max(8, 2 * 2) * 1.5
+    assert isclose(result, expected_result)
+    # With Leverage
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -0.4, 8.0)
+    assert isclose(result, expected_result / 8.0)
+    # Max
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 2)
+    assert result == 1000
 
     # Really big stoploss
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1)
-    assert isclose(result, max(8, 2 * 2) * 1.5)
+    expected_result = max(8, 2 * 2) * 1.5
+    assert isclose(result, expected_result)
+    # With Leverage
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1, 12.0)
+    assert isclose(result, expected_result / 12)
+    # Max
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 2)
+    assert result == 1000
+
+    markets["ETH/BTC"]["contractSize"] = '0.01'
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+
+    # Contract size 0.01
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1)
+    assert isclose(result, expected_result * 0.01)
+    # Max
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 2)
+    assert result == 10
+
+    markets["ETH/BTC"]["contractSize"] = '10'
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    # With Leverage, Contract size 10
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 2, -1, 12.0)
+    assert isclose(result, (expected_result / 12) * 10.0)
+    # Max
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 2)
+    assert result == 10000
 
 
 def test_get_min_pair_stake_amount_real_data(mocker, default_conf) -> None:
@@ -446,20 +504,34 @@ def test_get_min_pair_stake_amount_real_data(mocker, default_conf) -> None:
     stoploss = -0.05
     markets = {'ETH/BTC': {'symbol': 'ETH/BTC'}}
 
-    # Real Binance data
+    # ~Real Binance data
     markets["ETH/BTC"]["limits"] = {
-        'cost': {'min': 0.0001},
-        'amount': {'min': 0.001}
+        'cost': {'min': 0.0001, 'max': 4000},
+        'amount': {'min': 0.001, 'max': 10000},
     }
     mocker.patch(
         'freqtrade.exchange.Exchange.markets',
         PropertyMock(return_value=markets)
     )
     result = exchange.get_min_pair_stake_amount('ETH/BTC', 0.020405, stoploss)
-    assert round(result, 8) == round(
-        max(0.0001, 0.001 * 0.020405) * (1+0.05) / (1-abs(stoploss)),
-        8
-    )
+    expected_result = max(0.0001, 0.001 * 0.020405) * (1 + 0.05) / (1 - abs(stoploss))
+    assert round(result, 8) == round(expected_result, 8)
+    # Max
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 2.0)
+    assert result == 4000
+
+    # Leverage
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 0.020405, stoploss, 3.0)
+    assert round(result, 8) == round(expected_result / 3, 8)
+
+    # Contract_size
+    markets["ETH/BTC"]["contractSize"] = 0.1
+    result = exchange.get_min_pair_stake_amount('ETH/BTC', 0.020405, stoploss, 3.0)
+    assert round(result, 8) == round((expected_result / 3), 8)
+
+    # Max
+    result = exchange.get_max_pair_stake_amount('ETH/BTC', 12.0)
+    assert result == 4000
 
 
 def test_set_sandbox(default_conf, mocker):
@@ -503,6 +575,7 @@ def test__load_async_markets(default_conf, mocker, caplog):
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange._load_markets')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     exchange = Exchange(default_conf)
     exchange._api_async.load_markets = get_mock_coro(None)
     exchange._load_async_markets()
@@ -524,6 +597,7 @@ def test__load_markets(default_conf, mocker, caplog):
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     Exchange(default_conf)
     assert log_has('Unable to initialize markets.', caplog)
 
@@ -592,6 +666,7 @@ def test_validate_stakecurrency(default_conf, stake_currency, mocker, caplog):
     mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     Exchange(default_conf)
 
 
@@ -622,7 +697,7 @@ def test_validate_stakecurrency_error(default_conf, mocker, caplog):
 def test_get_quote_currencies(default_conf, mocker):
     ex = get_patched_exchange(mocker, default_conf)
 
-    assert set(ex.get_quote_currencies()) == set(['USD', 'ETH', 'BTC', 'USDT'])
+    assert set(ex.get_quote_currencies()) == set(['USD', 'ETH', 'BTC', 'USDT', 'BUSD'])
 
 
 @pytest.mark.parametrize('pair,expected', [
@@ -664,6 +739,7 @@ def test_validate_pairs(default_conf, mocker):  # test exchange.validate_pairs d
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     Exchange(default_conf)
 
 
@@ -690,6 +766,7 @@ def test_validate_pairs_exception(default_conf, mocker, caplog):
     mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
 
     with pytest.raises(OperationalException, match=r'Pair ETH/BTC is not available on Binance'):
@@ -710,6 +787,7 @@ def test_validate_pairs_restricted(default_conf, mocker, caplog):
     mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
 
     Exchange(default_conf)
@@ -729,6 +807,7 @@ def test_validate_pairs_stakecompatibility(default_conf, mocker, caplog):
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
 
     Exchange(default_conf)
 
@@ -745,6 +824,7 @@ def test_validate_pairs_stakecompatibility_downloaddata(default_conf, mocker, ca
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
 
     Exchange(default_conf)
     assert type(api_mock).load_markets.call_count == 1
@@ -785,6 +865,7 @@ def test_validate_timeframes(default_conf, mocker, timeframe):
     mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
     mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     Exchange(default_conf)
 
 
@@ -869,10 +950,49 @@ def test_validate_timeframes_not_in_config(default_conf, mocker):
     mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
     mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     Exchange(default_conf)
 
 
-def test_validate_order_types(default_conf, mocker):
+def test_validate_pricing(default_conf, mocker):
+    api_mock = MagicMock()
+    has = {
+        'fetchL2OrderBook': True,
+        'fetchTicker': True,
+    }
+    type(api_mock).has = PropertyMock(return_value=has)
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.exchange.Exchange.validate_trading_mode_and_margin_mode')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.name', 'Binance')
+    ExchangeResolver.load_exchange('binance', default_conf)
+    has.update({'fetchTicker': False})
+    with pytest.raises(OperationalException, match="Ticker pricing not available for .*"):
+        ExchangeResolver.load_exchange('binance', default_conf)
+
+    has.update({'fetchTicker': True})
+
+    default_conf['exit_pricing']['use_order_book'] = True
+    ExchangeResolver.load_exchange('binance', default_conf)
+    has.update({'fetchL2OrderBook': False})
+
+    with pytest.raises(OperationalException, match="Orderbook not available for .*"):
+        ExchangeResolver.load_exchange('binance', default_conf)
+
+    has.update({'fetchL2OrderBook': True})
+
+    # Binance has no tickers on futures
+    default_conf['trading_mode'] = TradingMode.FUTURES
+    default_conf['margin_mode'] = MarginMode.ISOLATED
+
+    with pytest.raises(OperationalException, match="Ticker pricing not available for .*"):
+        ExchangeResolver.load_exchange('binance', default_conf)
+
+
+def test_validate_ordertypes(default_conf, mocker):
     api_mock = MagicMock()
 
     type(api_mock).has = PropertyMock(return_value={'createMarketOrder': True})
@@ -881,11 +1001,12 @@ def test_validate_order_types(default_conf, mocker):
     mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     mocker.patch('freqtrade.exchange.Exchange.name', 'Bittrex')
 
     default_conf['order_types'] = {
-        'buy': 'limit',
-        'sell': 'limit',
+        'entry': 'limit',
+        'exit': 'limit',
         'stoploss': 'market',
         'stoploss_on_exchange': False
     }
@@ -895,8 +1016,8 @@ def test_validate_order_types(default_conf, mocker):
     mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
 
     default_conf['order_types'] = {
-        'buy': 'limit',
-        'sell': 'limit',
+        'entry': 'limit',
+        'exit': 'limit',
         'stoploss': 'market',
         'stoploss_on_exchange': False
     }
@@ -905,8 +1026,8 @@ def test_validate_order_types(default_conf, mocker):
         Exchange(default_conf)
 
     default_conf['order_types'] = {
-        'buy': 'limit',
-        'sell': 'limit',
+        'entry': 'limit',
+        'exit': 'limit',
         'stoploss': 'limit',
         'stoploss_on_exchange': True
     }
@@ -921,6 +1042,7 @@ def test_validate_order_types_not_in_config(default_conf, mocker):
     mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
     mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
 
     conf = copy.deepcopy(default_conf)
@@ -935,14 +1057,28 @@ def test_validate_required_startup_candles(default_conf, mocker, caplog):
     mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
     mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
     mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
     mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
 
     default_conf['startup_candle_count'] = 20
     ex = Exchange(default_conf)
     assert ex
-    default_conf['startup_candle_count'] = 600
+    # assumption is that the exchange provides 500 candles per call.s
+    assert ex.validate_required_startup_candles(200, '5m') == 1
+    assert ex.validate_required_startup_candles(499, '5m') == 1
+    assert ex.validate_required_startup_candles(600, '5m') == 2
+    assert ex.validate_required_startup_candles(501, '5m') == 2
+    assert ex.validate_required_startup_candles(499, '5m') == 1
+    assert ex.validate_required_startup_candles(1000, '5m') == 3
+    assert ex.validate_required_startup_candles(2499, '5m') == 5
+    assert log_has_re(r'Using 5 calls to get OHLCV. This.*', caplog)
 
-    with pytest.raises(OperationalException, match=r'This strategy requires 600.*'):
+    with pytest.raises(OperationalException, match=r'This strategy requires 2500.*'):
+        ex.validate_required_startup_candles(2500, '5m')
+
+    # Ensure the same also happens on init
+    default_conf['startup_candle_count'] = 6000
+    with pytest.raises(OperationalException, match=r'This strategy requires 6000.*'):
         Exchange(default_conf)
 
 
@@ -960,22 +1096,33 @@ def test_exchange_has(default_conf, mocker):
     assert not exchange.exchange_has("deadbeef")
 
 
-@pytest.mark.parametrize("side", [
-    ("buy"),
-    ("sell")
+@pytest.mark.parametrize("side,leverage", [
+    ("buy", 1),
+    ("buy", 5),
+    ("sell", 1.0),
+    ("sell", 5.0),
 ])
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_create_dry_run_order(default_conf, mocker, side, exchange_name):
+def test_create_dry_run_order(default_conf, mocker, side, exchange_name, leverage):
     default_conf['dry_run'] = True
     exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
 
     order = exchange.create_dry_run_order(
-        pair='ETH/BTC', ordertype='limit', side=side, amount=1, rate=200)
+        pair='ETH/BTC',
+        ordertype='limit',
+        side=side,
+        amount=1,
+        rate=200,
+        leverage=leverage
+    )
     assert 'id' in order
     assert f'dry_run_{side}_' in order["id"]
     assert order["side"] == side
     assert order["type"] == "limit"
     assert order["symbol"] == "ETH/BTC"
+    assert order["amount"] == 1
+    assert order["leverage"] == leverage
+    assert order["cost"] == 1 * 200 / leverage
 
 
 @pytest.mark.parametrize("side,startprice,endprice", [
@@ -993,7 +1140,13 @@ def test_create_dry_run_order_limit_fill(default_conf, mocker, side, startprice,
                           )
 
     order = exchange.create_dry_run_order(
-        pair='LTC/USDT', ordertype='limit', side=side, amount=1, rate=startprice)
+        pair='LTC/USDT',
+        ordertype='limit',
+        side=side,
+        amount=1,
+        rate=startprice,
+        leverage=1.0
+    )
     assert order_book_l2_usd.call_count == 1
     assert 'id' in order
     assert f'dry_run_{side}_' in order["id"]
@@ -1006,6 +1159,7 @@ def test_create_dry_run_order_limit_fill(default_conf, mocker, side, startprice,
     assert order_book_l2_usd.call_count == 1
     assert order_closed['status'] == 'open'
     assert not order['fee']
+    assert order_closed['filled'] == 0
 
     order_book_l2_usd.reset_mock()
     order_closed['price'] = endprice
@@ -1013,6 +1167,14 @@ def test_create_dry_run_order_limit_fill(default_conf, mocker, side, startprice,
     order_closed = exchange.fetch_dry_run_order(order['id'])
     assert order_closed['status'] == 'closed'
     assert order['fee']
+    assert order_closed['filled'] == 1
+    assert order_closed['filled'] == order_closed['amount']
+
+    # Empty orderbook test
+    mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book',
+                 return_value={'asks': [], 'bids': []})
+    exchange._dry_run_open_orders[order['id']]['status'] = 'open'
+    order_closed = exchange.fetch_dry_run_order(order['id'])
 
 
 @pytest.mark.parametrize("side,rate,amount,endprice", [
@@ -1039,20 +1201,24 @@ def test_create_dry_run_order_market_fill(default_conf, mocker, side, rate, amou
                           )
 
     order = exchange.create_dry_run_order(
-        pair='LTC/USDT', ordertype='market', side=side, amount=amount, rate=rate)
+        pair='LTC/USDT',
+        ordertype='market',
+        side=side,
+        amount=amount,
+        rate=rate,
+        leverage=1.0
+    )
     assert 'id' in order
     assert f'dry_run_{side}_' in order["id"]
     assert order["side"] == side
     assert order["type"] == "market"
     assert order["symbol"] == "LTC/USDT"
     assert order['status'] == 'closed'
+    assert order['filled'] == amount
     assert round(order["average"], 4) == round(endprice, 4)
 
 
-@pytest.mark.parametrize("side", [
-    ("buy"),
-    ("sell")
-])
+@pytest.mark.parametrize("side", ["buy", "sell"])
 @pytest.mark.parametrize("ordertype,rate,marketprice", [
     ("market", None, None),
     ("market", 200, True),
@@ -1068,24 +1234,63 @@ def test_create_order(default_conf, mocker, side, ordertype, rate, marketprice,
         'id': order_id,
         'info': {
             'foo': 'bar'
-        }
+        },
+        'symbol': 'XLTCUSDT',
+        'amount': 1
     })
     default_conf['dry_run'] = False
+    default_conf['margin_mode'] = 'isolated'
     mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
     mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    exchange._set_leverage = MagicMock()
+    exchange.set_margin_mode = MagicMock()
 
     order = exchange.create_order(
-        pair='ETH/BTC', ordertype=ordertype, side=side, amount=1, rate=200)
+        pair='XLTCUSDT',
+        ordertype=ordertype,
+        side=side,
+        amount=1,
+        rate=rate,
+        leverage=1.0
+    )
 
     assert 'id' in order
     assert 'info' in order
     assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert order['amount'] == 1
+    assert api_mock.create_order.call_args[0][0] == 'XLTCUSDT'
     assert api_mock.create_order.call_args[0][1] == ordertype
     assert api_mock.create_order.call_args[0][2] == side
     assert api_mock.create_order.call_args[0][3] == 1
     assert api_mock.create_order.call_args[0][4] is rate
+    assert exchange._set_leverage.call_count == 0
+    assert exchange.set_margin_mode.call_count == 0
+
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        },
+        'symbol': 'ADA/USDT:USDT',
+        'amount': 1
+    })
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    exchange.trading_mode = TradingMode.FUTURES
+    exchange._set_leverage = MagicMock()
+    exchange.set_margin_mode = MagicMock()
+    order = exchange.create_order(
+        pair='ADA/USDT:USDT',
+        ordertype=ordertype,
+        side=side,
+        amount=1,
+        rate=200,
+        leverage=3.0
+    )
+
+    assert exchange._set_leverage.call_count == 1
+    assert exchange.set_margin_mode.call_count == 1
+    assert order['amount'] == 0.01
 
 
 def test_buy_dry_run(default_conf, mocker):
@@ -1093,7 +1298,8 @@ def test_buy_dry_run(default_conf, mocker):
     exchange = get_patched_exchange(mocker, default_conf)
 
     order = exchange.create_order(pair='ETH/BTC', ordertype='limit', side="buy",
-                                  amount=1, rate=200, time_in_force='gtc')
+                                  amount=1, rate=200, leverage=1.0,
+                                  time_in_force='gtc')
     assert 'id' in order
     assert 'dry_run_buy_' in order['id']
 
@@ -1107,6 +1313,7 @@ def test_buy_prod(default_conf, mocker, exchange_name):
     api_mock.options = {}
     api_mock.create_order = MagicMock(return_value={
         'id': order_id,
+        'symbol': 'ETH/BTC',
         'info': {
             'foo': 'bar'
         }
@@ -1117,7 +1324,8 @@ def test_buy_prod(default_conf, mocker, exchange_name):
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
 
     order = exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="buy",
-                                  amount=1, rate=200, time_in_force=time_in_force)
+                                  amount=1, rate=200, leverage=1.0,
+                                  time_in_force=time_in_force)
 
     assert 'id' in order
     assert 'info' in order
@@ -1136,7 +1344,9 @@ def test_buy_prod(default_conf, mocker, exchange_name):
         side="buy",
         amount=1,
         rate=200,
-        time_in_force=time_in_force)
+        leverage=1.0,
+        time_in_force=time_in_force
+    )
     assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
     assert api_mock.create_order.call_args[0][1] == order_type
     assert api_mock.create_order.call_args[0][2] == 'buy'
@@ -1148,31 +1358,36 @@ def test_buy_prod(default_conf, mocker, exchange_name):
         api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("Not enough funds"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
         exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="buy",
-                              amount=1, rate=200, time_in_force=time_in_force)
+                              amount=1, rate=200, leverage=1.0,
+                              time_in_force=time_in_force)
 
     with pytest.raises(DependencyException):
         api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
         exchange.create_order(pair='ETH/BTC', ordertype='limit', side="buy",
-                              amount=1, rate=200, time_in_force=time_in_force)
+                              amount=1, rate=200, leverage=1.0,
+                              time_in_force=time_in_force)
 
     with pytest.raises(DependencyException):
         api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
         exchange.create_order(pair='ETH/BTC', ordertype='market', side="buy",
-                              amount=1, rate=200, time_in_force=time_in_force)
+                              amount=1, rate=200, leverage=1.0,
+                              time_in_force=time_in_force)
 
     with pytest.raises(TemporaryError):
         api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError("Network disconnect"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
         exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="buy",
-                              amount=1, rate=200, time_in_force=time_in_force)
+                              amount=1, rate=200, leverage=1.0,
+                              time_in_force=time_in_force)
 
     with pytest.raises(OperationalException):
         api_mock.create_order = MagicMock(side_effect=ccxt.BaseError("Unknown error"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
         exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="buy",
-                              amount=1, rate=200, time_in_force=time_in_force)
+                              amount=1, rate=200, leverage=1.0,
+                              time_in_force=time_in_force)
 
 
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
@@ -1182,6 +1397,7 @@ def test_buy_considers_time_in_force(default_conf, mocker, exchange_name):
     api_mock.options = {}
     api_mock.create_order = MagicMock(return_value={
         'id': order_id,
+        'symbol': 'ETH/BTC',
         'info': {
             'foo': 'bar'
         }
@@ -1195,7 +1411,8 @@ def test_buy_considers_time_in_force(default_conf, mocker, exchange_name):
     time_in_force = 'ioc'
 
     order = exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="buy",
-                                  amount=1, rate=200, time_in_force=time_in_force)
+                                  amount=1, rate=200, leverage=1.0,
+                                  time_in_force=time_in_force)
 
     assert 'id' in order
     assert 'info' in order
@@ -1212,7 +1429,8 @@ def test_buy_considers_time_in_force(default_conf, mocker, exchange_name):
     time_in_force = 'ioc'
 
     order = exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="buy",
-                                  amount=1, rate=200, time_in_force=time_in_force)
+                                  amount=1, rate=200, leverage=1.0,
+                                  time_in_force=time_in_force)
 
     assert 'id' in order
     assert 'info' in order
@@ -1231,7 +1449,7 @@ def test_sell_dry_run(default_conf, mocker):
     exchange = get_patched_exchange(mocker, default_conf)
 
     order = exchange.create_order(pair='ETH/BTC', ordertype='limit',
-                                  side="sell", amount=1, rate=200)
+                                  side="sell", amount=1, rate=200, leverage=1.0)
     assert 'id' in order
     assert 'dry_run_sell_' in order['id']
 
@@ -1244,6 +1462,7 @@ def test_sell_prod(default_conf, mocker, exchange_name):
     api_mock.options = {}
     api_mock.create_order = MagicMock(return_value={
         'id': order_id,
+        'symbol': 'ETH/BTC',
         'info': {
             'foo': 'bar'
         }
@@ -1255,7 +1474,7 @@ def test_sell_prod(default_conf, mocker, exchange_name):
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
 
     order = exchange.create_order(pair='ETH/BTC', ordertype=order_type,
-                                  side="sell", amount=1, rate=200)
+                                  side="sell", amount=1, rate=200, leverage=1.0)
 
     assert 'id' in order
     assert 'info' in order
@@ -1269,7 +1488,8 @@ def test_sell_prod(default_conf, mocker, exchange_name):
     api_mock.create_order.reset_mock()
     order_type = 'limit'
     order = exchange.create_order(pair='ETH/BTC', ordertype=order_type,
-                                  side="sell", amount=1, rate=200)
+                                  side="sell", amount=1, rate=200,
+                                  leverage=1.0)
     assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
     assert api_mock.create_order.call_args[0][1] == order_type
     assert api_mock.create_order.call_args[0][2] == 'sell'
@@ -1280,28 +1500,33 @@ def test_sell_prod(default_conf, mocker, exchange_name):
     with pytest.raises(DependencyException):
         api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="sell", amount=1, rate=200)
+        exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="sell", amount=1, rate=200,
+                              leverage=1.0)
 
     with pytest.raises(DependencyException):
         api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.create_order(pair='ETH/BTC', ordertype='limit', side="sell", amount=1, rate=200)
+        exchange.create_order(pair='ETH/BTC', ordertype='limit', side="sell", amount=1, rate=200,
+                              leverage=1.0)
 
     # Market orders don't require price, so the behaviour is slightly different
     with pytest.raises(DependencyException):
         api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.create_order(pair='ETH/BTC', ordertype='market', side="sell", amount=1, rate=200)
+        exchange.create_order(pair='ETH/BTC', ordertype='market', side="sell", amount=1, rate=200,
+                              leverage=1.0)
 
     with pytest.raises(TemporaryError):
         api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError("No Connection"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="sell", amount=1, rate=200)
+        exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="sell", amount=1, rate=200,
+                              leverage=1.0)
 
     with pytest.raises(OperationalException):
         api_mock.create_order = MagicMock(side_effect=ccxt.BaseError("DeadBeef"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="sell", amount=1, rate=200)
+        exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="sell", amount=1, rate=200,
+                              leverage=1.0)
 
 
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
@@ -1310,6 +1535,7 @@ def test_sell_considers_time_in_force(default_conf, mocker, exchange_name):
     order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
     api_mock.create_order = MagicMock(return_value={
         'id': order_id,
+        'symbol': 'ETH/BTC',
         'info': {
             'foo': 'bar'
         }
@@ -1324,7 +1550,8 @@ def test_sell_considers_time_in_force(default_conf, mocker, exchange_name):
     time_in_force = 'ioc'
 
     order = exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="sell",
-                                  amount=1, rate=200, time_in_force=time_in_force)
+                                  amount=1, rate=200, leverage=1.0,
+                                  time_in_force=time_in_force)
 
     assert 'id' in order
     assert 'info' in order
@@ -1340,7 +1567,8 @@ def test_sell_considers_time_in_force(default_conf, mocker, exchange_name):
     order_type = 'market'
     time_in_force = 'ioc'
     order = exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="sell",
-                                  amount=1, rate=200, time_in_force=time_in_force)
+                                  amount=1, rate=200, leverage=1.0,
+                                  time_in_force=time_in_force)
 
     assert 'id' in order
     assert 'info' in order
@@ -1379,6 +1607,136 @@ def test_get_balances_prod(default_conf, mocker, exchange_name):
                            "get_balances", "fetch_balance")
 
 
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_fetch_positions(default_conf, mocker, exchange_name):
+    mocker.patch('freqtrade.exchange.Exchange.validate_trading_mode_and_margin_mode')
+    api_mock = MagicMock()
+    api_mock.fetch_positions = MagicMock(return_value=[
+        {'symbol': 'ETH/USDT:USDT', 'leverage': 5},
+        {'symbol': 'XRP/USDT:USDT', 'leverage': 5},
+    ])
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    assert exchange.fetch_positions() == []
+    default_conf['dry_run'] = False
+    default_conf['trading_mode'] = 'futures'
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    res = exchange.fetch_positions()
+    assert len(res) == 2
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           "fetch_positions", "fetch_positions")
+
+
+def test_fetch_trading_fees(default_conf, mocker):
+    api_mock = MagicMock()
+    tick = {
+        '1INCH/USDT:USDT': {
+            'info': {'user_id': '',
+                     'taker_fee': '0.0018',
+                     'maker_fee': '0.0018',
+                     'gt_discount': False,
+                     'gt_taker_fee': '0',
+                     'gt_maker_fee': '0',
+                     'loan_fee': '0.18',
+                     'point_type': '1',
+                     'futures_taker_fee': '0.0005',
+                     'futures_maker_fee': '0'},
+            'symbol': '1INCH/USDT:USDT',
+            'maker': 0.0,
+            'taker': 0.0005},
+        'ETH/USDT:USDT': {
+            'info': {'user_id': '',
+                     'taker_fee': '0.0018',
+                     'maker_fee': '0.0018',
+                     'gt_discount': False,
+                     'gt_taker_fee': '0',
+                     'gt_maker_fee': '0',
+                     'loan_fee': '0.18',
+                     'point_type': '1',
+                     'futures_taker_fee': '0.0005',
+                     'futures_maker_fee': '0'},
+            'symbol': 'ETH/USDT:USDT',
+            'maker': 0.0,
+            'taker': 0.0005}
+    }
+    exchange_name = 'gateio'
+    default_conf['dry_run'] = False
+    default_conf['trading_mode'] = TradingMode.FUTURES
+    default_conf['margin_mode'] = MarginMode.ISOLATED
+    api_mock.fetch_trading_fees = MagicMock(return_value=tick)
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    assert '1INCH/USDT:USDT' in exchange._trading_fees
+    assert 'ETH/USDT:USDT' in exchange._trading_fees
+    assert api_mock.fetch_trading_fees.call_count == 1
+
+    api_mock.fetch_trading_fees.reset_mock()
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           "fetch_trading_fees", "fetch_trading_fees")
+
+    api_mock.fetch_trading_fees = MagicMock(return_value={})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    exchange.fetch_trading_fees()
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    assert exchange.fetch_trading_fees() == {}
+
+
+def test_fetch_bids_asks(default_conf, mocker):
+    api_mock = MagicMock()
+    tick = {'ETH/BTC': {
+        'symbol': 'ETH/BTC',
+        'bid': 0.5,
+        'ask': 1,
+        'last': 42,
+    }, 'BCH/BTC': {
+        'symbol': 'BCH/BTC',
+        'bid': 0.6,
+        'ask': 0.5,
+        'last': 41,
+    }
+    }
+    exchange_name = 'binance'
+    api_mock.fetch_bids_asks = MagicMock(return_value=tick)
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    # retrieve original ticker
+    bidsasks = exchange.fetch_bids_asks()
+
+    assert 'ETH/BTC' in bidsasks
+    assert 'BCH/BTC' in bidsasks
+    assert bidsasks['ETH/BTC']['bid'] == 0.5
+    assert bidsasks['ETH/BTC']['ask'] == 1
+    assert bidsasks['BCH/BTC']['bid'] == 0.6
+    assert bidsasks['BCH/BTC']['ask'] == 0.5
+    assert api_mock.fetch_bids_asks.call_count == 1
+
+    api_mock.fetch_bids_asks.reset_mock()
+
+    # Cached ticker should not call api again
+    tickers2 = exchange.fetch_bids_asks(cached=True)
+    assert tickers2 == bidsasks
+    assert api_mock.fetch_bids_asks.call_count == 0
+    tickers2 = exchange.fetch_bids_asks(cached=False)
+    assert api_mock.fetch_bids_asks.call_count == 1
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           "fetch_bids_asks", "fetch_bids_asks")
+
+    with pytest.raises(OperationalException):
+        api_mock.fetch_bids_asks = MagicMock(side_effect=ccxt.NotSupported("DeadBeef"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.fetch_bids_asks()
+
+    api_mock.fetch_bids_asks = MagicMock(return_value={})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    exchange.fetch_bids_asks()
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    assert exchange.fetch_bids_asks() == {}
+
+
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
 def test_get_tickers(default_conf, mocker, exchange_name):
     api_mock = MagicMock()
@@ -1395,6 +1753,7 @@ def test_get_tickers(default_conf, mocker, exchange_name):
     }
     }
     api_mock.fetch_tickers = MagicMock(return_value=tick)
+    api_mock.fetch_bids_asks = MagicMock(return_value={})
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
     # retrieve original ticker
     tickers = exchange.get_tickers()
@@ -1406,6 +1765,7 @@ def test_get_tickers(default_conf, mocker, exchange_name):
     assert tickers['BCH/BTC']['bid'] == 0.6
     assert tickers['BCH/BTC']['ask'] == 0.5
     assert api_mock.fetch_tickers.call_count == 1
+    assert api_mock.fetch_bids_asks.call_count == 0
 
     api_mock.fetch_tickers.reset_mock()
 
@@ -1413,8 +1773,10 @@ def test_get_tickers(default_conf, mocker, exchange_name):
     tickers2 = exchange.get_tickers(cached=True)
     assert tickers2 == tickers
     assert api_mock.fetch_tickers.call_count == 0
+    assert api_mock.fetch_bids_asks.call_count == 0
     tickers2 = exchange.get_tickers(cached=False)
     assert api_mock.fetch_tickers.call_count == 1
+    assert api_mock.fetch_bids_asks.call_count == 0
 
     ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
                            "get_tickers", "fetch_tickers")
@@ -1428,6 +1790,17 @@ def test_get_tickers(default_conf, mocker, exchange_name):
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
     exchange.get_tickers()
 
+    api_mock.fetch_tickers.reset_mock()
+    api_mock.fetch_bids_asks.reset_mock()
+    default_conf['trading_mode'] = TradingMode.FUTURES
+    default_conf['margin_mode'] = MarginMode.ISOLATED
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    exchange.get_tickers()
+    assert api_mock.fetch_tickers.call_count == 1
+    assert api_mock.fetch_bids_asks.call_count == (1 if exchange_name == 'binance' else 0)
+
 
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
 def test_fetch_ticker(default_conf, mocker, exchange_name):
@@ -1478,7 +1851,8 @@ def test_fetch_ticker(default_conf, mocker, exchange_name):
 
 
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name):
+@pytest.mark.parametrize('candle_type', ['mark', ''])
+def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name, candle_type):
     exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
     ohlcv = [
         [
@@ -1492,19 +1866,24 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name):
     ]
     pair = 'ETH/BTC'
 
-    async def mock_candle_hist(pair, timeframe, since_ms):
-        return pair, timeframe, ohlcv
+    async def mock_candle_hist(pair, timeframe, candle_type, since_ms):
+        return pair, timeframe, candle_type, ohlcv
 
     exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
     # one_call calculation * 1.8 should do 2 calls
 
     since = 5 * 60 * exchange.ohlcv_candle_limit('5m') * 1.8
-    ret = exchange.get_historic_ohlcv(pair, "5m", int((
-        arrow.utcnow().int_timestamp - since) * 1000))
+    ret = exchange.get_historic_ohlcv(
+        pair,
+        "5m",
+        int((arrow.utcnow().int_timestamp - since) * 1000),
+        candle_type=candle_type
+    )
 
     assert exchange._async_get_candle_history.call_count == 2
     # Returns twice the above OHLCV data
     assert len(ret) == 2
+    assert log_has_re(r'Downloaded data for .* with length .*\.', caplog)
 
     caplog.clear()
 
@@ -1512,13 +1891,18 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name):
         raise TimeoutError()
 
     exchange._async_get_candle_history = MagicMock(side_effect=mock_get_candle_hist_error)
-    ret = exchange.get_historic_ohlcv(pair, "5m", int(
-        (arrow.utcnow().int_timestamp - since) * 1000))
+    ret = exchange.get_historic_ohlcv(
+        pair,
+        "5m",
+        int((arrow.utcnow().int_timestamp - since) * 1000),
+        candle_type=candle_type
+    )
     assert log_has_re(r"Async code raised an exception: .*", caplog)
 
 
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_historic_ohlcv_as_df(default_conf, mocker, exchange_name):
+@pytest.mark.parametrize('candle_type', ['mark', ''])
+def test_get_historic_ohlcv_as_df(default_conf, mocker, exchange_name, candle_type):
     exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
     ohlcv = [
         [
@@ -1548,15 +1932,19 @@ def test_get_historic_ohlcv_as_df(default_conf, mocker, exchange_name):
     ]
     pair = 'ETH/BTC'
 
-    async def mock_candle_hist(pair, timeframe, since_ms):
-        return pair, timeframe, ohlcv
+    async def mock_candle_hist(pair, timeframe, candle_type, since_ms):
+        return pair, timeframe, candle_type, ohlcv
 
     exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
     # one_call calculation * 1.8 should do 2 calls
 
     since = 5 * 60 * exchange.ohlcv_candle_limit('5m') * 1.8
-    ret = exchange.get_historic_ohlcv_as_df(pair, "5m", int((
-        arrow.utcnow().int_timestamp - since) * 1000))
+    ret = exchange.get_historic_ohlcv_as_df(
+        pair,
+        "5m",
+        int((arrow.utcnow().int_timestamp - since) * 1000),
+        candle_type=candle_type
+    )
 
     assert exchange._async_get_candle_history.call_count == 2
     # Returns twice the above OHLCV data
@@ -1570,7 +1958,8 @@ def test_get_historic_ohlcv_as_df(default_conf, mocker, exchange_name):
 
 @pytest.mark.asyncio
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
-async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name):
+@pytest.mark.parametrize('candle_type', [CandleType.MARK, CandleType.SPOT])
+async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name, candle_type):
     ohlcv = [
         [
             int((datetime.now(timezone.utc).timestamp() - 1000) * 1000),
@@ -1586,15 +1975,17 @@ async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_
     exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
 
     pair = 'ETH/USDT'
-    res = await exchange._async_get_historic_ohlcv(pair, "5m",
-                                                   1500000000000, is_new_pair=False)
+    respair, restf, _, res = await exchange._async_get_historic_ohlcv(
+        pair, "5m", 1500000000000, candle_type=candle_type, is_new_pair=False)
+    assert respair == pair
+    assert restf == '5m'
     # Call with very old timestamp - causes tons of requests
     assert exchange._api_async.fetch_ohlcv.call_count > 200
     assert res[0] == ohlcv[0]
-    assert log_has_re(r'Downloaded data for .* with length .*\.', caplog)
 
 
-def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
+@pytest.mark.parametrize('candle_type', [CandleType.FUTURES, CandleType.MARK, CandleType.SPOT])
+def test_refresh_latest_ohlcv(mocker, default_conf, caplog, candle_type) -> None:
     ohlcv = [
         [
             (arrow.utcnow().int_timestamp - 1) * 1000,  # unix timestamp ms
@@ -1618,7 +2009,7 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
     exchange = get_patched_exchange(mocker, default_conf)
     exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
 
-    pairs = [('IOTA/ETH', '5m'), ('XRP/ETH', '5m')]
+    pairs = [('IOTA/ETH', '5m', candle_type), ('XRP/ETH', '5m', candle_type)]
     # empty dicts
     assert not exchange._klines
     res = exchange.refresh_latest_ohlcv(pairs, cache=False)
@@ -1629,12 +2020,14 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
     assert exchange._api_async.fetch_ohlcv.call_count == 2
     exchange._api_async.fetch_ohlcv.reset_mock()
 
+    exchange.required_candle_call_count = 2
     res = exchange.refresh_latest_ohlcv(pairs)
     assert len(res) == len(pairs)
 
     assert log_has(f'Refreshing candle (OHLCV) data for {len(pairs)} pairs', caplog)
     assert exchange._klines
-    assert exchange._api_async.fetch_ohlcv.call_count == 2
+    assert exchange._api_async.fetch_ohlcv.call_count == 4
+    exchange._api_async.fetch_ohlcv.reset_mock()
     for pair in pairs:
         assert isinstance(exchange.klines(pair), DataFrame)
         assert len(exchange.klines(pair)) > 0
@@ -1647,16 +2040,38 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
         assert exchange.klines(pair, copy=False) is exchange.klines(pair, copy=False)
 
     # test caching
-    res = exchange.refresh_latest_ohlcv([('IOTA/ETH', '5m'), ('XRP/ETH', '5m')])
+    res = exchange.refresh_latest_ohlcv(
+        [('IOTA/ETH', '5m', candle_type), ('XRP/ETH', '5m', candle_type)])
     assert len(res) == len(pairs)
 
-    assert exchange._api_async.fetch_ohlcv.call_count == 2
-    assert log_has(f"Using cached candle (OHLCV) data for pair {pairs[0][0]}, "
-                   f"timeframe {pairs[0][1]} ...",
+    assert exchange._api_async.fetch_ohlcv.call_count == 0
+    exchange.required_candle_call_count = 1
+    assert log_has(f"Using cached candle (OHLCV) data for {pairs[0][0]}, "
+                   f"{pairs[0][1]}, {candle_type} ...",
                    caplog)
-    res = exchange.refresh_latest_ohlcv([('IOTA/ETH', '5m'), ('XRP/ETH', '5m'), ('XRP/ETH', '1d')],
-                                        cache=False)
+    pairlist = [
+        ('IOTA/ETH', '5m', candle_type),
+        ('XRP/ETH', '5m', candle_type),
+        ('XRP/ETH', '1d', candle_type)]
+    res = exchange.refresh_latest_ohlcv(pairlist, cache=False)
     assert len(res) == 3
+    assert exchange._api_async.fetch_ohlcv.call_count == 3
+
+    # Test the same again, should NOT return from cache!
+    exchange._api_async.fetch_ohlcv.reset_mock()
+    res = exchange.refresh_latest_ohlcv(pairlist, cache=False)
+    assert len(res) == 3
+    assert exchange._api_async.fetch_ohlcv.call_count == 3
+    exchange._api_async.fetch_ohlcv.reset_mock()
+    caplog.clear()
+    # Call with invalid timeframe
+    res = exchange.refresh_latest_ohlcv([('IOTA/ETH', '3m', candle_type)], cache=False)
+    if candle_type != CandleType.MARK:
+        assert not res
+        assert len(res) == 0
+        assert log_has_re(r'Cannot download \(IOTA\/ETH, 3m\).*', caplog)
+    else:
+        assert len(res) == 1
 
 
 @pytest.mark.asyncio
@@ -1679,36 +2094,77 @@ async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_
     exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
 
     pair = 'ETH/BTC'
-    res = await exchange._async_get_candle_history(pair, "5m")
+    res = await exchange._async_get_candle_history(pair, "5m", CandleType.SPOT)
     assert type(res) is tuple
-    assert len(res) == 3
+    assert len(res) == 4
     assert res[0] == pair
     assert res[1] == "5m"
-    assert res[2] == ohlcv
+    assert res[2] == CandleType.SPOT
+    assert res[3] == ohlcv
     assert exchange._api_async.fetch_ohlcv.call_count == 1
     assert not log_has(f"Using cached candle (OHLCV) data for {pair} ...", caplog)
 
     # exchange = Exchange(default_conf)
     await async_ccxt_exception(mocker, default_conf, MagicMock(),
                                "_async_get_candle_history", "fetch_ohlcv",
-                               pair='ABCD/BTC', timeframe=default_conf['timeframe'])
+                               pair='ABCD/BTC', timeframe=default_conf['timeframe'],
+                               candle_type=CandleType.SPOT)
 
     api_mock = MagicMock()
     with pytest.raises(OperationalException,
                        match=r'Could not fetch historical candle \(OHLCV\) data.*'):
         api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.BaseError("Unknown error"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        await exchange._async_get_candle_history(pair, "5m",
+        await exchange._async_get_candle_history(pair, "5m", CandleType.SPOT,
                                                  (arrow.utcnow().int_timestamp - 2000) * 1000)
 
     with pytest.raises(OperationalException, match=r'Exchange.* does not support fetching '
                                                    r'historical candle \(OHLCV\) data\..*'):
         api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.NotSupported("Not supported"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        await exchange._async_get_candle_history(pair, "5m",
+        await exchange._async_get_candle_history(pair, "5m", CandleType.SPOT,
                                                  (arrow.utcnow().int_timestamp - 2000) * 1000)
 
 
+@pytest.mark.asyncio
+async def test__async_kucoin_get_candle_history(default_conf, mocker, caplog):
+    caplog.set_level(logging.INFO)
+    api_mock = MagicMock()
+    api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.DDoSProtection(
+        "kucoin GET https://openapi-v2.kucoin.com/api/v1/market/candles?"
+        "symbol=ETH-BTC&type=5min&startAt=1640268735&endAt=1640418735"
+        "429 Too Many Requests" '{"code":"429000","msg":"Too Many Requests"}'))
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="KuCoin")
+    mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value='KuCoin'))
+
+    msg = "Kucoin 429 error, avoid triggering DDosProtection backoff delay"
+    assert not num_log_has_re(msg, caplog)
+
+    for _ in range(3):
+        with pytest.raises(DDosProtection, match=r'429 Too Many Requests'):
+            await exchange._async_get_candle_history(
+                "ETH/BTC", "5m", (arrow.utcnow().int_timestamp - 2000) * 1000, count=3)
+    assert num_log_has_re(msg, caplog) == 3
+
+    caplog.clear()
+    # Test regular non-kucoin message
+    api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.DDoSProtection(
+        "kucoin GET https://openapi-v2.kucoin.com/api/v1/market/candles?"
+        "symbol=ETH-BTC&type=5min&startAt=1640268735&endAt=1640418735"
+        "429 Too Many Requests" '{"code":"2222222","msg":"Too Many Requests"}'))
+
+    msg = r'_async_get_candle_history\(\) returned exception: .*'
+    msg2 = r'Applying DDosProtection backoff delay: .*'
+    with patch('freqtrade.exchange.common.asyncio.sleep', get_mock_coro(None)):
+        for _ in range(3):
+            with pytest.raises(DDosProtection, match=r'429 Too Many Requests'):
+                await exchange._async_get_candle_history(
+                    "ETH/BTC", "5m", (arrow.utcnow().int_timestamp - 2000) * 1000, count=3)
+        # Expect the "returned exception" message 12 times (4 retries * 3 (loop))
+        assert num_log_has_re(msg, caplog) == 12
+        assert num_log_has_re(msg2, caplog) == 9
+
+
 @pytest.mark.asyncio
 async def test__async_get_candle_history_empty(default_conf, mocker, caplog):
     """ Test empty exchange result """
@@ -1721,12 +2177,13 @@ async def test__async_get_candle_history_empty(default_conf, mocker, caplog):
 
     exchange = Exchange(default_conf)
     pair = 'ETH/BTC'
-    res = await exchange._async_get_candle_history(pair, "5m")
+    res = await exchange._async_get_candle_history(pair, "5m", CandleType.SPOT)
     assert type(res) is tuple
-    assert len(res) == 3
+    assert len(res) == 4
     assert res[0] == pair
     assert res[1] == "5m"
-    assert res[2] == ohlcv
+    assert res[2] == CandleType.SPOT
+    assert res[3] == ohlcv
     assert exchange._api_async.fetch_ohlcv.call_count == 1
 
 
@@ -1743,7 +2200,7 @@ def test_refresh_latest_ohlcv_inv_result(default_conf, mocker, caplog):
     # Monkey-patch async function with empty result
     exchange._api_async.fetch_ohlcv = MagicMock(side_effect=mock_get_candle_hist)
 
-    pairs = [("ETH/BTC", "5m"), ("XRP/BTC", "5m")]
+    pairs = [("ETH/BTC", "5m", ''), ("XRP/BTC", "5m", '')]
     res = exchange.refresh_latest_ohlcv(pairs)
     assert exchange._klines
     assert exchange._api_async.fetch_ohlcv.call_count == 2
@@ -1752,7 +2209,7 @@ def test_refresh_latest_ohlcv_inv_result(default_conf, mocker, caplog):
     assert len(res) == 1
     # Test that each is in list at least once as order is not guaranteed
     assert log_has("Error loading ETH/BTC. Result was [[]].", caplog)
-    assert log_has("Async code raised an exception: TypeError", caplog)
+    assert log_has("Async code raised an exception: TypeError()", caplog)
 
 
 def test_get_next_limit_in_list():
@@ -1824,6 +2281,7 @@ def test_fetch_l2_order_book_exception(default_conf, mocker, exchange_name):
 
 
 @pytest.mark.parametrize("side,ask,bid,last,last_ab,expected", [
+    ('other', 20, 19, 10, 0.0, 20),  # Full ask side
     ('ask', 20, 19, 10, 0.0, 20),  # Full ask side
     ('ask', 20, 19, 10, 1.0, 10),  # Full last side
     ('ask', 20, 19, 10, 0.5, 15),  # Between ask and last
@@ -1831,40 +2289,46 @@ def test_fetch_l2_order_book_exception(default_conf, mocker, exchange_name):
     ('ask', 20, 19, 10, 0.3, 17),  # Between ask and last
     ('ask', 5, 6, 10, 1.0, 5),  # last bigger than ask
     ('ask', 5, 6, 10, 0.5, 5),  # last bigger than ask
+    ('ask', 20, 19, 10, None, 20),  # price_last_balance missing
     ('ask', 10, 20, None, 0.5, 10),  # last not available - uses ask
     ('ask', 4, 5, None, 0.5, 4),  # last not available - uses ask
     ('ask', 4, 5, None, 1, 4),  # last not available - uses ask
     ('ask', 4, 5, None, 0, 4),  # last not available - uses ask
+    ('same', 21, 20, 10, 0.0, 20),  # Full bid side
     ('bid', 21, 20, 10, 0.0, 20),  # Full bid side
     ('bid', 21, 20, 10, 1.0, 10),  # Full last side
     ('bid', 21, 20, 10, 0.5, 15),  # Between bid and last
     ('bid', 21, 20, 10, 0.7, 13),  # Between bid and last
     ('bid', 21, 20, 10, 0.3, 17),  # Between bid and last
     ('bid', 6, 5, 10, 1.0, 5),  # last bigger than bid
+    ('bid', 21, 20, 10, None, 20),  # price_last_balance missing
     ('bid', 6, 5, 10, 0.5, 5),  # last bigger than bid
     ('bid', 21, 20, None, 0.5, 20),  # last not available - uses bid
     ('bid', 6, 5, None, 0.5, 5),  # last not available - uses bid
     ('bid', 6, 5, None, 1, 5),  # last not available - uses bid
     ('bid', 6, 5, None, 0, 5),  # last not available - uses bid
 ])
-def test_get_buy_rate(mocker, default_conf, caplog, side, ask, bid,
-                      last, last_ab, expected) -> None:
+def test_get_entry_rate(mocker, default_conf, caplog, side, ask, bid,
+                        last, last_ab, expected) -> None:
     caplog.set_level(logging.DEBUG)
-    default_conf['bid_strategy']['ask_last_balance'] = last_ab
-    default_conf['bid_strategy']['price_side'] = side
+    if last_ab is None:
+        del default_conf['entry_pricing']['price_last_balance']
+    else:
+        default_conf['entry_pricing']['price_last_balance'] = last_ab
+    default_conf['entry_pricing']['price_side'] = side
     exchange = get_patched_exchange(mocker, default_conf)
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  return_value={'ask': ask, 'last': last, 'bid': bid})
 
-    assert exchange.get_rate('ETH/BTC', refresh=True, side="buy") == expected
-    assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
+    assert exchange.get_rate('ETH/BTC', side="entry", is_short=False, refresh=True) == expected
+    assert not log_has("Using cached entry rate for ETH/BTC.", caplog)
 
-    assert exchange.get_rate('ETH/BTC', refresh=False, side="buy") == expected
-    assert log_has("Using cached buy rate for ETH/BTC.", caplog)
+    assert exchange.get_rate('ETH/BTC', side="entry", is_short=False, refresh=False) == expected
+    assert log_has("Using cached entry rate for ETH/BTC.", caplog)
     # Running a 2nd time with Refresh on!
     caplog.clear()
-    assert exchange.get_rate('ETH/BTC', refresh=True, side="buy") == expected
-    assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
+    assert exchange.get_rate('ETH/BTC', side="entry", is_short=False, refresh=True) == expected
+    assert not log_has("Using cached entry rate for ETH/BTC.", caplog)
 
 
 @pytest.mark.parametrize('side,ask,bid,last,last_ab,expected', [
@@ -1875,6 +2339,7 @@ def test_get_buy_rate(mocker, default_conf, caplog, side, ask, bid,
     ('bid', 12.0, 11.2, 10.5, 1.0, 11.2),  # Last smaller than bid - uses bid
     ('bid', 12.0, 11.2, 10.5, 0.5, 11.2),  # Last smaller than bid - uses bid
     ('bid', 0.003, 0.002, 0.005, 0.0, 0.002),
+    ('bid', 0.003, 0.002, 0.005, None, 0.002),
     ('ask', 12.0, 11.0, 12.5, 0.0, 12.0),  # full ask side
     ('ask', 12.0, 11.0, 12.5, 1.0, 12.5),  # full last side
     ('ask', 12.0, 11.0, 12.5, 0.5, 12.25),  # between bid and lat
@@ -1885,121 +2350,122 @@ def test_get_buy_rate(mocker, default_conf, caplog, side, ask, bid,
     ('ask', 10.11, 11.2, 11.0, 0.0, 10.11),
     ('ask', 0.001, 0.002, 11.0, 0.0, 0.001),
     ('ask', 0.006, 1.0, 11.0, 0.0, 0.006),
+    ('ask', 0.006, 1.0, 11.0, None, 0.006),
 ])
-def test_get_sell_rate(default_conf, mocker, caplog, side, bid, ask,
+def test_get_exit_rate(default_conf, mocker, caplog, side, bid, ask,
                        last, last_ab, expected) -> None:
     caplog.set_level(logging.DEBUG)
 
-    default_conf['ask_strategy']['price_side'] = side
-    default_conf['ask_strategy']['bid_last_balance'] = last_ab
+    default_conf['exit_pricing']['price_side'] = side
+    if last_ab is not None:
+        default_conf['exit_pricing']['price_last_balance'] = last_ab
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  return_value={'ask': ask, 'bid': bid, 'last': last})
     pair = "ETH/BTC"
 
     # Test regular mode
     exchange = get_patched_exchange(mocker, default_conf)
-    rate = exchange.get_rate(pair, refresh=True, side="sell")
-    assert not log_has("Using cached sell rate for ETH/BTC.", caplog)
+    rate = exchange.get_rate(pair, side="exit", is_short=False, refresh=True)
+    assert not log_has("Using cached exit rate for ETH/BTC.", caplog)
     assert isinstance(rate, float)
     assert rate == expected
     # Use caching
-    rate = exchange.get_rate(pair, refresh=False, side="sell")
+    rate = exchange.get_rate(pair, side="exit", is_short=False, refresh=False)
     assert rate == expected
-    assert log_has("Using cached sell rate for ETH/BTC.", caplog)
+    assert log_has("Using cached exit rate for ETH/BTC.", caplog)
 
 
-@pytest.mark.parametrize("entry,side,ask,bid,last,last_ab,expected", [
-    ('buy', 'ask', None, 4, 4,  0, 4),  # ask not available
-    ('buy', 'ask', None, None, 4,  0, 4),  # ask not available
-    ('buy', 'bid', 6, None, 4,  0, 5),  # bid not available
-    ('buy', 'bid', None, None, 4,  0, 5),  # No rate available
-    ('sell', 'ask', None, 4, 4,  0, 4),  # ask not available
-    ('sell', 'ask', None, None, 4,  0, 4),  # ask not available
-    ('sell', 'bid', 6, None, 4,  0, 5),  # bid not available
-    ('sell', 'bid', None, None, 4,  0, 5),  # bid not available
+@pytest.mark.parametrize("entry,is_short,side,ask,bid,last,last_ab,expected", [
+    ('entry', False, 'ask', None, 4, 4,  0, 4),  # ask not available
+    ('entry', False, 'ask', None, None, 4,  0, 4),  # ask not available
+    ('entry', False, 'bid', 6, None, 4,  0, 5),  # bid not available
+    ('entry', False, 'bid', None, None, 4,  0, 5),  # No rate available
+    ('exit', False, 'ask', None, 4, 4,  0, 4),  # ask not available
+    ('exit', False, 'ask', None, None, 4,  0, 4),  # ask not available
+    ('exit', False, 'bid', 6, None, 4,  0, 5),  # bid not available
+    ('exit', False, 'bid', None, None, 4,  0, 5),  # bid not available
 ])
-def test_get_ticker_rate_error(mocker, entry, default_conf, caplog, side, ask, bid,
+def test_get_ticker_rate_error(mocker, entry, default_conf, caplog, side, is_short, ask, bid,
                                last, last_ab, expected) -> None:
     caplog.set_level(logging.DEBUG)
-    default_conf['bid_strategy']['ask_last_balance'] = last_ab
-    default_conf['bid_strategy']['price_side'] = side
-    default_conf['ask_strategy']['price_side'] = side
-    default_conf['ask_strategy']['ask_last_balance'] = last_ab
+    default_conf['entry_pricing']['price_last_balance'] = last_ab
+    default_conf['entry_pricing']['price_side'] = side
+    default_conf['exit_pricing']['price_side'] = side
+    default_conf['exit_pricing']['price_last_balance'] = last_ab
     exchange = get_patched_exchange(mocker, default_conf)
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  return_value={'ask': ask, 'last': last, 'bid': bid})
 
     with pytest.raises(PricingError):
-        exchange.get_rate('ETH/BTC', refresh=True, side=entry)
+        exchange.get_rate('ETH/BTC', refresh=True, side=entry, is_short=is_short)
 
 
-@pytest.mark.parametrize('side,expected', [
-    ('bid', 0.043936),  # Value from order_book_l2 fiture - bids side
-    ('ask', 0.043949),  # Value from order_book_l2 fiture - asks side
+@pytest.mark.parametrize('is_short,side,expected', [
+    (False, 'bid', 0.043936),  # Value from order_book_l2 fitxure - bids side
+    (False, 'ask', 0.043949),  # Value from order_book_l2 fitxure - asks side
+    (False, 'other', 0.043936),  # Value from order_book_l2 fitxure - bids side
+    (False, 'same', 0.043949),  # Value from order_book_l2 fitxure - asks side
+    (True, 'bid', 0.043936),  # Value from order_book_l2 fitxure - bids side
+    (True, 'ask', 0.043949),  # Value from order_book_l2 fitxure - asks side
+    (True, 'other', 0.043949),  # Value from order_book_l2 fitxure - asks side
+    (True, 'same', 0.043936),  # Value from order_book_l2 fitxure - bids side
 ])
-def test_get_sell_rate_orderbook(default_conf, mocker, caplog, side, expected, order_book_l2):
+def test_get_exit_rate_orderbook(
+        default_conf, mocker, caplog, is_short, side, expected, order_book_l2):
     caplog.set_level(logging.DEBUG)
     # Test orderbook mode
-    default_conf['ask_strategy']['price_side'] = side
-    default_conf['ask_strategy']['use_order_book'] = True
-    default_conf['ask_strategy']['order_book_top'] = 1
+    default_conf['exit_pricing']['price_side'] = side
+    default_conf['exit_pricing']['use_order_book'] = True
+    default_conf['exit_pricing']['order_book_top'] = 1
     pair = "ETH/BTC"
     mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
     exchange = get_patched_exchange(mocker, default_conf)
-    rate = exchange.get_rate(pair, refresh=True, side="sell")
-    assert not log_has("Using cached sell rate for ETH/BTC.", caplog)
+    rate = exchange.get_rate(pair, refresh=True, side="exit", is_short=is_short)
+    assert not log_has("Using cached exit rate for ETH/BTC.", caplog)
     assert isinstance(rate, float)
     assert rate == expected
-    rate = exchange.get_rate(pair, refresh=False, side="sell")
+    rate = exchange.get_rate(pair, refresh=False, side="exit", is_short=is_short)
     assert rate == expected
-    assert log_has("Using cached sell rate for ETH/BTC.", caplog)
+    assert log_has("Using cached exit rate for ETH/BTC.", caplog)
 
 
-def test_get_sell_rate_orderbook_exception(default_conf, mocker, caplog):
+def test_get_exit_rate_orderbook_exception(default_conf, mocker, caplog):
     # Test orderbook mode
-    default_conf['ask_strategy']['price_side'] = 'ask'
-    default_conf['ask_strategy']['use_order_book'] = True
-    default_conf['ask_strategy']['order_book_top'] = 1
+    default_conf['exit_pricing']['price_side'] = 'ask'
+    default_conf['exit_pricing']['use_order_book'] = True
+    default_conf['exit_pricing']['order_book_top'] = 1
     pair = "ETH/BTC"
     # Test What happens if the exchange returns an empty orderbook.
     mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book',
                  return_value={'bids': [[]], 'asks': [[]]})
     exchange = get_patched_exchange(mocker, default_conf)
     with pytest.raises(PricingError):
-        exchange.get_rate(pair, refresh=True, side="sell")
-    assert log_has_re(r"Sell Price at location 1 from orderbook could not be determined\..*",
+        exchange.get_rate(pair, refresh=True, side="exit", is_short=False)
+    assert log_has_re(r"Exit Price at location 1 from orderbook could not be determined\..*",
                       caplog)
 
 
-def test_get_sell_rate_exception(default_conf, mocker, caplog):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_get_exit_rate_exception(default_conf, mocker, is_short):
     # Ticker on one side can be empty in certain circumstances.
-    default_conf['ask_strategy']['price_side'] = 'ask'
+    default_conf['exit_pricing']['price_side'] = 'ask'
     pair = "ETH/BTC"
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  return_value={'ask': None, 'bid': 0.12, 'last': None})
     exchange = get_patched_exchange(mocker, default_conf)
-    with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
-        exchange.get_rate(pair, refresh=True, side="sell")
+    with pytest.raises(PricingError, match=r"Exit-Rate for ETH/BTC was empty."):
+        exchange.get_rate(pair, refresh=True, side="exit", is_short=is_short)
 
-    exchange._config['ask_strategy']['price_side'] = 'bid'
-    assert exchange.get_rate(pair, refresh=True, side="sell") == 0.12
+    exchange._config['exit_pricing']['price_side'] = 'bid'
+    assert exchange.get_rate(pair, refresh=True, side="exit", is_short=is_short) == 0.12
     # Reverse sides
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  return_value={'ask': 0.13, 'bid': None, 'last': None})
-    with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
-        exchange.get_rate(pair, refresh=True, side="sell")
+    with pytest.raises(PricingError, match=r"Exit-Rate for ETH/BTC was empty."):
+        exchange.get_rate(pair, refresh=True, side="exit", is_short=is_short)
 
-    exchange._config['ask_strategy']['price_side'] = 'ask'
-    assert exchange.get_rate(pair, refresh=True, side="sell") == 0.13
-
-
-def make_fetch_ohlcv_mock(data):
-    def fetch_ohlcv_mock(pair, timeframe, since):
-        if since:
-            assert since > data[-1][0]
-            return []
-        return data
-    return fetch_ohlcv_mock
+    exchange._config['exit_pricing']['price_side'] = 'ask'
+    assert exchange.get_rate(pair, refresh=True, side="exit", is_short=is_short) == 0.13
 
 
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
@@ -2026,9 +2492,10 @@ async def test___async_get_candle_history_sort(default_conf, mocker, exchange_na
     exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
     sort_mock = mocker.patch('freqtrade.exchange.exchange.sorted', MagicMock(side_effect=sort_data))
     # Test the OHLCV data sort
-    res = await exchange._async_get_candle_history('ETH/BTC', default_conf['timeframe'])
+    res = await exchange._async_get_candle_history(
+        'ETH/BTC', default_conf['timeframe'], CandleType.SPOT)
     assert res[0] == 'ETH/BTC'
-    res_ohlcv = res[2]
+    res_ohlcv = res[3]
 
     assert sort_mock.call_count == 1
     assert res_ohlcv[0][0] == 1527830400000
@@ -2063,10 +2530,11 @@ async def test___async_get_candle_history_sort(default_conf, mocker, exchange_na
     # Reset sort mock
     sort_mock = mocker.patch('freqtrade.exchange.sorted', MagicMock(side_effect=sort_data))
     # Test the OHLCV data sort
-    res = await exchange._async_get_candle_history('ETH/BTC', default_conf['timeframe'])
+    res = await exchange._async_get_candle_history(
+        'ETH/BTC', default_conf['timeframe'], CandleType.SPOT)
     assert res[0] == 'ETH/BTC'
     assert res[1] == default_conf['timeframe']
-    res_ohlcv = res[2]
+    res_ohlcv = res[3]
     # Sorted not called again - data is already in order
     assert sort_mock.call_count == 0
     assert res_ohlcv[0][0] == 1527827700000
@@ -2088,7 +2556,6 @@ async def test___async_get_candle_history_sort(default_conf, mocker, exchange_na
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
 async def test__async_fetch_trades(default_conf, mocker, caplog, exchange_name,
                                    fetch_trades_result):
-
     caplog.set_level(logging.DEBUG)
     exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
     # Monkey-patch async function
@@ -2132,6 +2599,43 @@ async def test__async_fetch_trades(default_conf, mocker, caplog, exchange_name,
         await exchange._async_fetch_trades(pair, since=(arrow.utcnow().int_timestamp - 2000) * 1000)
 
 
+@pytest.mark.asyncio
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+async def test__async_fetch_trades_contract_size(default_conf, mocker, caplog, exchange_name,
+                                                 fetch_trades_result):
+    caplog.set_level(logging.DEBUG)
+    default_conf['margin_mode'] = 'isolated'
+    default_conf['trading_mode'] = 'futures'
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    # Monkey-patch async function
+    exchange._api_async.fetch_trades = get_mock_coro([
+        {'info': {'a': 126181333,
+                  'p': '0.01952600',
+                  'q': '0.01200000',
+                  'f': 138604158,
+                  'l': 138604158,
+                  'T': 1565798399872,
+                  'm': True,
+                  'M': True},
+         'timestamp': 1565798399872,
+         'datetime': '2019-08-14T15:59:59.872Z',
+         'symbol': 'ETH/USDT:USDT',
+         'id': '126181383',
+         'order': None,
+         'type': None,
+         'takerOrMaker': None,
+         'side': 'sell',
+         'price': 2.0,
+         'amount': 30.0,
+         'cost': 60.0,
+         'fee': None}]
+    )
+
+    pair = 'ETH/USDT:USDT'
+    res = await exchange._async_fetch_trades(pair, since=None, params=None)
+    assert res[0][5] == 300
+
+
 @pytest.mark.asyncio
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
 async def test__async_get_trade_history_id(default_conf, mocker, exchange_name,
@@ -2191,9 +2695,10 @@ async def test__async_get_trade_history_time(default_conf, mocker, caplog, excha
     # Monkey-patch async function
     exchange._api_async.fetch_trades = MagicMock(side_effect=mock_get_trade_hist)
     pair = 'ETH/BTC'
-    ret = await exchange._async_get_trade_history_time(pair,
-                                                       since=fetch_trades_result[0]['timestamp'],
-                                                       until=fetch_trades_result[-1]['timestamp']-1)
+    ret = await exchange._async_get_trade_history_time(
+        pair,
+        since=fetch_trades_result[0]['timestamp'],
+        until=fetch_trades_result[-1]['timestamp'] - 1)
     assert type(ret) is tuple
     assert ret[0] == pair
     assert type(ret[1]) is list
@@ -2229,7 +2734,7 @@ async def test__async_get_trade_history_time_empty(default_conf, mocker, caplog,
     exchange._async_fetch_trades = MagicMock(side_effect=mock_get_trade_hist)
     pair = 'ETH/BTC'
     ret = await exchange._async_get_trade_history_time(pair, since=trades_history[0][0],
-                                                       until=trades_history[-1][0]-1)
+                                                       until=trades_history[-1][0] - 1)
     assert type(ret) is tuple
     assert ret[0] == pair
     assert type(ret[1]) is list
@@ -2284,7 +2789,15 @@ def test_cancel_order_dry_run(default_conf, mocker, exchange_name):
     assert exchange.cancel_order(order_id='123', pair='TKN/BTC') == {}
     assert exchange.cancel_stoploss_order(order_id='123', pair='TKN/BTC') == {}
 
-    order = exchange.create_order('ETH/BTC', 'limit', "buy", 5, 0.55, 'gtc')
+    order = exchange.create_order(
+        pair='ETH/BTC',
+        ordertype='limit',
+        side='buy',
+        amount=5,
+        rate=0.55,
+        time_in_force='gtc',
+        leverage=1.0,
+    )
 
     cancel_order = exchange.cancel_order(order_id=order['id'], pair='ETH/BTC')
     assert order['id'] == cancel_order['id']
@@ -2399,37 +2912,36 @@ def test_cancel_stoploss_order_with_result(default_conf, mocker, exchange_name):
     default_conf['dry_run'] = False
     mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', return_value={'for': 123})
     mocker.patch('freqtrade.exchange.Ftx.fetch_stoploss_order', return_value={'for': 123})
+    mocker.patch('freqtrade.exchange.Gateio.fetch_stoploss_order', return_value={'for': 123})
     exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
 
-    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order',
-                 return_value={'fee': {}, 'status': 'canceled', 'amount': 1234})
-    mocker.patch('freqtrade.exchange.Ftx.cancel_stoploss_order',
-                 return_value={'fee': {}, 'status': 'canceled', 'amount': 1234})
+    res = {'fee': {}, 'status': 'canceled', 'amount': 1234}
+    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', return_value=res)
+    mocker.patch('freqtrade.exchange.Ftx.cancel_stoploss_order', return_value=res)
+    mocker.patch('freqtrade.exchange.Gateio.cancel_stoploss_order', return_value=res)
     co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555)
-    assert co == {'fee': {}, 'status': 'canceled', 'amount': 1234}
+    assert co == res
 
-    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order',
-                 return_value='canceled')
-    mocker.patch('freqtrade.exchange.Ftx.cancel_stoploss_order',
-                 return_value='canceled')
+    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', return_value='canceled')
+    mocker.patch('freqtrade.exchange.Ftx.cancel_stoploss_order', return_value='canceled')
+    mocker.patch('freqtrade.exchange.Gateio.cancel_stoploss_order', return_value='canceled')
     # Fall back to fetch_stoploss_order
     co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555)
     assert co == {'for': 123}
 
-    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order',
-                 side_effect=InvalidOrderException(""))
-    mocker.patch('freqtrade.exchange.Ftx.fetch_stoploss_order',
-                 side_effect=InvalidOrderException(""))
-
+    exc = InvalidOrderException("")
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', side_effect=exc)
+    mocker.patch('freqtrade.exchange.Ftx.fetch_stoploss_order', side_effect=exc)
+    mocker.patch('freqtrade.exchange.Gateio.fetch_stoploss_order', side_effect=exc)
     co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555)
     assert co['amount'] == 555
     assert co == {'fee': {}, 'status': 'canceled', 'amount': 555, 'info': {}}
 
     with pytest.raises(InvalidOrderException):
-        mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order',
-                     side_effect=InvalidOrderException("Did not find order"))
-        mocker.patch('freqtrade.exchange.Ftx.cancel_stoploss_order',
-                     side_effect=InvalidOrderException("Did not find order"))
+        exc = InvalidOrderException("Did not find order")
+        mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', side_effect=exc)
+        mocker.patch('freqtrade.exchange.Ftx.cancel_stoploss_order', side_effect=exc)
+        mocker.patch('freqtrade.exchange.Gateio.cancel_stoploss_order', side_effect=exc)
         exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
         exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=123)
 
@@ -2440,6 +2952,8 @@ def test_fetch_order(default_conf, mocker, exchange_name, caplog):
     default_conf['exchange']['log_responses'] = True
     order = MagicMock()
     order.myid = 123
+    order.symbol = 'TKN/BTC'
+
     exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
     exchange._dry_run_open_orders['X'] = order
     assert exchange.fetch_order('X', 'TKN/BTC').myid == 123
@@ -2449,10 +2963,15 @@ def test_fetch_order(default_conf, mocker, exchange_name, caplog):
 
     default_conf['dry_run'] = False
     api_mock = MagicMock()
-    api_mock.fetch_order = MagicMock(return_value=456)
+    api_mock.fetch_order = MagicMock(return_value={'id': '123', 'amount': 2, 'symbol': 'TKN/BTC'})
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    assert exchange.fetch_order('X', 'TKN/BTC') == 456
-    assert log_has("API fetch_order: 456", caplog)
+    assert exchange.fetch_order(
+        'X', 'TKN/BTC') == {'id': '123', 'amount': 2, 'symbol': 'TKN/BTC'}
+    assert log_has(
+        ("API fetch_order: {\'id\': \'123\', \'amount\': 2, \'symbol\': \'TKN/BTC\'}"
+         ),
+        caplog
+    )
 
     with pytest.raises(InvalidOrderException):
         api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
@@ -2496,9 +3015,9 @@ def test_fetch_stoploss_order(default_conf, mocker, exchange_name):
 
     default_conf['dry_run'] = False
     api_mock = MagicMock()
-    api_mock.fetch_order = MagicMock(return_value=456)
+    api_mock.fetch_order = MagicMock(return_value={'id': '123', 'symbol': 'TKN/BTC'})
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    assert exchange.fetch_stoploss_order('X', 'TKN/BTC') == 456
+    assert exchange.fetch_stoploss_order('X', 'TKN/BTC') == {'id': '123', 'symbol': 'TKN/BTC'}
 
     with pytest.raises(InvalidOrderException):
         api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
@@ -2545,12 +3064,17 @@ def test_name(default_conf, mocker, exchange_name):
     assert exchange.id == exchange_name
 
 
+@pytest.mark.parametrize("trading_mode,amount", [
+    ('spot', 0.2340606),
+    ('futures', 2.340606),
+])
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_trades_for_order(default_conf, mocker, exchange_name):
-
+def test_get_trades_for_order(default_conf, mocker, exchange_name, trading_mode, amount):
     order_id = 'ABCD-ABCD'
     since = datetime(2018, 5, 5, 0, 0, 0)
     default_conf["dry_run"] = False
+    default_conf["trading_mode"] = trading_mode
+    default_conf["margin_mode"] = 'isolated'
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
     api_mock = MagicMock()
 
@@ -2567,22 +3091,24 @@ def test_get_trades_for_order(default_conf, mocker, exchange_name):
                                                                  'id': 'ABCD-ABCD'},
                                                         'timestamp': 1519860024438,
                                                         'datetime': '2018-02-28T23:20:24.438Z',
-                                                        'symbol': 'LTC/BTC',
+                                                        'symbol': 'ETH/USDT:USDT',
                                                         'type': 'limit',
                                                         'side': 'buy',
                                                         'price': 165.0,
                                                         'amount': 0.2340606,
                                                         'fee': {'cost': 0.06179, 'currency': 'BTC'}
                                                         }])
+
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
 
-    orders = exchange.get_trades_for_order(order_id, 'LTC/BTC', since)
+    orders = exchange.get_trades_for_order(order_id, 'ETH/USDT:USDT', since)
     assert len(orders) == 1
     assert orders[0]['price'] == 165
+    assert isclose(orders[0]['amount'], amount)
     assert api_mock.fetch_my_trades.call_count == 1
     # since argument should be
     assert isinstance(api_mock.fetch_my_trades.call_args[0][1], int)
-    assert api_mock.fetch_my_trades.call_args[0][0] == 'LTC/BTC'
+    assert api_mock.fetch_my_trades.call_args[0][0] == 'ETH/USDT:USDT'
     # Same test twice, hardcoded number and doing the same calculation
     assert api_mock.fetch_my_trades.call_args[0][1] == 1525478395000
     assert api_mock.fetch_my_trades.call_args[0][1] == int(since.replace(
@@ -2590,10 +3116,10 @@ def test_get_trades_for_order(default_conf, mocker, exchange_name):
 
     ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
                            'get_trades_for_order', 'fetch_my_trades',
-                           order_id=order_id, pair='LTC/BTC', since=since)
+                           order_id=order_id, pair='ETH/USDT:USDT', since=since)
 
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=False))
-    assert exchange.get_trades_for_order(order_id, 'LTC/BTC', since) == []
+    assert exchange.get_trades_for_order(order_id, 'ETH/USDT:USDT', since) == []
 
 
 @pytest.mark.parametrize("exchange_name", EXCHANGES)
@@ -2624,10 +3150,17 @@ def test_get_fee(default_conf, mocker, exchange_name):
 def test_stoploss_order_unsupported_exchange(default_conf, mocker):
     exchange = get_patched_exchange(mocker, default_conf, id='bittrex')
     with pytest.raises(OperationalException, match=r"stoploss is not implemented .*"):
-        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+        exchange.stoploss(
+            pair='ETH/BTC',
+            amount=1,
+            stop_price=220,
+            order_types={},
+            side="sell",
+            leverage=1.0
+        )
 
     with pytest.raises(OperationalException, match=r"stoploss is not implemented .*"):
-        exchange.stoploss_adjust(1, {})
+        exchange.stoploss_adjust(1, {}, side="sell")
 
 
 def test_merge_ft_has_dict(default_conf, mocker):
@@ -2636,7 +3169,8 @@ def test_merge_ft_has_dict(default_conf, mocker):
                           _load_async_markets=MagicMock(),
                           validate_pairs=MagicMock(),
                           validate_timeframes=MagicMock(),
-                          validate_stakecurrency=MagicMock()
+                          validate_stakecurrency=MagicMock(),
+                          validate_pricing=MagicMock(),
                           )
     ex = Exchange(default_conf)
     assert ex._ft_has == Exchange._ft_has_default
@@ -2670,6 +3204,7 @@ def test_get_valid_pair_combination(default_conf, mocker, markets):
                           _load_async_markets=MagicMock(),
                           validate_pairs=MagicMock(),
                           validate_timeframes=MagicMock(),
+                          validate_pricing=MagicMock(),
                           markets=PropertyMock(return_value=markets))
     ex = Exchange(default_conf)
 
@@ -2680,7 +3215,8 @@ def test_get_valid_pair_combination(default_conf, mocker, markets):
 
 
 @pytest.mark.parametrize(
-    "base_currencies, quote_currencies, pairs_only, active_only, expected_keys", [
+    "base_currencies,quote_currencies,tradable_only,active_only,spot_only,"
+    "futures_only,expected_keys,test_comment", [
         # Testing markets (in conftest.py):
         # 'BLK/BTC':  'active': True
         # 'BTT/BTC':  'active': True
@@ -2694,58 +3230,81 @@ def test_get_valid_pair_combination(default_conf, mocker, markets):
         # 'TKN/BTC':  'active'  not set
         # 'XLTCUSDT': 'active': True, not a pair
         # 'XRP/BTC':  'active': False
-        # all markets
-        ([], [], False, False,
+        ([], [], False, False, False, False,
+         ['BLK/BTC', 'BTT/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD', 'LTC/USDT',
+          'NEO/BTC', 'TKN/BTC', 'XLTCUSDT', 'XRP/BTC', 'ADA/USDT:USDT',
+          'ETH/USDT:USDT'],
+         'all markets'),
+        ([], [], False, False, True, False,
          ['BLK/BTC', 'BTT/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD',
-          'LTC/USDT', 'NEO/BTC', 'TKN/BTC', 'XLTCUSDT', 'XRP/BTC']),
-        # active markets
-        ([], [], False, True,
+          'LTC/USDT', 'NEO/BTC', 'TKN/BTC', 'XRP/BTC'],
+         'all markets, only spot pairs'),
+        ([], [], False, True, False, False,
          ['BLK/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD', 'NEO/BTC',
-          'TKN/BTC', 'XLTCUSDT', 'XRP/BTC']),
-        # all pairs
-        ([], [], True, False,
+          'TKN/BTC', 'XLTCUSDT', 'XRP/BTC', 'ADA/USDT:USDT', 'ETH/USDT:USDT'],
+         'active markets'),
+        ([], [], True, False, False, False,
          ['BLK/BTC', 'BTT/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD',
-          'LTC/USDT', 'NEO/BTC', 'TKN/BTC', 'XRP/BTC']),
-        # active pairs
-        ([], [], True, True,
+          'LTC/USDT', 'NEO/BTC', 'TKN/BTC', 'XRP/BTC'],
+         'all pairs'),
+        ([], [], True, True, False, False,
          ['BLK/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD', 'NEO/BTC',
-          'TKN/BTC', 'XRP/BTC']),
-        # all markets, base=ETH, LTC
-        (['ETH', 'LTC'], [], False, False,
-         ['ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD', 'LTC/USDT', 'XLTCUSDT']),
-        # all markets, base=LTC
-        (['LTC'], [], False, False,
-         ['LTC/BTC', 'LTC/ETH', 'LTC/USD', 'LTC/USDT', 'XLTCUSDT']),
-        # all markets, quote=USDT
-        ([], ['USDT'], False, False,
-         ['ETH/USDT', 'LTC/USDT', 'XLTCUSDT']),
-        # all markets, quote=USDT, USD
-        ([], ['USDT', 'USD'], False, False,
-         ['ETH/USDT', 'LTC/USD', 'LTC/USDT', 'XLTCUSDT']),
-        # all markets, base=LTC, quote=USDT
-        (['LTC'], ['USDT'], False, False,
-         ['LTC/USDT', 'XLTCUSDT']),
-        # all pairs, base=LTC, quote=USDT
-        (['LTC'], ['USDT'], True, False,
-         ['LTC/USDT']),
-        # all markets, base=LTC, quote=USDT, NONEXISTENT
-        (['LTC'], ['USDT', 'NONEXISTENT'], False, False,
-         ['LTC/USDT', 'XLTCUSDT']),
-        # all markets, base=LTC, quote=NONEXISTENT
-        (['LTC'], ['NONEXISTENT'], False, False,
-         []),
+          'TKN/BTC', 'XRP/BTC'],
+         'active pairs'),
+        (['ETH', 'LTC'], [], False, False, False, False,
+         ['ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD', 'LTC/USDT', 'XLTCUSDT',
+          'ETH/USDT:USDT'],
+         'all markets, base=ETH, LTC'),
+        (['LTC'], [], False, False, False, False,
+         ['LTC/BTC', 'LTC/ETH', 'LTC/USD', 'LTC/USDT', 'XLTCUSDT'],
+         'all markets, base=LTC'),
+        (['LTC'], [], False, False, True, False,
+         ['LTC/BTC', 'LTC/ETH', 'LTC/USD', 'LTC/USDT'],
+         'spot markets, base=LTC'),
+        ([], ['USDT'], False, False, False, False,
+         ['ETH/USDT', 'LTC/USDT', 'XLTCUSDT', 'ADA/USDT:USDT', 'ETH/USDT:USDT'],
+         'all markets, quote=USDT'),
+        ([], ['USDT'], False, False, False, True,
+         ['ADA/USDT:USDT', 'ETH/USDT:USDT'],
+         'Futures markets, quote=USDT'),
+        ([], ['USDT', 'USD'], False, False, False, False,
+         ['ETH/USDT', 'LTC/USD', 'LTC/USDT', 'XLTCUSDT', 'ADA/USDT:USDT', 'ETH/USDT:USDT'],
+         'all markets, quote=USDT, USD'),
+        ([], ['USDT', 'USD'], False, False, True, False,
+         ['ETH/USDT', 'LTC/USD', 'LTC/USDT'],
+         'spot markets, quote=USDT, USD'),
+        (['LTC'], ['USDT'], False, False, False, False,
+         ['LTC/USDT', 'XLTCUSDT'],
+         'all markets, base=LTC, quote=USDT'),
+        (['LTC'], ['USDT'], True, False, False, False,
+         ['LTC/USDT'],
+         'all pairs, base=LTC, quote=USDT'),
+        (['LTC'], ['USDT', 'NONEXISTENT'], False, False, False, False,
+         ['LTC/USDT', 'XLTCUSDT'],
+         'all markets, base=LTC, quote=USDT, NONEXISTENT'),
+        (['LTC'], ['NONEXISTENT'], False, False, False, False,
+         [],
+         'all markets, base=LTC, quote=NONEXISTENT'),
     ])
-def test_get_markets(default_conf, mocker, markets,
-                     base_currencies, quote_currencies, pairs_only, active_only,
-                     expected_keys):
+def test_get_markets(default_conf, mocker, markets_static,
+                     base_currencies, quote_currencies, tradable_only, active_only,
+                     spot_only, futures_only, expected_keys,
+                     test_comment  # Here for debugging purposes (Not used within method)
+                     ):
     mocker.patch.multiple('freqtrade.exchange.Exchange',
                           _init_ccxt=MagicMock(return_value=MagicMock()),
                           _load_async_markets=MagicMock(),
                           validate_pairs=MagicMock(),
                           validate_timeframes=MagicMock(),
-                          markets=PropertyMock(return_value=markets))
+                          validate_pricing=MagicMock(),
+                          markets=PropertyMock(return_value=markets_static))
     ex = Exchange(default_conf)
-    pairs = ex.get_markets(base_currencies, quote_currencies, pairs_only, active_only)
+    pairs = ex.get_markets(base_currencies,
+                           quote_currencies,
+                           tradable_only=tradable_only,
+                           spot_only=spot_only,
+                           futures_only=futures_only,
+                           active_only=active_only)
     assert sorted(pairs.keys()) == sorted(expected_keys)
 
 
@@ -2816,6 +3375,8 @@ def test_timeframe_to_prev_date():
     # Does not round
     time = datetime(2019, 8, 12, 13, 20, 0, tzinfo=timezone.utc)
     assert timeframe_to_prev_date('5m', time) == time
+    time = datetime(2019, 8, 12, 13, 0, 0, tzinfo=timezone.utc)
+    assert timeframe_to_prev_date('1h', time) == time
 
 
 def test_timeframe_to_next_date():
@@ -2846,39 +3407,64 @@ def test_timeframe_to_next_date():
     assert timeframe_to_next_date("5m", date) == date + timedelta(minutes=5)
 
 
-@pytest.mark.parametrize("market_symbol,base,quote,exchange,add_dict,expected_result", [
-    ("BTC/USDT", 'BTC', 'USDT', "binance", {}, True),
-    ("USDT/BTC", 'USDT', 'BTC', "binance", {}, True),
-    ("USDT/BTC", 'BTC', 'USDT', "binance", {}, False),  # Reversed currencies
-    ("BTCUSDT", 'BTC', 'USDT', "binance", {}, False),  # No seperating /
-    ("BTCUSDT", None, "USDT", "binance", {}, False),  #
-    ("USDT/BTC", "BTC", None, "binance", {}, False),
-    ("BTCUSDT", "BTC", None, "binance", {}, False),
-    ("BTC/USDT", "BTC", "USDT", "binance", {}, True),
-    ("BTC/USDT", "USDT", "BTC", "binance", {}, False),  # reversed currencies
-    ("BTC/USDT", "BTC", "USD", "binance", {}, False),  # Wrong quote currency
-    ("BTC/", "BTC", 'UNK', "binance", {}, False),
-    ("/USDT", 'UNK', 'USDT', "binance", {}, False),
-    ("BTC/EUR", 'BTC', 'EUR', "kraken", {"darkpool": False}, True),
-    ("EUR/BTC", 'EUR', 'BTC', "kraken", {"darkpool": False}, True),
-    ("EUR/BTC", 'BTC', 'EUR', "kraken", {"darkpool": False}, False),  # Reversed currencies
-    ("BTC/EUR", 'BTC', 'USD', "kraken", {"darkpool": False}, False),  # wrong quote currency
-    ("BTC/EUR", 'BTC', 'EUR', "kraken", {"darkpool": True}, False),  # no darkpools
-    ("BTC/EUR.d", 'BTC', 'EUR', "kraken", {"darkpool": True}, False),  # no darkpools
-    ("BTC/USD", 'BTC', 'USD', "ftx", {'spot': True}, True),
-    ("USD/BTC", 'USD', 'BTC', "ftx", {'spot': True}, True),
-    ("BTC/USD", 'BTC', 'USDT', "ftx", {'spot': True}, False),  # Wrong quote currency
-    ("BTC/USD", 'USD', 'BTC', "ftx", {'spot': True}, False),  # Reversed currencies
-    ("BTC/USD", 'BTC', 'USD', "ftx", {'spot': False}, False),  # Can only trade spot markets
-    ("BTC-PERP", 'BTC', 'USD', "ftx", {'spot': False}, False),  # Can only trade spot markets
-])
-def test_market_is_tradable(mocker, default_conf, market_symbol, base,
-                            quote, add_dict, exchange, expected_result) -> None:
+@pytest.mark.parametrize(
+    "market_symbol,base,quote,exchange,spot,margin,futures,trademode,add_dict,expected_result",
+    [
+        ("BTC/USDT", 'BTC', 'USDT', "binance", True, False, False, 'spot', {}, True),
+        ("USDT/BTC", 'USDT', 'BTC', "binance", True, False, False, 'spot', {}, True),
+        # No seperating /
+        ("BTCUSDT", 'BTC', 'USDT', "binance", True, False, False, 'spot', {}, True),
+        ("BTCUSDT", None, "USDT", "binance", True, False, False, 'spot', {}, False),
+        ("USDT/BTC", "BTC", None, "binance", True, False, False, 'spot', {}, False),
+        ("BTCUSDT", "BTC", None, "binance", True, False, False, 'spot', {}, False),
+        ("BTC/USDT", "BTC", "USDT", "binance", True, False, False, 'spot', {}, True),
+        # Futures mode, spot pair
+        ("BTC/USDT", "BTC", "USDT", "binance", True, False, False, 'futures', {}, False),
+        ("BTC/USDT", "BTC", "USDT", "binance", True, False, False, 'margin', {}, False),
+        ("BTC/USDT", "BTC", "USDT", "binance", True, True, True, 'margin', {}, True),
+        ("BTC/USDT", "BTC", "USDT", "binance", False, True, False, 'margin', {}, True),
+        # Futures mode, futures pair
+        ("BTC/USDT", "BTC", "USDT", "binance", False, False, True, 'futures', {}, True),
+        # Futures market
+        ("BTC/UNK", "BTC", 'UNK', "binance", False, False, True, 'spot', {}, False),
+        ("BTC/EUR", 'BTC', 'EUR', "kraken", True, False, False, 'spot', {"darkpool": False}, True),
+        ("EUR/BTC", 'EUR', 'BTC', "kraken", True, False, False, 'spot', {"darkpool": False}, True),
+        # no darkpools
+        ("BTC/EUR", 'BTC', 'EUR', "kraken", True, False, False, 'spot',
+         {"darkpool": True}, False),
+        # no darkpools
+        ("BTC/EUR.d", 'BTC', 'EUR', "kraken", True, False, False, 'spot',
+         {"darkpool": True}, False),
+        ("BTC/USD", 'BTC', 'USD', "ftx", True, False, False, 'spot', {}, True),
+        ("USD/BTC", 'USD', 'BTC', "ftx", True, False, False, 'spot', {}, True),
+        # Can only trade spot markets
+        ("BTC/USD", 'BTC', 'USD', "ftx", False, False, True, 'spot', {}, False),
+        ("BTC/USD", 'BTC', 'USD', "ftx", False, False, True, 'futures', {}, True),
+        # Can only trade spot markets
+        ("BTC-PERP", 'BTC', 'USD', "ftx", False, False, True, 'spot', {}, False),
+        ("BTC-PERP", 'BTC', 'USD', "ftx", False, False, True, 'margin', {}, False),
+        ("BTC-PERP", 'BTC', 'USD', "ftx", False, False, True, 'futures', {}, True),
+
+        ("BTC/USDT:USDT", 'BTC', 'USD', "okx", False, False, True, 'spot', {}, False),
+        ("BTC/USDT:USDT", 'BTC', 'USD', "okx", False, False, True, 'margin', {}, False),
+        ("BTC/USDT:USDT", 'BTC', 'USD', "okx", False, False, True, 'futures', {}, True),
+    ])
+def test_market_is_tradable(
+        mocker, default_conf, market_symbol, base,
+        quote, spot, margin, futures, trademode, add_dict, exchange, expected_result
+) -> None:
+    default_conf['trading_mode'] = trademode
+    mocker.patch('freqtrade.exchange.exchange.Exchange.validate_trading_mode_and_margin_mode')
     ex = get_patched_exchange(mocker, default_conf, id=exchange)
     market = {
         'symbol': market_symbol,
         'base': base,
         'quote': quote,
+        'spot': spot,
+        'future': futures,
+        'swap': futures,
+        'margin': margin,
+        'linear': True,
         **(add_dict),
     }
     assert ex.market_is_tradable(market) == expected_result
@@ -2918,39 +3504,49 @@ def test_extract_cost_curr_rate(mocker, default_conf, order, expected) -> None:
     assert ex.extract_cost_curr_rate(order) == expected
 
 
-@pytest.mark.parametrize("order,expected", [
+@pytest.mark.parametrize("order,unknown_fee_rate,expected", [
     # Using base-currency
     ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
-        'fee': {'currency': 'ETH', 'cost': 0.004, 'rate': None}}, 0.1),
+        'fee': {'currency': 'ETH', 'cost': 0.004, 'rate': None}}, None, 0.1),
     ({'symbol': 'ETH/BTC', 'amount': 0.05, 'cost': 0.05,
-        'fee': {'currency': 'ETH', 'cost': 0.004, 'rate': None}}, 0.08),
+        'fee': {'currency': 'ETH', 'cost': 0.004, 'rate': None}}, None, 0.08),
     # Using quote currency
     ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
-        'fee': {'currency': 'BTC', 'cost': 0.005}}, 0.1),
+        'fee': {'currency': 'BTC', 'cost': 0.005}}, None, 0.1),
     ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
-        'fee': {'currency': 'BTC', 'cost': 0.002, 'rate': None}}, 0.04),
+        'fee': {'currency': 'BTC', 'cost': 0.002, 'rate': None}}, None, 0.04),
     # Using foreign currency
     ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
-        'fee': {'currency': 'NEO', 'cost': 0.0012}}, 0.001944),
+        'fee': {'currency': 'NEO', 'cost': 0.0012}}, None, 0.001944),
     ({'symbol': 'ETH/BTC', 'amount': 2.21, 'cost': 0.02992561,
-        'fee': {'currency': 'NEO', 'cost': 0.00027452}}, 0.00074305),
+        'fee': {'currency': 'NEO', 'cost': 0.00027452}}, None, 0.00074305),
     # Rate included in return - return as is
     ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
-        'fee': {'currency': 'USDT', 'cost': 0.34, 'rate': 0.01}}, 0.01),
+        'fee': {'currency': 'USDT', 'cost': 0.34, 'rate': 0.01}}, None, 0.01),
     ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
-        'fee': {'currency': 'USDT', 'cost': 0.34, 'rate': 0.005}}, 0.005),
+        'fee': {'currency': 'USDT', 'cost': 0.34, 'rate': 0.005}}, None, 0.005),
     # 0.1% filled - no costs (kraken - #3431)
     ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.0,
-      'fee': {'currency': 'BTC', 'cost': 0.0, 'rate': None}}, None),
+      'fee': {'currency': 'BTC', 'cost': 0.0, 'rate': None}}, None, None),
     ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.0,
-      'fee': {'currency': 'ETH', 'cost': 0.0, 'rate': None}}, 0.0),
+      'fee': {'currency': 'ETH', 'cost': 0.0, 'rate': None}}, None, 0.0),
     ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.0,
-      'fee': {'currency': 'NEO', 'cost': 0.0, 'rate': None}}, None),
+      'fee': {'currency': 'NEO', 'cost': 0.0, 'rate': None}}, None, None),
+    # Invalid pair combination - POINT/BTC is not a pair
+    ({'symbol': 'POINT/BTC', 'amount': 0.04, 'cost': 0.5,
+      'fee': {'currency': 'POINT', 'cost': 2.0, 'rate': None}}, None, None),
+    ({'symbol': 'POINT/BTC', 'amount': 0.04, 'cost': 0.5,
+      'fee': {'currency': 'POINT', 'cost': 2.0, 'rate': None}}, 1, 4.0),
+    ({'symbol': 'POINT/BTC', 'amount': 0.04, 'cost': 0.5,
+      'fee': {'currency': 'POINT', 'cost': 2.0, 'rate': None}}, 2, 8.0),
 ])
-def test_calculate_fee_rate(mocker, default_conf, order, expected) -> None:
+def test_calculate_fee_rate(mocker, default_conf, order, expected, unknown_fee_rate) -> None:
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', return_value={'last': 0.081})
+    if unknown_fee_rate:
+        default_conf['exchange']['unknown_fee_rate'] = unknown_fee_rate
 
     ex = get_patched_exchange(mocker, default_conf)
+
     assert ex.calculate_fee_rate(order) == expected
 
 
@@ -2972,7 +3568,1366 @@ def test_calculate_fee_rate(mocker, default_conf, order, expected) -> None:
     (3, 5, 5),
     (4, 5, 2),
     (5, 5, 1),
-
 ])
 def test_calculate_backoff(retrycount, max_retries, expected):
     assert calculate_backoff(retrycount, max_retries) == expected
+
+
+@pytest.mark.parametrize("exchange_name", ['binance', 'ftx'])
+def test__get_funding_fees_from_exchange(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    api_mock.fetch_funding_history = MagicMock(return_value=[
+        {
+            'amount': 0.14542,
+            'code': 'USDT',
+            'datetime': '2021-09-01T08:00:01.000Z',
+            'id': '485478',
+            'info': {'asset': 'USDT',
+                     'income': '0.14542',
+                     'incomeType': 'FUNDING_FEE',
+                     'info': 'FUNDING_FEE',
+                     'symbol': 'XRPUSDT',
+                     'time': '1630382001000',
+                     'tradeId': '',
+                     'tranId': '993203'},
+            'symbol': 'XRP/USDT',
+            'timestamp': 1630382001000
+        },
+        {
+            'amount': -0.14642,
+            'code': 'USDT',
+            'datetime': '2021-09-01T16:00:01.000Z',
+            'id': '485479',
+            'info': {'asset': 'USDT',
+                     'income': '-0.14642',
+                     'incomeType': 'FUNDING_FEE',
+                     'info': 'FUNDING_FEE',
+                     'symbol': 'XRPUSDT',
+                     'time': '1630314001000',
+                     'tradeId': '',
+                     'tranId': '993204'},
+            'symbol': 'XRP/USDT',
+            'timestamp': 1630314001000
+        }
+    ])
+    type(api_mock).has = PropertyMock(return_value={'fetchFundingHistory': True})
+
+    # mocker.patch('freqtrade.exchange.Exchange.get_funding_fees', lambda pair, since: y)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    date_time = datetime.strptime("2021-09-01T00:00:01.000Z", '%Y-%m-%dT%H:%M:%S.%fZ')
+    unix_time = int(date_time.timestamp())
+    expected_fees = -0.001  # 0.14542341 + -0.14642341
+    fees_from_datetime = exchange._get_funding_fees_from_exchange(
+        pair='XRP/USDT',
+        since=date_time
+    )
+    fees_from_unix_time = exchange._get_funding_fees_from_exchange(
+        pair='XRP/USDT',
+        since=unix_time
+    )
+
+    assert(isclose(expected_fees, fees_from_datetime))
+    assert(isclose(expected_fees, fees_from_unix_time))
+
+    ccxt_exceptionhandlers(
+        mocker,
+        default_conf,
+        api_mock,
+        exchange_name,
+        "_get_funding_fees_from_exchange",
+        "fetch_funding_history",
+        pair="XRP/USDT",
+        since=unix_time
+    )
+
+
+@pytest.mark.parametrize('exchange', ['binance', 'kraken', 'ftx'])
+@pytest.mark.parametrize('stake_amount,leverage,min_stake_with_lev', [
+    (9.0, 3.0, 3.0),
+    (20.0, 5.0, 4.0),
+    (100.0, 100.0, 1.0)
+])
+def test_get_stake_amount_considering_leverage(
+    exchange,
+    stake_amount,
+    leverage,
+    min_stake_with_lev,
+    mocker,
+    default_conf
+):
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange)
+    assert exchange._get_stake_amount_considering_leverage(
+        stake_amount, leverage) == min_stake_with_lev
+
+
+@pytest.mark.parametrize("exchange_name,trading_mode", [
+    ("binance", TradingMode.FUTURES),
+    ("ftx", TradingMode.MARGIN),
+    ("ftx", TradingMode.FUTURES)
+])
+def test__set_leverage(mocker, default_conf, exchange_name, trading_mode):
+
+    api_mock = MagicMock()
+    api_mock.set_leverage = MagicMock()
+    type(api_mock).has = PropertyMock(return_value={'setLeverage': True})
+    default_conf['dry_run'] = False
+
+    ccxt_exceptionhandlers(
+        mocker,
+        default_conf,
+        api_mock,
+        exchange_name,
+        "_set_leverage",
+        "set_leverage",
+        pair="XRP/USDT",
+        leverage=5.0,
+        trading_mode=trading_mode
+    )
+
+
+@pytest.mark.parametrize("margin_mode", [
+    (MarginMode.CROSS),
+    (MarginMode.ISOLATED)
+])
+def test_set_margin_mode(mocker, default_conf, margin_mode):
+
+    api_mock = MagicMock()
+    api_mock.set_margin_mode = MagicMock()
+    type(api_mock).has = PropertyMock(return_value={'setMarginMode': True})
+    default_conf['dry_run'] = False
+
+    ccxt_exceptionhandlers(
+        mocker,
+        default_conf,
+        api_mock,
+        "binance",
+        "set_margin_mode",
+        "set_margin_mode",
+        pair="XRP/USDT",
+        margin_mode=margin_mode
+    )
+
+
+@pytest.mark.parametrize("exchange_name, trading_mode, margin_mode, exception_thrown", [
+    ("binance", TradingMode.SPOT, None, False),
+    ("binance", TradingMode.MARGIN, MarginMode.ISOLATED, True),
+    ("kraken", TradingMode.SPOT, None, False),
+    ("kraken", TradingMode.MARGIN, MarginMode.ISOLATED, True),
+    ("kraken", TradingMode.FUTURES, MarginMode.ISOLATED, True),
+    ("ftx", TradingMode.SPOT, None, False),
+    ("ftx", TradingMode.MARGIN, MarginMode.ISOLATED, True),
+    ("ftx", TradingMode.FUTURES, MarginMode.ISOLATED, True),
+    ("bittrex", TradingMode.SPOT, None, False),
+    ("bittrex", TradingMode.MARGIN, MarginMode.CROSS, True),
+    ("bittrex", TradingMode.MARGIN, MarginMode.ISOLATED, True),
+    ("bittrex", TradingMode.FUTURES, MarginMode.CROSS, True),
+    ("bittrex", TradingMode.FUTURES, MarginMode.ISOLATED, True),
+    ("gateio", TradingMode.MARGIN, MarginMode.ISOLATED, True),
+    ("okx", TradingMode.SPOT, None, False),
+    ("okx", TradingMode.MARGIN, MarginMode.CROSS, True),
+    ("okx", TradingMode.MARGIN, MarginMode.ISOLATED, True),
+    ("okx", TradingMode.FUTURES, MarginMode.CROSS, True),
+
+    ("binance", TradingMode.FUTURES, MarginMode.ISOLATED, False),
+    ("gateio", TradingMode.FUTURES, MarginMode.ISOLATED, False),
+    ("okx", TradingMode.FUTURES, MarginMode.ISOLATED, False),
+
+    # * Remove once implemented
+    ("binance", TradingMode.MARGIN, MarginMode.CROSS, True),
+    ("binance", TradingMode.FUTURES, MarginMode.CROSS, True),
+    ("kraken", TradingMode.MARGIN, MarginMode.CROSS, True),
+    ("kraken", TradingMode.FUTURES, MarginMode.CROSS, True),
+    ("ftx", TradingMode.MARGIN, MarginMode.CROSS, True),
+    ("ftx", TradingMode.FUTURES, MarginMode.CROSS, True),
+    ("gateio", TradingMode.MARGIN, MarginMode.CROSS, True),
+    ("gateio", TradingMode.FUTURES, MarginMode.CROSS, True),
+
+    # * Uncomment once implemented
+    # ("binance", TradingMode.MARGIN, MarginMode.CROSS, False),
+    # ("binance", TradingMode.FUTURES, MarginMode.CROSS, False),
+    # ("kraken", TradingMode.MARGIN, MarginMode.CROSS, False),
+    # ("kraken", TradingMode.FUTURES, MarginMode.CROSS, False),
+    # ("ftx", TradingMode.MARGIN, MarginMode.CROSS, False),
+    # ("ftx", TradingMode.FUTURES, MarginMode.CROSS, False),
+    # ("gateio", TradingMode.MARGIN, MarginMode.CROSS, False),
+    # ("gateio", TradingMode.FUTURES, MarginMode.CROSS, False),
+])
+def test_validate_trading_mode_and_margin_mode(
+    default_conf,
+    mocker,
+    exchange_name,
+    trading_mode,
+    margin_mode,
+    exception_thrown
+):
+    exchange = get_patched_exchange(
+        mocker, default_conf, id=exchange_name, mock_supported_modes=False)
+    if (exception_thrown):
+        with pytest.raises(OperationalException):
+            exchange.validate_trading_mode_and_margin_mode(trading_mode, margin_mode)
+    else:
+        exchange.validate_trading_mode_and_margin_mode(trading_mode, margin_mode)
+
+
+@pytest.mark.parametrize("exchange_name,trading_mode,ccxt_config", [
+    ("binance", "spot", {}),
+    ("binance", "margin", {"options": {"defaultType": "margin"}}),
+    ("binance", "futures", {"options": {"defaultType": "future"}}),
+    ("bibox", "spot", {"has": {"fetchCurrencies": False}}),
+    ("bibox", "margin", {"has": {"fetchCurrencies": False}, "options": {"defaultType": "margin"}}),
+    ("bibox", "futures", {"has": {"fetchCurrencies": False}, "options": {"defaultType": "swap"}}),
+    ("bybit", "futures", {"options": {"defaultType": "linear"}}),
+    ("ftx", "futures", {"options": {"defaultType": "swap"}}),
+    ("gateio", "futures", {"options": {"defaultType": "swap"}}),
+    ("hitbtc", "futures", {"options": {"defaultType": "swap"}}),
+    ("kraken", "futures", {"options": {"defaultType": "swap"}}),
+    ("kucoin", "futures", {"options": {"defaultType": "swap"}}),
+    ("okx", "futures", {"options": {"defaultType": "swap"}}),
+])
+def test__ccxt_config(
+    default_conf,
+    mocker,
+    exchange_name,
+    trading_mode,
+    ccxt_config
+):
+    default_conf['trading_mode'] = trading_mode
+    default_conf['margin_mode'] = 'isolated'
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    assert exchange._ccxt_config == ccxt_config
+
+
+@pytest.mark.parametrize('pair,nominal_value,max_lev', [
+    ("ETH/BTC", 0.0, 2.0),
+    ("TKN/BTC", 100.0, 5.0),
+    ("BLK/BTC", 173.31, 3.0),
+    ("LTC/BTC", 0.0, 1.0),
+    ("TKN/USDT", 210.30, 1.0),
+])
+def test_get_max_leverage_from_margin(default_conf, mocker, pair, nominal_value, max_lev):
+    default_conf['trading_mode'] = 'margin'
+    default_conf['margin_mode'] = 'isolated'
+    api_mock = MagicMock()
+    type(api_mock).has = PropertyMock(return_value={'fetchLeverageTiers': False})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="gateio")
+    assert exchange.get_max_leverage(pair, nominal_value) == max_lev
+
+
+@pytest.mark.parametrize(
+    'size,funding_rate,mark_price,time_in_ratio,funding_fee,kraken_fee', [
+        (10, 0.0001, 2.0, 1.0, 0.002, 0.002),
+        (10, 0.0002, 2.0, 0.01, 0.004, 0.00004),
+        (10, 0.0002, 2.5, None, 0.005, None),
+    ])
+def test_calculate_funding_fees(
+    default_conf,
+    mocker,
+    size,
+    funding_rate,
+    mark_price,
+    funding_fee,
+    kraken_fee,
+    time_in_ratio
+):
+    exchange = get_patched_exchange(mocker, default_conf)
+    kraken = get_patched_exchange(mocker, default_conf, id="kraken")
+    prior_date = timeframe_to_prev_date('1h', datetime.now(timezone.utc) - timedelta(hours=1))
+    trade_date = timeframe_to_prev_date('1h', datetime.now(timezone.utc))
+    funding_rates = DataFrame([
+        {'date': prior_date, 'open': funding_rate},  # Line not used.
+        {'date': trade_date, 'open': funding_rate},
+    ])
+    mark_rates = DataFrame([
+        {'date': prior_date, 'open': mark_price},
+        {'date': trade_date, 'open': mark_price},
+    ])
+    df = exchange.combine_funding_and_mark(funding_rates, mark_rates)
+
+    assert exchange.calculate_funding_fees(
+        df,
+        amount=size,
+        is_short=True,
+        open_date=trade_date,
+        close_date=trade_date,
+        time_in_ratio=time_in_ratio,
+    ) == funding_fee
+
+    if (kraken_fee is None):
+        with pytest.raises(OperationalException):
+            kraken.calculate_funding_fees(
+                df,
+                amount=size,
+                is_short=True,
+                open_date=trade_date,
+                close_date=trade_date,
+                time_in_ratio=time_in_ratio,
+            )
+
+    else:
+        assert kraken.calculate_funding_fees(
+            df,
+            amount=size,
+            is_short=True,
+            open_date=trade_date,
+            close_date=trade_date,
+            time_in_ratio=time_in_ratio,
+        ) == kraken_fee
+
+
+def test_get_or_calculate_liquidation_price(mocker, default_conf):
+
+    api_mock = MagicMock()
+    positions = [
+        {
+            'info': {},
+            'symbol': 'NEAR/USDT:USDT',
+            'timestamp': 1642164737148,
+            'datetime': '2022-01-14T12:52:17.148Z',
+            'initialMargin': 1.51072,
+            'initialMarginPercentage': 0.1,
+            'maintenanceMargin': 0.38916147,
+            'maintenanceMarginPercentage': 0.025,
+            'entryPrice': 18.884,
+            'notional': 15.1072,
+            'leverage': 9.97,
+            'unrealizedPnl': 0.0048,
+            'contracts': 8,
+            'contractSize': 0.1,
+            'marginRatio': None,
+            'liquidationPrice': 17.47,
+            'markPrice': 18.89,
+            'margin_mode': 1.52549075,
+            'marginType': 'isolated',
+            'side': 'buy',
+            'percentage': 0.003177292946409658
+        }
+    ]
+    api_mock.fetch_positions = MagicMock(return_value=positions)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        exchange_has=MagicMock(return_value=True),
+    )
+    default_conf['dry_run'] = False
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    default_conf['liquidation_buffer'] = 0.0
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    liq_price = exchange.get_or_calculate_liquidation_price(
+        pair='NEAR/USDT:USDT',
+        open_rate=18.884,
+        is_short=False,
+        position=0.8,
+        wallet_balance=0.8,
+    )
+    assert liq_price == 17.47
+
+    default_conf['liquidation_buffer'] = 0.05
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    liq_price = exchange.get_or_calculate_liquidation_price(
+        pair='NEAR/USDT:USDT',
+        open_rate=18.884,
+        is_short=False,
+        position=0.8,
+        wallet_balance=0.8,
+    )
+    assert liq_price == 17.540699999999998
+
+    ccxt_exceptionhandlers(
+        mocker,
+        default_conf,
+        api_mock,
+        "binance",
+        "get_or_calculate_liquidation_price",
+        "fetch_positions",
+        pair="XRP/USDT",
+        open_rate=0.0,
+        is_short=False,
+        position=0.0,
+        wallet_balance=0.0,
+    )
+
+
+@pytest.mark.parametrize('exchange,rate_start,rate_end,d1,d2,amount,expected_fees', [
+    ('binance', 0, 2, "2021-09-01 01:00:00", "2021-09-01 04:00:00",  30.0, 0.0),
+    ('binance', 0, 2, "2021-09-01 00:00:00", "2021-09-01 08:00:00",  30.0, -0.00091409999),
+    ('binance', 0, 2, "2021-09-01 00:00:15", "2021-09-01 08:00:00",  30.0, -0.0002493),
+    ('binance', 1, 2, "2021-09-01 01:00:14", "2021-09-01 08:00:00",  30.0, -0.0002493),
+    ('binance', 1, 2, "2021-09-01 00:00:16", "2021-09-01 08:00:00",  30.0, -0.0002493),
+    ('binance', 0, 1, "2021-09-01 00:00:00", "2021-09-01 07:59:59",  30.0, -0.00066479999),
+    ('binance', 0, 2, "2021-09-01 00:00:00", "2021-09-01 12:00:00",  30.0, -0.00091409999),
+    ('binance', 0, 2, "2021-09-01 00:00:01", "2021-09-01 08:00:00",  30.0, -0.0002493),
+    # TODO: Uncoment once _calculate_funding_fees can pas time_in_ratio to exchange._get_funding_fee
+    # ('kraken', "2021-09-01 00:00:00", "2021-09-01 08:00:00",  30.0, -0.0014937),
+    # ('kraken', "2021-09-01 00:00:15", "2021-09-01 08:00:00",  30.0, -0.0008289),
+    # ('kraken', "2021-09-01 01:00:14", "2021-09-01 08:00:00",  30.0, -0.0008289),
+    # ('kraken', "2021-09-01 00:00:00", "2021-09-01 07:59:59",  30.0, -0.0012443999999999999),
+    # ('kraken', "2021-09-01 00:00:00", "2021-09-01 12:00:00", 30.0,  0.0045759),
+    # ('kraken', "2021-09-01 00:00:01", "2021-09-01 08:00:00",  30.0, -0.0008289),
+    ('ftx', 0, 2, "2021-09-01 00:10:00", "2021-09-01 00:30:00",  30.0, 0.0),
+    ('ftx', 0, 9, "2021-09-01 00:00:00", "2021-09-01 08:00:00", 30.0,  0.0010008),
+    ('ftx', 0, 13, "2021-09-01 00:00:00", "2021-09-01 12:00:00", 30.0,  0.0146691),
+    ('ftx', 0, 9, "2021-09-01 00:00:00", "2021-09-01 08:00:00", 50.0,  0.001668),
+    ('ftx', 1, 9, "2021-09-01 00:00:01", "2021-09-01 08:00:00", 30.0,  0.0019932),
+    ('gateio', 0, 2, "2021-09-01 00:10:00", "2021-09-01 04:00:00",  30.0, 0.0),
+    ('gateio', 0, 2, "2021-09-01 00:00:00", "2021-09-01 08:00:00",  30.0, -0.0009140999),
+    ('gateio', 0, 2, "2021-09-01 00:00:00", "2021-09-01 12:00:00",  30.0, -0.0009140999),
+    ('gateio', 1, 2, "2021-09-01 00:00:01", "2021-09-01 08:00:00",  30.0, -0.0002493),
+    ('binance', 0,  2, "2021-09-01 00:00:00", "2021-09-01 08:00:00",  50.0, -0.0015235),
+    # TODO: Uncoment once _calculate_funding_fees can pas time_in_ratio to exchange._get_funding_fee
+    # ('kraken', "2021-09-01 00:00:00", "2021-09-01 08:00:00",  50.0, -0.0024895),
+])
+def test__fetch_and_calculate_funding_fees(
+    mocker,
+    default_conf,
+    funding_rate_history_hourly,
+    funding_rate_history_octohourly,
+    rate_start,
+    rate_end,
+    mark_ohlcv,
+    exchange,
+    d1,
+    d2,
+    amount,
+    expected_fees
+):
+    """
+    nominal_value = mark_price * size
+    funding_fee = nominal_value * funding_rate
+    size: 30
+        time: 0, mark: 2.77, nominal_value: 83.1, fundRate: -0.000008, fundFee: -0.0006648
+        time: 1, mark: 2.73, nominal_value: 81.9, fundRate: -0.000004, fundFee: -0.0003276
+        time: 2, mark: 2.74, nominal_value: 82.2, fundRate: 0.000012, fundFee: 0.0009864
+        time: 3, mark: 2.76, nominal_value: 82.8, fundRate: -0.000003, fundFee: -0.0002484
+        time: 4, mark: 2.76, nominal_value: 82.8, fundRate: -0.000007, fundFee: -0.0005796
+        time: 5, mark: 2.77, nominal_value: 83.1, fundRate: 0.000003, fundFee: 0.0002493
+        time: 6, mark: 2.78, nominal_value: 83.4, fundRate: 0.000019, fundFee: 0.0015846
+        time: 7, mark: 2.78, nominal_value: 83.4, fundRate: 0.000003, fundFee: 0.0002502
+        time: 8, mark: 2.77, nominal_value: 83.1, fundRate: -0.000003, fundFee: -0.0002493
+        time: 9, mark: 2.77, nominal_value: 83.1, fundRate: 0, fundFee: 0.0
+        time: 10, mark: 2.84, nominal_value: 85.2, fundRate: 0.000013, fundFee: 0.0011076
+        time: 11, mark: 2.81, nominal_value: 84.3, fundRate: 0.000077, fundFee: 0.0064911
+        time: 12, mark: 2.81, nominal_value: 84.3, fundRate: 0.000072, fundFee: 0.0060696
+        time: 13, mark: 2.82, nominal_value: 84.6, fundRate: 0.000097, fundFee: 0.0082062
+
+    size: 50
+        time: 0, mark: 2.77, nominal_value: 138.5, fundRate: -0.000008, fundFee: -0.001108
+        time: 1, mark: 2.73, nominal_value: 136.5, fundRate: -0.000004, fundFee: -0.000546
+        time: 2, mark: 2.74, nominal_value: 137.0, fundRate: 0.000012, fundFee: 0.001644
+        time: 3, mark: 2.76, nominal_value: 138.0, fundRate: -0.000003, fundFee: -0.000414
+        time: 4, mark: 2.76, nominal_value: 138.0, fundRate: -0.000007, fundFee: -0.000966
+        time: 5, mark: 2.77, nominal_value: 138.5, fundRate: 0.000003, fundFee: 0.0004155
+        time: 6, mark: 2.78, nominal_value: 139.0, fundRate: 0.000019, fundFee: 0.002641
+        time: 7, mark: 2.78, nominal_value: 139.0, fundRate: 0.000003, fundFee: 0.000417
+        time: 8, mark: 2.77, nominal_value: 138.5, fundRate: -0.000003, fundFee: -0.0004155
+        time: 9, mark: 2.77, nominal_value: 138.5, fundRate: 0, fundFee: 0.0
+        time: 10, mark: 2.84, nominal_value: 142.0, fundRate: 0.000013, fundFee: 0.001846
+        time: 11, mark: 2.81, nominal_value: 140.5, fundRate: 0.000077, fundFee: 0.0108185
+        time: 12, mark: 2.81, nominal_value: 140.5, fundRate: 0.000072, fundFee: 0.010116
+        time: 13, mark: 2.82, nominal_value: 141.0, fundRate: 0.000097, fundFee: 0.013677
+    """
+    d1 = datetime.strptime(f"{d1} +0000", '%Y-%m-%d %H:%M:%S %z')
+    d2 = datetime.strptime(f"{d2} +0000", '%Y-%m-%d %H:%M:%S %z')
+    funding_rate_history = {
+        'binance': funding_rate_history_octohourly,
+        'ftx': funding_rate_history_hourly,
+        'gateio': funding_rate_history_octohourly,
+    }[exchange][rate_start:rate_end]
+    api_mock = MagicMock()
+    api_mock.fetch_funding_rate_history = get_mock_coro(return_value=funding_rate_history)
+    api_mock.fetch_ohlcv = get_mock_coro(return_value=mark_ohlcv)
+    type(api_mock).has = PropertyMock(return_value={'fetchOHLCV': True})
+    type(api_mock).has = PropertyMock(return_value={'fetchFundingRateHistory': True})
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange)
+    mocker.patch('freqtrade.exchange.Exchange.timeframes', PropertyMock(
+        return_value=['1h', '4h', '8h']))
+    funding_fees = exchange._fetch_and_calculate_funding_fees(
+        pair='ADA/USDT', amount=amount, is_short=True, open_date=d1, close_date=d2)
+    assert pytest.approx(funding_fees) == expected_fees
+    # Fees for Longs are inverted
+    funding_fees = exchange._fetch_and_calculate_funding_fees(
+        pair='ADA/USDT', amount=amount, is_short=False, open_date=d1, close_date=d2)
+    assert pytest.approx(funding_fees) == -expected_fees
+
+
+@pytest.mark.parametrize('exchange,expected_fees', [
+    ('binance', -0.0009140999999999999),
+    ('gateio', -0.0009140999999999999),
+])
+def test__fetch_and_calculate_funding_fees_datetime_called(
+    mocker,
+    default_conf,
+    funding_rate_history_octohourly,
+    mark_ohlcv,
+    exchange,
+    time_machine,
+    expected_fees
+):
+    api_mock = MagicMock()
+    api_mock.fetch_ohlcv = get_mock_coro(return_value=mark_ohlcv)
+    api_mock.fetch_funding_rate_history = get_mock_coro(
+        return_value=funding_rate_history_octohourly)
+    type(api_mock).has = PropertyMock(return_value={'fetchOHLCV': True})
+    type(api_mock).has = PropertyMock(return_value={'fetchFundingRateHistory': True})
+    mocker.patch('freqtrade.exchange.Exchange.timeframes', PropertyMock(return_value=['4h', '8h']))
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange)
+    d1 = datetime.strptime("2021-09-01 00:00:00 +0000", '%Y-%m-%d %H:%M:%S %z')
+
+    time_machine.move_to("2021-09-01 08:00:00 +00:00")
+    funding_fees = exchange._fetch_and_calculate_funding_fees('ADA/USDT', 30.0, True, d1)
+    assert funding_fees == expected_fees
+    funding_fees = exchange._fetch_and_calculate_funding_fees('ADA/USDT', 30.0, False, d1)
+    assert funding_fees == 0 - expected_fees
+
+
+@pytest.mark.parametrize('pair,expected_size,trading_mode', [
+    ('XLTCUSDT', 1, 'spot'),
+    ('LTC/USD', 1, 'futures'),
+    ('XLTCUSDT', 0.01, 'futures'),
+    ('ETH/USDT:USDT', 10, 'futures')
+])
+def test__get_contract_size(mocker, default_conf, pair, expected_size, trading_mode):
+    api_mock = MagicMock()
+    default_conf['trading_mode'] = trading_mode
+    default_conf['margin_mode'] = 'isolated'
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    mocker.patch('freqtrade.exchange.Exchange.markets', {
+        'LTC/USD': {
+            'symbol': 'LTC/USD',
+            'contractSize': None,
+        },
+        'XLTCUSDT': {
+            'symbol': 'XLTCUSDT',
+            'contractSize': '0.01',
+        },
+        'ETH/USDT:USDT': {
+            'symbol': 'ETH/USDT:USDT',
+            'contractSize': '10',
+        }
+    })
+    size = exchange._get_contract_size(pair)
+    assert expected_size == size
+
+
+@pytest.mark.parametrize('pair,contract_size,trading_mode', [
+    ('XLTCUSDT', 1, 'spot'),
+    ('LTC/USD', 1, 'futures'),
+    ('ADA/USDT:USDT', 0.01, 'futures'),
+    ('LTC/ETH', 1, 'futures'),
+    ('ETH/USDT:USDT', 10, 'futures'),
+])
+def test__order_contracts_to_amount(
+    mocker,
+    default_conf,
+    markets,
+    pair,
+    contract_size,
+    trading_mode,
+):
+    api_mock = MagicMock()
+    default_conf['trading_mode'] = trading_mode
+    default_conf['margin_mode'] = 'isolated'
+    mocker.patch('freqtrade.exchange.Exchange.markets', markets)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+
+    orders = [
+        {
+            'id': '123456320',
+            'clientOrderId': '12345632018',
+            'timestamp': 1640124992000,
+            'datetime': 'Tue 21 Dec 2021 22:16:32 UTC',
+            'lastTradeTimestamp': 1640124911000,
+            'status': 'active',
+            'symbol': pair,
+            'type': 'limit',
+            'timeInForce': 'gtc',
+            'postOnly': None,
+            'side': 'buy',
+            'price': 2.0,
+            'stopPrice': None,
+            'average': None,
+            'amount': 30.0,
+            'cost': 60.0,
+            'filled': None,
+            'remaining': 30.0,
+            'fee': 0.06,
+            'fees': [{
+                'currency': 'USDT',
+                'cost': 0.06,
+            }],
+            'trades': None,
+            'info': {},
+        },
+        {
+            'id': '123456380',
+            'clientOrderId': '12345638203',
+            'timestamp': 1640124992000,
+            'datetime': 'Tue 21 Dec 2021 22:16:32 UTC',
+            'lastTradeTimestamp': 1640124911000,
+            'status': 'active',
+            'symbol': pair,
+            'type': 'limit',
+            'timeInForce': 'gtc',
+            'postOnly': None,
+            'side': 'sell',
+            'price': 2.2,
+            'stopPrice': None,
+            'average': None,
+            'amount': 40.0,
+            'cost': 80.0,
+            'filled': None,
+            'remaining': 40.0,
+            'fee': 0.08,
+            'fees': [{
+                'currency': 'USDT',
+                'cost': 0.08,
+            }],
+            'trades': None,
+            'info': {},
+        },
+        {
+            # Realistic stoploss order on gateio.
+            'id': '123456380',
+            'clientOrderId': '12345638203',
+            'timestamp': None,
+            'datetime': None,
+            'lastTradeTimestamp': None,
+            'status': None,
+            'symbol': None,
+            'type': None,
+            'timeInForce': None,
+            'postOnly': None,
+            'side': None,
+            'price': None,
+            'stopPrice': None,
+            'average': None,
+            'amount': None,
+            'cost': None,
+            'filled': None,
+            'remaining': None,
+            'fee': None,
+            'fees': [],
+            'trades': None,
+            'info': {},
+        },
+    ]
+
+    order1 = exchange._order_contracts_to_amount(orders[0])
+    order2 = exchange._order_contracts_to_amount(orders[1])
+    exchange._order_contracts_to_amount(orders[2])
+    assert order1['amount'] == 30.0 * contract_size
+    assert order2['amount'] == 40.0 * contract_size
+
+
+@pytest.mark.parametrize('pair,contract_size,trading_mode', [
+    ('XLTCUSDT', 1, 'spot'),
+    ('LTC/USD', 1, 'futures'),
+    ('ADA/USDT:USDT', 0.01, 'futures'),
+    ('LTC/ETH', 1, 'futures'),
+    ('ETH/USDT:USDT', 10, 'futures'),
+])
+def test__trades_contracts_to_amount(
+    mocker,
+    default_conf,
+    markets,
+    pair,
+    contract_size,
+    trading_mode,
+):
+    api_mock = MagicMock()
+    default_conf['trading_mode'] = trading_mode
+    default_conf['margin_mode'] = 'isolated'
+    mocker.patch('freqtrade.exchange.Exchange.markets', markets)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+
+    trades = [
+        {
+            'symbol': pair,
+            'amount': 30.0,
+        },
+        {
+            'symbol': pair,
+            'amount': 40.0,
+        }
+    ]
+
+    new_amount_trades = exchange._trades_contracts_to_amount(trades)
+    assert new_amount_trades[0]['amount'] == 30.0 * contract_size
+    assert new_amount_trades[1]['amount'] == 40.0 * contract_size
+
+
+@pytest.mark.parametrize('pair,param_amount,param_size', [
+    ('ADA/USDT:USDT', 40, 4000),
+    ('LTC/ETH', 30, 30),
+    ('LTC/USD', 30, 30),
+    ('ETH/USDT:USDT', 10, 1),
+])
+def test__amount_to_contracts(
+    mocker,
+    default_conf,
+    pair,
+    param_amount,
+    param_size
+):
+    api_mock = MagicMock()
+    default_conf['trading_mode'] = 'spot'
+    default_conf['margin_mode'] = 'isolated'
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    mocker.patch('freqtrade.exchange.Exchange.markets', {
+        'LTC/USD': {
+            'symbol': 'LTC/USD',
+            'contractSize': None,
+        },
+        'XLTCUSDT': {
+            'symbol': 'XLTCUSDT',
+            'contractSize': '0.01',
+        },
+        'LTC/ETH': {
+            'symbol': 'LTC/ETH',
+        },
+        'ETH/USDT:USDT': {
+            'symbol': 'ETH/USDT:USDT',
+            'contractSize': '10',
+        }
+    })
+    result_size = exchange._amount_to_contracts(pair, param_amount)
+    assert result_size == param_amount
+    result_amount = exchange._contracts_to_amount(pair, param_size)
+    assert result_amount == param_size
+
+    default_conf['trading_mode'] = 'futures'
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    result_size = exchange._amount_to_contracts(pair, param_amount)
+    assert result_size == param_size
+    result_amount = exchange._contracts_to_amount(pair, param_size)
+    assert result_amount == param_amount
+
+
+@pytest.mark.parametrize('exchange_name,open_rate,is_short,trading_mode,margin_mode', [
+    # Bittrex
+    ('bittrex', 2.0, False, 'spot', None),
+    ('bittrex', 2.0, False, 'spot', 'cross'),
+    ('bittrex', 2.0, True, 'spot', 'isolated'),
+    # Binance
+    ('binance', 2.0, False, 'spot', None),
+    ('binance', 2.0, False, 'spot', 'cross'),
+    ('binance', 2.0, True, 'spot', 'isolated'),
+])
+def test_liquidation_price_is_none(
+    mocker,
+    default_conf,
+    exchange_name,
+    open_rate,
+    is_short,
+    trading_mode,
+    margin_mode
+):
+    default_conf['trading_mode'] = trading_mode
+    default_conf['margin_mode'] = margin_mode
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    assert exchange.get_or_calculate_liquidation_price(
+        pair='DOGE/USDT',
+        open_rate=open_rate,
+        is_short=is_short,
+        position=71200.81144,
+        wallet_balance=-56354.57,
+        mm_ex_1=0.10,
+        upnl_ex_1=0.0
+    ) is None
+
+
+@pytest.mark.parametrize(
+    'exchange_name, is_short, trading_mode, margin_mode, wallet_balance, '
+    'mm_ex_1, upnl_ex_1, maintenance_amt, position, open_rate, '
+    'mm_ratio, expected',
+    [
+        ("binance", False, 'futures', 'isolated', 1535443.01, 0.0,
+         0.0, 135365.00, 3683.979, 1456.84, 0.10, 1114.78),
+        ("binance", False, 'futures', 'isolated', 1535443.01, 0.0,
+         0.0, 16300.000, 109.488, 32481.980, 0.025, 18778.73),
+        ("binance", False, 'futures', 'cross', 1535443.01, 71200.81144,
+         -56354.57, 135365.00, 3683.979, 1456.84, 0.10, 1153.26),
+        ("binance", False, 'futures', 'cross', 1535443.01, 356512.508,
+         -448192.89, 16300.000, 109.488, 32481.980, 0.025, 26316.89)
+    ])
+def test_liquidation_price(
+    mocker, default_conf, exchange_name, open_rate, is_short, trading_mode,
+    margin_mode, wallet_balance, mm_ex_1, upnl_ex_1, maintenance_amt, position, mm_ratio, expected
+):
+    default_conf['trading_mode'] = trading_mode
+    default_conf['margin_mode'] = margin_mode
+    default_conf['liquidation_buffer'] = 0.0
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    exchange.get_maintenance_ratio_and_amt = MagicMock(return_value=(mm_ratio, maintenance_amt))
+    assert isclose(round(exchange.get_or_calculate_liquidation_price(
+        pair='DOGE/USDT',
+        open_rate=open_rate,
+        is_short=is_short,
+        wallet_balance=wallet_balance,
+        mm_ex_1=mm_ex_1,
+        upnl_ex_1=upnl_ex_1,
+        position=position,
+    ), 2), expected)
+
+
+def test_get_max_pair_stake_amount(
+    mocker,
+    default_conf,
+):
+    api_mock = MagicMock()
+    default_conf['margin_mode'] = 'isolated'
+    default_conf['trading_mode'] = 'futures'
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    markets = {
+        'XRP/USDT:USDT': {
+            'limits': {
+                'amount': {
+                    'min': 0.001,
+                    'max': 10000
+                },
+                'cost': {
+                    'min': 5,
+                    'max': None
+                },
+            },
+            'contractSize': None,
+            'spot': False,
+        },
+        'LTC/USDT:USDT': {
+            'limits': {
+                'amount': {
+                    'min': 0.001,
+                    'max': None
+                },
+                'cost': {
+                    'min': 5,
+                    'max': None
+                },
+            },
+            'contractSize': 0.01,
+            'spot': False,
+        },
+        'ETH/USDT:USDT': {
+            'limits': {
+                'amount': {
+                    'min': 0.001,
+                    'max': 10000
+                },
+                'cost': {
+                    'min': 5,
+                    'max': 30000,
+                },
+            },
+            'contractSize': 0.01,
+            'spot': False,
+        },
+        'BTC/USDT': {
+            'limits': {
+                'amount': {
+                    'min': 0.001,
+                    'max': 10000
+                },
+                'cost': {
+                    'min': 5,
+                    'max': None
+                },
+            },
+            'contractSize': 0.01,
+            'spot': True,
+        },
+        'ADA/USDT': {
+            'limits': {
+                'amount': {
+                    'min': 0.001,
+                    'max': 10000
+                },
+                'cost': {
+                    'min': 5,
+                    'max': 500,
+                },
+            },
+            'contractSize': 0.01,
+            'spot': True,
+        },
+        'DOGE/USDT:USDT': {
+            'limits': {
+                'amount': {
+                    'min': 0.001,
+                    'max': 10000
+                },
+                'cost': {
+                    'min': 5,
+                    'max': 500
+                },
+            },
+            'contractSize': None,
+            'spot': False,
+        },
+        'LUNA/USDT:USDT': {
+            'limits': {
+                'amount': {
+                    'min': 0.001,
+                    'max': 10000
+                },
+                'cost': {
+                    'min': 5,
+                    'max': 500
+                },
+            },
+            'contractSize': 0.01,
+            'spot': False,
+        },
+    }
+
+    mocker.patch('freqtrade.exchange.Exchange.markets', markets)
+    assert exchange.get_max_pair_stake_amount('XRP/USDT:USDT', 2.0) == 20000
+    assert exchange.get_max_pair_stake_amount('XRP/USDT:USDT', 2.0, 5) == 4000
+    assert exchange.get_max_pair_stake_amount('LTC/USDT:USDT', 2.0) == float('inf')
+    assert exchange.get_max_pair_stake_amount('ETH/USDT:USDT', 2.0) == 200
+    assert exchange.get_max_pair_stake_amount('DOGE/USDT:USDT', 2.0) == 500
+    assert exchange.get_max_pair_stake_amount('LUNA/USDT:USDT', 2.0) == 5.0
+
+    default_conf['trading_mode'] = 'spot'
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    mocker.patch('freqtrade.exchange.Exchange.markets', markets)
+    assert exchange.get_max_pair_stake_amount('BTC/USDT', 2.0) == 20000
+    assert exchange.get_max_pair_stake_amount('ADA/USDT', 2.0) == 500
+
+
+@pytest.mark.parametrize('exchange_name', EXCHANGES)
+def test_load_leverage_tiers(mocker, default_conf, leverage_tiers, exchange_name):
+    api_mock = MagicMock()
+    api_mock.fetch_leverage_tiers = MagicMock()
+    type(api_mock).has = PropertyMock(return_value={'fetchLeverageTiers': True})
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.exchange.Exchange.validate_trading_mode_and_margin_mode')
+
+    api_mock.fetch_leverage_tiers = MagicMock(return_value={
+        'ADA/USDT:USDT': [
+            {
+                'tier': 1,
+                'notionalFloor': 0,
+                'notionalCap': 500,
+                'maintenanceMarginRate': 0.02,
+                'maxLeverage': 75,
+                'info': {
+                    'baseMaxLoan': '',
+                    'imr': '0.013',
+                    'instId': '',
+                    'maxLever': '75',
+                    'maxSz': '500',
+                    'minSz': '0',
+                    'mmr': '0.01',
+                    'optMgnFactor': '0',
+                    'quoteMaxLoan': '',
+                    'tier': '1',
+                    'uly': 'ADA-USDT'
+                }
+            },
+        ]
+    })
+
+    # SPOT
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    assert exchange.load_leverage_tiers() == {}
+
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+
+    if exchange_name != 'binance':
+        # FUTURES has.fetchLeverageTiers == False
+        type(api_mock).has = PropertyMock(return_value={'fetchLeverageTiers': False})
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        assert exchange.load_leverage_tiers() == {}
+
+    # FUTURES regular
+    type(api_mock).has = PropertyMock(return_value={'fetchLeverageTiers': True})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    assert exchange.load_leverage_tiers() == {
+        'ADA/USDT:USDT': [
+            {
+                'tier': 1,
+                'notionalFloor': 0,
+                'notionalCap': 500,
+                'maintenanceMarginRate': 0.02,
+                'maxLeverage': 75,
+                'info': {
+                    'baseMaxLoan': '',
+                    'imr': '0.013',
+                    'instId': '',
+                    'maxLever': '75',
+                    'maxSz': '500',
+                    'minSz': '0',
+                    'mmr': '0.01',
+                    'optMgnFactor': '0',
+                    'quoteMaxLoan': '',
+                    'tier': '1',
+                    'uly': 'ADA-USDT'
+                }
+            },
+        ]
+    }
+
+    ccxt_exceptionhandlers(
+        mocker,
+        default_conf,
+        api_mock,
+        exchange_name,
+        "load_leverage_tiers",
+        "fetch_leverage_tiers",
+    )
+
+
+def test_parse_leverage_tier(mocker, default_conf):
+    exchange = get_patched_exchange(mocker, default_conf)
+
+    tier = {
+        "tier": 1,
+        "notionalFloor": 0,
+        "notionalCap": 100000,
+        "maintenanceMarginRate": 0.025,
+        "maxLeverage": 20,
+        "info": {
+            "bracket": "1",
+            "initialLeverage": "20",
+            "notionalCap": "100000",
+            "notionalFloor": "0",
+            "maintMarginRatio": "0.025",
+            "cum": "0.0"
+        }
+    }
+
+    assert exchange.parse_leverage_tier(tier) == {
+        "min": 0,
+        "max": 100000,
+        "mmr": 0.025,
+        "lev": 20,
+        "maintAmt": 0.0,
+    }
+
+    tier2 = {
+        'tier': 1,
+        'notionalFloor': 0,
+        'notionalCap': 2000,
+        'maintenanceMarginRate': 0.01,
+        'maxLeverage': 75,
+        'info': {
+            'baseMaxLoan': '',
+            'imr': '0.013',
+            'instId': '',
+            'maxLever': '75',
+            'maxSz': '2000',
+            'minSz': '0',
+            'mmr': '0.01',
+            'optMgnFactor': '0',
+            'quoteMaxLoan': '',
+            'tier': '1',
+            'uly': 'SHIB-USDT'
+        }
+    }
+
+    assert exchange.parse_leverage_tier(tier2) == {
+        'min': 0,
+        'max': 2000,
+        'mmr': 0.01,
+        'lev': 75,
+        "maintAmt": None,
+    }
+
+
+def test_get_maintenance_ratio_and_amt_exceptions(mocker, default_conf, leverage_tiers):
+    api_mock = MagicMock()
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+
+    exchange._leverage_tiers = leverage_tiers
+    with pytest.raises(
+        OperationalException,
+        match='nominal value can not be lower than 0',
+    ):
+        exchange.get_maintenance_ratio_and_amt('1000SHIB/USDT', -1)
+
+    exchange._leverage_tiers = {}
+
+    with pytest.raises(
+        InvalidOrderException,
+        match="Maintenance margin rate for 1000SHIB/USDT is unavailable for",
+    ):
+        exchange.get_maintenance_ratio_and_amt('1000SHIB/USDT', 10000)
+
+
+@pytest.mark.parametrize('pair,value,mmr,maintAmt', [
+    ('ADA/BUSD', 500, 0.025, 0.0),
+    ('ADA/BUSD', 20000000, 0.5, 1527500.0),
+    ('ZEC/USDT', 500, 0.01, 0.0),
+    ('ZEC/USDT', 20000000, 0.5, 654500.0),
+])
+def test_get_maintenance_ratio_and_amt(
+    mocker,
+    default_conf,
+    leverage_tiers,
+    pair,
+    value,
+    mmr,
+    maintAmt
+):
+    api_mock = MagicMock()
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    exchange._leverage_tiers = leverage_tiers
+    exchange.get_maintenance_ratio_and_amt(pair, value) == (mmr, maintAmt)
+
+
+def test_get_max_leverage_futures(default_conf, mocker, leverage_tiers):
+
+    # Test Spot
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+    assert exchange.get_max_leverage("BNB/USDT", 100.0) == 1.0
+
+    # Test Futures
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+
+    exchange._leverage_tiers = leverage_tiers
+
+    assert exchange.get_max_leverage("BNB/BUSD", 1.0) == 20.0
+    assert exchange.get_max_leverage("BNB/USDT", 100.0) == 75.0
+    assert exchange.get_max_leverage("BTC/USDT", 170.30) == 125.0
+    assert isclose(exchange.get_max_leverage("BNB/BUSD", 99999.9), 5.000005)
+    assert isclose(exchange.get_max_leverage("BNB/USDT", 1500), 33.333333333333333)
+    assert exchange.get_max_leverage("BTC/USDT", 300000000) == 2.0
+    assert exchange.get_max_leverage("BTC/USDT", 600000000) == 1.0  # Last tier
+
+    assert exchange.get_max_leverage("SPONGE/USDT", 200) == 1.0    # Pair not in leverage_tiers
+    assert exchange.get_max_leverage("BTC/USDT", 0.0) == 125.0  # No stake amount
+    with pytest.raises(
+        InvalidOrderException,
+        match=r'Amount 1000000000.01 too high for BTC/USDT'
+    ):
+        exchange.get_max_leverage("BTC/USDT", 1000000000.01)
+
+
+@pytest.mark.parametrize("exchange_name", ['bittrex', 'binance', 'kraken', 'ftx', 'gateio', 'okx'])
+def test__get_params(mocker, default_conf, exchange_name):
+    api_mock = MagicMock()
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    exchange._params = {'test': True}
+
+    params1 = {'test': True}
+    params2 = {
+        'test': True,
+        'timeInForce': 'ioc',
+        'reduceOnly': True,
+    }
+
+    if exchange_name == 'kraken':
+        params2['leverage'] = 3.0
+
+    if exchange_name == 'okx':
+        params2['tdMode'] = 'isolated'
+
+    assert exchange._get_params(
+        ordertype='market',
+        reduceOnly=False,
+        time_in_force='gtc',
+        leverage=1.0,
+    ) == params1
+
+    assert exchange._get_params(
+        ordertype='market',
+        reduceOnly=False,
+        time_in_force='ioc',
+        leverage=1.0,
+    ) == params1
+
+    assert exchange._get_params(
+        ordertype='limit',
+        reduceOnly=False,
+        time_in_force='gtc',
+        leverage=1.0,
+    ) == params1
+
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    exchange._params = {'test': True}
+
+    assert exchange._get_params(
+        ordertype='limit',
+        reduceOnly=True,
+        time_in_force='ioc',
+        leverage=3.0,
+    ) == params2
+
+
+@pytest.mark.parametrize('liquidation_buffer', [0.0, 0.05])
+@pytest.mark.parametrize(
+    "is_short,trading_mode,exchange_name,margin_mode,leverage,open_rate,amount,expected_liq", [
+        (False, 'spot', 'binance', '', 5.0,  10.0, 1.0, None),
+        (True, 'spot', 'binance', '', 5.0,  10.0, 1.0, None),
+        (False, 'spot', 'gateio', '', 5.0,  10.0, 1.0, None),
+        (True, 'spot', 'gateio', '', 5.0,  10.0, 1.0, None),
+        (False, 'spot', 'okx', '', 5.0,  10.0, 1.0, None),
+        (True, 'spot', 'okx', '', 5.0,  10.0, 1.0, None),
+        # Binance, short
+        (True, 'futures', 'binance', 'isolated', 5.0, 10.0, 1.0, 11.89108910891089),
+        (True, 'futures', 'binance', 'isolated', 3.0, 10.0, 1.0, 13.211221122079207),
+        (True, 'futures', 'binance', 'isolated', 5.0, 8.0, 1.0, 9.514851485148514),
+        (True, 'futures', 'binance', 'isolated', 5.0, 10.0, 0.6, 12.557755775577558),
+        # Binance, long
+        (False, 'futures', 'binance', 'isolated', 5, 10, 1.0, 8.070707070707071),
+        (False, 'futures', 'binance', 'isolated', 5, 8, 1.0, 6.454545454545454),
+        (False, 'futures', 'binance', 'isolated', 3, 10, 1.0, 6.717171717171718),
+        (False, 'futures', 'binance', 'isolated', 5, 10, 0.6, 7.39057239057239),
+        # Gateio/okx, short
+        (True, 'futures', 'gateio', 'isolated', 5, 10, 1.0, 11.87413417771621),
+        (True, 'futures', 'gateio', 'isolated', 5, 10, 2.0, 11.87413417771621),
+        (True, 'futures', 'gateio', 'isolated', 3, 10, 1.0, 13.476180850346978),
+        (True, 'futures', 'gateio', 'isolated', 5, 8, 1.0, 9.499307342172967),
+        # Gateio/okx, long
+        (False, 'futures', 'gateio', 'isolated', 5.0, 10.0, 1.0, 8.085708510208207),
+        (False, 'futures', 'gateio', 'isolated', 3.0, 10.0, 1.0, 6.738090425173506),
+        # (True, 'futures', 'okx', 'isolated', 11.87413417771621),
+        # (False, 'futures', 'okx', 'isolated', 8.085708510208207),
+    ]
+)
+def test_get_liquidation_price(
+    mocker,
+    default_conf_usdt,
+    is_short,
+    trading_mode,
+    exchange_name,
+    margin_mode,
+    leverage,
+    open_rate,
+    amount,
+    expected_liq,
+    liquidation_buffer,
+):
+    """
+    position = 0.2 * 5
+    wb: wallet balance (stake_amount if isolated)
+    cum_b: maintenance amount
+    side_1: -1 if is_short else 1
+    ep1: entry price
+    mmr_b: maintenance margin ratio
+
+    Binance, Short
+    leverage = 5, open_rate = 10, amount = 1.0
+        ((wb + cum_b) - (side_1 * position * ep1)) / ((position * mmr_b) - (side_1 * position))
+        ((2 + 0.01) - ((-1) * 1 * 10)) / ((1 * 0.01) - ((-1) * 1)) = 11.89108910891089
+    leverage = 3, open_rate = 10, amount = 1.0
+        ((3.3333333333 + 0.01) - ((-1) * 1.0 * 10)) / ((1.0 * 0.01) - ((-1) * 1.0)) = 13.2112211220
+    leverage = 5, open_rate = 8, amount = 1.0
+        ((1.6 + 0.01) - ((-1) * 1 * 8)) / ((1 * 0.01) - ((-1) * 1)) = 9.514851485148514
+    leverage = 5, open_rate = 10, amount = 0.6
+        ((1.6 + 0.01) - ((-1) * 0.6 * 10)) / ((0.6 * 0.01) - ((-1) * 0.6)) = 12.557755775577558
+
+    Binance, Long
+    leverage = 5, open_rate = 10, amount = 1.0
+        ((wb + cum_b) - (side_1 * position * ep1)) / ((position * mmr_b) - (side_1 * position))
+        ((2 + 0.01) - (1 * 1 * 10)) / ((1 * 0.01) - (1 * 1)) = 8.070707070707071
+    leverage = 5, open_rate = 8, amount = 1.0
+        ((1.6 + 0.01) - (1 * 1 * 8)) / ((1 * 0.01) - (1 * 1)) = 6.454545454545454
+    leverage = 3, open_rate = 10, amount = 1.0
+        ((2 + 0.01) - (1 * 0.6 * 10)) / ((0.6 * 0.01) - (1 * 0.6)) = 6.717171717171718
+    leverage = 5, open_rate = 10, amount = 0.6
+        ((1.6 + 0.01) - (1 * 0.6 * 10)) / ((0.6 * 0.01) - (1 * 0.6)) = 7.39057239057239
+
+    Gateio/Okx, Short
+    leverage = 5, open_rate = 10, amount = 1.0
+        (open_rate + (wallet_balance / position)) / (1 + (mm_ratio + taker_fee_rate))
+        (10 + (2 / 1.0)) / (1 + (0.01 + 0.0006)) = 11.87413417771621
+    leverage = 5, open_rate = 10, amount = 2.0
+        (10 + (4 / 2.0)) / (1 + (0.01 + 0.0006)) = 11.87413417771621
+    leverage = 3, open_rate = 10, amount = 1.0
+        (10 + (3.3333333333333 / 1.0)) / (1 - (0.01 + 0.0006)) = 13.476180850346978
+    leverage = 5, open_rate = 8, amount = 1.0
+        (8 + (1.6 / 1.0)) / (1 + (0.01 + 0.0006)) = 9.499307342172967
+
+    Gateio/Okx, Long
+    leverage = 5, open_rate = 10, amount = 1.0
+        (open_rate - (wallet_balance / position)) / (1 - (mm_ratio + taker_fee_rate))
+        (10 - (2 / 1)) / (1 - (0.01 + 0.0006)) = 8.085708510208207
+    leverage = 5, open_rate = 10, amount = 2.0
+        (10 - (4 / 2.0)) / (1 + (0.01 + 0.0006)) = 7.916089451810806
+    leverage = 3, open_rate = 10, amount = 1.0
+        (10 - (3.333333333333333333 / 1.0)) / (1 - (0.01 + 0.0006)) = 6.738090425173506
+    leverage = 5, open_rate = 8, amount = 1.0
+        (8 - (1.6 / 1.0)) / (1 + (0.01 + 0.0006)) = 6.332871561448645
+    """
+    default_conf_usdt['liquidation_buffer'] = liquidation_buffer
+    default_conf_usdt['trading_mode'] = trading_mode
+    default_conf_usdt['exchange']['name'] = exchange_name
+    default_conf_usdt['margin_mode'] = margin_mode
+    mocker.patch('freqtrade.exchange.Gateio.validate_ordertypes')
+    exchange = get_patched_exchange(mocker, default_conf_usdt)
+
+    exchange.get_maintenance_ratio_and_amt = MagicMock(return_value=(0.01, 0.01))
+    exchange.name = exchange_name
+    # default_conf_usdt.update({
+    #     "dry_run": False,
+    # })
+    liq = exchange.get_liquidation_price(
+        pair='ETH/USDT:USDT',
+        open_rate=open_rate,
+        amount=amount,
+        leverage=leverage,
+        is_short=is_short,
+    )
+    if expected_liq is None:
+        assert liq is None
+    else:
+        buffer_amount = liquidation_buffer * abs(open_rate - expected_liq)
+        expected_liq = expected_liq - buffer_amount if is_short else expected_liq + buffer_amount
+        isclose(expected_liq, liq)
+
+
+@pytest.mark.parametrize('contract_size,order_amount', [
+    (10, 10),
+    (0.01, 10000),
+])
+def test_stoploss_contract_size(mocker, default_conf, contract_size, order_amount):
+    api_mock = MagicMock()
+    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
+
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        },
+        'amount': order_amount,
+        'cost': order_amount,
+        'filled': order_amount,
+        'remaining': order_amount,
+        'symbol': 'ETH/BTC',
+    })
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    exchange._get_contract_size = MagicMock(return_value=contract_size)
+
+    api_mock.create_order.reset_mock()
+    order = exchange.stoploss(
+        pair='ETH/BTC',
+        amount=100,
+        stop_price=220,
+        order_types={},
+        side='buy',
+        leverage=1.0
+    )
+
+    assert api_mock.create_order.call_args_list[0][1]['amount'] == order_amount
+    assert order['amount'] == 100
+    assert order['cost'] == 100
+    assert order['filled'] == 100
+    assert order['remaining'] == 100
diff --git a/tests/exchange/test_ftx.py b/tests/exchange/test_ftx.py
index 3794bb79c..0f16d4433 100644
--- a/tests/exchange/test_ftx.py
+++ b/tests/exchange/test_ftx.py
@@ -14,7 +14,11 @@ from .test_exchange import ccxt_exceptionhandlers
 STOPLOSS_ORDERTYPE = 'stop'
 
 
-def test_stoploss_order_ftx(default_conf, mocker):
+@pytest.mark.parametrize('order_price,exchangelimitratio,side', [
+    (217.8, 1.05, "sell"),
+    (222.2, 0.95, "buy"),
+])
+def test_stoploss_order_ftx(default_conf, mocker, order_price, exchangelimitratio, side):
     api_mock = MagicMock()
     order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
 
@@ -32,12 +36,18 @@ def test_stoploss_order_ftx(default_conf, mocker):
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
 
     # stoploss_on_exchange_limit_ratio is irrelevant for ftx market orders
-    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
-                              order_types={'stoploss_on_exchange_limit_ratio': 1.05})
+    order = exchange.stoploss(
+        pair='ETH/BTC',
+        amount=1,
+        stop_price=190,
+        side=side,
+        order_types={'stoploss_on_exchange_limit_ratio': exchangelimitratio},
+        leverage=1.0
+    )
 
     assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
     assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
-    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['side'] == side
     assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
     assert 'orderPrice' not in api_mock.create_order.call_args_list[0][1]['params']
     assert 'stopPrice' in api_mock.create_order.call_args_list[0][1]['params']
@@ -47,51 +57,79 @@ def test_stoploss_order_ftx(default_conf, mocker):
 
     api_mock.create_order.reset_mock()
 
-    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+    order = exchange.stoploss(
+        pair='ETH/BTC',
+        amount=1,
+        stop_price=220,
+        order_types={},
+        side=side,
+        leverage=1.0
+    )
 
     assert 'id' in order
     assert 'info' in order
     assert order['id'] == order_id
     assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
     assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
-    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['side'] == side
     assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
     assert 'orderPrice' not in api_mock.create_order.call_args_list[0][1]['params']
     assert api_mock.create_order.call_args_list[0][1]['params']['stopPrice'] == 220
 
     api_mock.create_order.reset_mock()
-    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
-                              order_types={'stoploss': 'limit'})
+    order = exchange.stoploss(
+        pair='ETH/BTC',
+        amount=1,
+        stop_price=220,
+        order_types={'stoploss': 'limit'}, side=side,
+        leverage=1.0
+    )
 
     assert 'id' in order
     assert 'info' in order
     assert order['id'] == order_id
     assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
     assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
-    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['side'] == side
     assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
     assert 'orderPrice' in api_mock.create_order.call_args_list[0][1]['params']
-    assert api_mock.create_order.call_args_list[0][1]['params']['orderPrice'] == 217.8
+    assert api_mock.create_order.call_args_list[0][1]['params']['orderPrice'] == order_price
     assert api_mock.create_order.call_args_list[0][1]['params']['stopPrice'] == 220
 
     # test exception handling
     with pytest.raises(DependencyException):
         api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
-        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+        exchange.stoploss(
+            pair='ETH/BTC',
+            amount=1,
+            stop_price=220,
+            order_types={},
+            side=side,
+            leverage=1.0
+        )
 
     with pytest.raises(InvalidOrderException):
         api_mock.create_order = MagicMock(
             side_effect=ccxt.InvalidOrder("ftx Order would trigger immediately."))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
-        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+        exchange.stoploss(
+            pair='ETH/BTC',
+            amount=1,
+            stop_price=220,
+            order_types={},
+            side=side,
+            leverage=1.0
+        )
 
     ccxt_exceptionhandlers(mocker, default_conf, api_mock, "ftx",
                            "stoploss", "create_order", retries=1,
-                           pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+                           pair='ETH/BTC', amount=1, stop_price=220, order_types={},
+                           side=side, leverage=1.0)
 
 
-def test_stoploss_order_dry_run_ftx(default_conf, mocker):
+@pytest.mark.parametrize('side', [("sell"), ("buy")])
+def test_stoploss_order_dry_run_ftx(default_conf, mocker, side):
     api_mock = MagicMock()
     default_conf['dry_run'] = True
     mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
@@ -101,7 +139,14 @@ def test_stoploss_order_dry_run_ftx(default_conf, mocker):
 
     api_mock.create_order.reset_mock()
 
-    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+    order = exchange.stoploss(
+        pair='ETH/BTC',
+        amount=1,
+        stop_price=220,
+        order_types={},
+        side=side,
+        leverage=1.0
+    )
 
     assert 'id' in order
     assert 'info' in order
@@ -112,20 +157,24 @@ def test_stoploss_order_dry_run_ftx(default_conf, mocker):
     assert order['amount'] == 1
 
 
-def test_stoploss_adjust_ftx(mocker, default_conf):
+@pytest.mark.parametrize('sl1,sl2,sl3,side', [
+    (1501, 1499, 1501, "sell"),
+    (1499, 1501, 1499, "buy")
+])
+def test_stoploss_adjust_ftx(mocker, default_conf, sl1, sl2, sl3, side):
     exchange = get_patched_exchange(mocker, default_conf, id='ftx')
     order = {
         'type': STOPLOSS_ORDERTYPE,
         'price': 1500,
     }
-    assert exchange.stoploss_adjust(1501, order)
-    assert not exchange.stoploss_adjust(1499, order)
+    assert exchange.stoploss_adjust(sl1, order, side=side)
+    assert not exchange.stoploss_adjust(sl2, order, side=side)
     # Test with invalid order case ...
     order['type'] = 'stop_loss_limit'
-    assert not exchange.stoploss_adjust(1501, order)
+    assert not exchange.stoploss_adjust(sl3, order, side=side)
 
 
-def test_fetch_stoploss_order(default_conf, mocker, limit_sell_order):
+def test_fetch_stoploss_order_ftx(default_conf, mocker, limit_sell_order, limit_buy_order):
     default_conf['dry_run'] = True
     order = MagicMock()
     order.myid = 123
@@ -147,9 +196,15 @@ def test_fetch_stoploss_order(default_conf, mocker, limit_sell_order):
     with pytest.raises(InvalidOrderException, match=r"Could not get stoploss order for id X"):
         exchange.fetch_stoploss_order('X', 'TKN/BTC')['status']
 
-    api_mock.fetch_orders = MagicMock(return_value=[{'id': 'X', 'status': 'closed'}])
+    # stoploss Limit order
+    api_mock.fetch_orders = MagicMock(return_value=[
+        {'id': 'X', 'status': 'closed',
+         'info': {
+             'orderId': 'mocked_limit_sell',
+         }}])
     api_mock.fetch_order = MagicMock(return_value=limit_sell_order)
 
+    # No orderId field - no call to fetch_order
     resp = exchange.fetch_stoploss_order('X', 'TKN/BTC')
     assert resp
     assert api_mock.fetch_order.call_count == 1
@@ -158,6 +213,17 @@ def test_fetch_stoploss_order(default_conf, mocker, limit_sell_order):
     assert resp['type'] == 'stop'
     assert resp['status_stop'] == 'triggered'
 
+    # Stoploss market order
+    # Contains no new Order, but "average" instead
+    order = {'id': 'X', 'status': 'closed', 'info': {'orderId': None}, 'average': 0.254}
+    api_mock.fetch_orders = MagicMock(return_value=[order])
+    api_mock.fetch_order.reset_mock()
+    resp = exchange.fetch_stoploss_order('X', 'TKN/BTC')
+    assert resp
+    # fetch_order not called (no regular order ID)
+    assert api_mock.fetch_order.call_count == 0
+    assert order == order
+
     with pytest.raises(InvalidOrderException):
         api_mock.fetch_orders = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, id='ftx')
diff --git a/tests/exchange/test_gateio.py b/tests/exchange/test_gateio.py
new file mode 100644
index 000000000..ad30a7d86
--- /dev/null
+++ b/tests/exchange/test_gateio.py
@@ -0,0 +1,118 @@
+from datetime import datetime, timezone
+from unittest.mock import MagicMock
+
+import pytest
+
+from freqtrade.enums import MarginMode, TradingMode
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import Gateio
+from freqtrade.resolvers.exchange_resolver import ExchangeResolver
+from tests.conftest import get_patched_exchange
+
+
+def test_validate_order_types_gateio(default_conf, mocker):
+    default_conf['exchange']['name'] = 'gateio'
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt')
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', return_value={})
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
+    mocker.patch('freqtrade.exchange.Exchange.name', 'Bittrex')
+    exch = ExchangeResolver.load_exchange('gateio', default_conf, True)
+    assert isinstance(exch, Gateio)
+
+    default_conf['order_types'] = {
+        'entry': 'market',
+        'exit': 'limit',
+        'stoploss': 'market',
+        'stoploss_on_exchange': False
+    }
+
+    with pytest.raises(OperationalException,
+                       match=r'Exchange .* does not support market orders.'):
+        ExchangeResolver.load_exchange('gateio', default_conf, True)
+
+
+def test_fetch_stoploss_order_gateio(default_conf, mocker):
+    exchange = get_patched_exchange(mocker, default_conf, id='gateio')
+
+    fetch_order_mock = MagicMock()
+    exchange.fetch_order = fetch_order_mock
+
+    exchange.fetch_stoploss_order('1234', 'ETH/BTC')
+    assert fetch_order_mock.call_count == 1
+    assert fetch_order_mock.call_args_list[0][1]['order_id'] == '1234'
+    assert fetch_order_mock.call_args_list[0][1]['pair'] == 'ETH/BTC'
+    assert fetch_order_mock.call_args_list[0][1]['params'] == {'stop': True}
+
+
+def test_cancel_stoploss_order_gateio(default_conf, mocker):
+    exchange = get_patched_exchange(mocker, default_conf, id='gateio')
+
+    cancel_order_mock = MagicMock()
+    exchange.cancel_order = cancel_order_mock
+
+    exchange.cancel_stoploss_order('1234', 'ETH/BTC')
+    assert cancel_order_mock.call_count == 1
+    assert cancel_order_mock.call_args_list[0][1]['order_id'] == '1234'
+    assert cancel_order_mock.call_args_list[0][1]['pair'] == 'ETH/BTC'
+    assert cancel_order_mock.call_args_list[0][1]['params'] == {'stop': True}
+
+
+@pytest.mark.parametrize('sl1,sl2,sl3,side', [
+    (1501, 1499, 1501, "sell"),
+    (1499, 1501, 1499, "buy")
+])
+def test_stoploss_adjust_gateio(mocker, default_conf, sl1, sl2, sl3, side):
+    exchange = get_patched_exchange(mocker, default_conf, id='gateio')
+    order = {
+        'price': 1500,
+        'stopPrice': 1500,
+    }
+    assert exchange.stoploss_adjust(sl1, order, side)
+    assert not exchange.stoploss_adjust(sl2, order, side)
+
+
+@pytest.mark.parametrize('takerormaker,rate,cost', [
+    ('taker', 0.0005, 0.0001554325),
+    ('maker', 0.0, 0.0),
+])
+def test_fetch_my_trades_gateio(mocker, default_conf, takerormaker, rate, cost):
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    tick = {'ETH/USDT:USDT': {
+        'info': {'user_id': '',
+                 'taker_fee': '0.0018',
+                 'maker_fee': '0.0018',
+                 'gt_discount': False,
+                 'gt_taker_fee': '0',
+                 'gt_maker_fee': '0',
+                 'loan_fee': '0.18',
+                 'point_type': '1',
+                 'futures_taker_fee': '0.0005',
+                 'futures_maker_fee': '0'},
+            'symbol': 'ETH/USDT:USDT',
+            'maker': 0.0,
+            'taker': 0.0005}
+            }
+    default_conf['dry_run'] = False
+    default_conf['trading_mode'] = TradingMode.FUTURES
+    default_conf['margin_mode'] = MarginMode.ISOLATED
+
+    api_mock = MagicMock()
+    api_mock.fetch_my_trades = MagicMock(return_value=[{
+        'fee': {'cost': None},
+        'price': 3108.65,
+        'cost': 0.310865,
+        'order': '22255',
+        'takerOrMaker': takerormaker,
+        'amount': 1,  # 1 contract
+    }])
+    exchange = get_patched_exchange(mocker, default_conf, api_mock=api_mock, id='gateio')
+    exchange._trading_fees = tick
+    trades = exchange.get_trades_for_order('22255', 'ETH/USDT:USDT', datetime.now(timezone.utc))
+    trade = trades[0]
+    assert trade['fee']
+    assert trade['fee']['rate'] == rate
+    assert trade['fee']['currency'] == 'USDT'
+    assert trade['fee']['cost'] == cost
diff --git a/tests/exchange/test_huobi.py b/tests/exchange/test_huobi.py
new file mode 100644
index 000000000..fc7c7cefb
--- /dev/null
+++ b/tests/exchange/test_huobi.py
@@ -0,0 +1,117 @@
+from random import randint
+from unittest.mock import MagicMock
+
+import ccxt
+import pytest
+
+from freqtrade.exceptions import DependencyException, InvalidOrderException, OperationalException
+from tests.conftest import get_patched_exchange
+from tests.exchange.test_exchange import ccxt_exceptionhandlers
+
+
+@pytest.mark.parametrize('limitratio,expected,side', [
+    (None, 220 * 0.99, "sell"),
+    (0.99, 220 * 0.99, "sell"),
+    (0.98, 220 * 0.98, "sell"),
+])
+def test_stoploss_order_huobi(default_conf, mocker, limitratio, expected, side):
+    api_mock = MagicMock()
+    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
+    order_type = 'stop-limit'
+
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'huobi')
+
+    with pytest.raises(OperationalException):
+        order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
+                                  order_types={'stoploss_on_exchange_limit_ratio': 1.05},
+                                  side=side,
+                                  leverage=1.0)
+
+    api_mock.create_order.reset_mock()
+    order_types = {} if limitratio is None else {'stoploss_on_exchange_limit_ratio': limitratio}
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types=order_types,
+                              side=side, leverage=1.0)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
+    assert api_mock.create_order.call_args_list[0][1]['type'] == order_type
+    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
+    # Price should be 1% below stopprice
+    assert api_mock.create_order.call_args_list[0][1]['price'] == expected
+    assert api_mock.create_order.call_args_list[0][1]['params'] == {"stopPrice": 220,
+                                                                    "operator": "lte",
+                                                                    }
+
+    # test exception handling
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'huobi')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
+                          order_types={},  side=side, leverage=1.0)
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.create_order = MagicMock(
+            side_effect=ccxt.InvalidOrder("binance Order would trigger immediately."))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
+                          order_types={},  side=side, leverage=1.0)
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, "huobi",
+                           "stoploss", "create_order", retries=1,
+                           pair='ETH/BTC', amount=1, stop_price=220, order_types={},
+                           side=side, leverage=1.0)
+
+
+def test_stoploss_order_dry_run_huobi(default_conf, mocker):
+    api_mock = MagicMock()
+    order_type = 'stop-limit'
+    default_conf['dry_run'] = True
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'huobi')
+
+    with pytest.raises(OperationalException):
+        order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
+                                  order_types={'stoploss_on_exchange_limit_ratio': 1.05},
+                                  side='sell', leverage=1.0)
+
+    api_mock.create_order.reset_mock()
+
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
+                              order_types={},  side='sell', leverage=1.0)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert 'type' in order
+
+    assert order['type'] == order_type
+    assert order['price'] == 220
+    assert order['amount'] == 1
+
+
+def test_stoploss_adjust_huobi(mocker, default_conf):
+    exchange = get_patched_exchange(mocker, default_conf, id='huobi')
+    order = {
+        'type': 'stop',
+        'price': 1500,
+        'stopPrice': '1500',
+    }
+    assert exchange.stoploss_adjust(1501, order, 'sell')
+    assert not exchange.stoploss_adjust(1499, order, 'sell')
+    # Test with invalid order case
+    order['type'] = 'stop_loss'
+    assert not exchange.stoploss_adjust(1501, order, 'sell')
diff --git a/tests/exchange/test_kraken.py b/tests/exchange/test_kraken.py
index eb79dfc10..02df60990 100644
--- a/tests/exchange/test_kraken.py
+++ b/tests/exchange/test_kraken.py
@@ -21,6 +21,7 @@ def test_buy_kraken_trading_agreement(default_conf, mocker):
     api_mock.options = {}
     api_mock.create_order = MagicMock(return_value={
         'id': order_id,
+        'symbol': 'ETH/BTC',
         'info': {
             'foo': 'bar'
         }
@@ -31,8 +32,15 @@ def test_buy_kraken_trading_agreement(default_conf, mocker):
     mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
 
-    order = exchange.create_order(pair='ETH/BTC', ordertype=order_type, side="buy",
-                                  amount=1, rate=200, time_in_force=time_in_force)
+    order = exchange.create_order(
+        pair='ETH/BTC',
+        ordertype=order_type,
+        side="buy",
+        amount=1,
+        rate=200,
+        leverage=1.0,
+        time_in_force=time_in_force
+    )
 
     assert 'id' in order
     assert 'info' in order
@@ -53,6 +61,7 @@ def test_sell_kraken_trading_agreement(default_conf, mocker):
     api_mock.options = {}
     api_mock.create_order = MagicMock(return_value={
         'id': order_id,
+        'symbol': 'ETH/BTC',
         'info': {
             'foo': 'bar'
         }
@@ -64,7 +73,7 @@ def test_sell_kraken_trading_agreement(default_conf, mocker):
     exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
 
     order = exchange.create_order(pair='ETH/BTC', ordertype=order_type,
-                                  side="sell", amount=1, rate=200)
+                                  side="sell", amount=1, rate=200, leverage=1.0)
 
     assert 'id' in order
     assert 'info' in order
@@ -166,7 +175,11 @@ def test_get_balances_prod(default_conf, mocker):
 
 
 @pytest.mark.parametrize('ordertype', ['market', 'limit'])
-def test_stoploss_order_kraken(default_conf, mocker, ordertype):
+@pytest.mark.parametrize('side,adjustedprice', [
+    ("sell", 217.8),
+    ("buy", 222.2),
+])
+def test_stoploss_order_kraken(default_conf, mocker, ordertype, side, adjustedprice):
     api_mock = MagicMock()
     order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
 
@@ -183,10 +196,17 @@ def test_stoploss_order_kraken(default_conf, mocker, ordertype):
 
     exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kraken')
 
-    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
-                              order_types={'stoploss': ordertype,
-                                           'stoploss_on_exchange_limit_ratio': 0.99
-                                           })
+    order = exchange.stoploss(
+        pair='ETH/BTC',
+        amount=1,
+        stop_price=220,
+        side=side,
+        order_types={
+            'stoploss': ordertype,
+            'stoploss_on_exchange_limit_ratio': 0.99
+        },
+        leverage=1.0
+    )
 
     assert 'id' in order
     assert 'info' in order
@@ -195,12 +215,14 @@ def test_stoploss_order_kraken(default_conf, mocker, ordertype):
     if ordertype == 'limit':
         assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_LIMIT_ORDERTYPE
         assert api_mock.create_order.call_args_list[0][1]['params'] == {
-            'trading_agreement': 'agree', 'price2': 217.8}
+            'trading_agreement': 'agree',
+            'price2': adjustedprice
+        }
     else:
         assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
         assert api_mock.create_order.call_args_list[0][1]['params'] == {
             'trading_agreement': 'agree'}
-    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['side'] == side
     assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
     assert api_mock.create_order.call_args_list[0][1]['price'] == 220
 
@@ -208,20 +230,36 @@ def test_stoploss_order_kraken(default_conf, mocker, ordertype):
     with pytest.raises(DependencyException):
         api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kraken')
-        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+        exchange.stoploss(
+            pair='ETH/BTC',
+            amount=1,
+            stop_price=220,
+            order_types={},
+            side=side,
+            leverage=1.0
+        )
 
     with pytest.raises(InvalidOrderException):
         api_mock.create_order = MagicMock(
             side_effect=ccxt.InvalidOrder("kraken Order would trigger immediately."))
         exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kraken')
-        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+        exchange.stoploss(
+            pair='ETH/BTC',
+            amount=1,
+            stop_price=220,
+            order_types={},
+            side=side,
+            leverage=1.0
+        )
 
     ccxt_exceptionhandlers(mocker, default_conf, api_mock, "kraken",
                            "stoploss", "create_order", retries=1,
-                           pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+                           pair='ETH/BTC', amount=1, stop_price=220, order_types={},
+                           side=side, leverage=1.0)
 
 
-def test_stoploss_order_dry_run_kraken(default_conf, mocker):
+@pytest.mark.parametrize('side', ['buy', 'sell'])
+def test_stoploss_order_dry_run_kraken(default_conf, mocker, side):
     api_mock = MagicMock()
     default_conf['dry_run'] = True
     mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
@@ -231,7 +269,14 @@ def test_stoploss_order_dry_run_kraken(default_conf, mocker):
 
     api_mock.create_order.reset_mock()
 
-    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+    order = exchange.stoploss(
+        pair='ETH/BTC',
+        amount=1,
+        stop_price=220,
+        order_types={},
+        side=side,
+        leverage=1.0
+    )
 
     assert 'id' in order
     assert 'info' in order
@@ -242,14 +287,18 @@ def test_stoploss_order_dry_run_kraken(default_conf, mocker):
     assert order['amount'] == 1
 
 
-def test_stoploss_adjust_kraken(mocker, default_conf):
+@pytest.mark.parametrize('sl1,sl2,sl3,side', [
+    (1501, 1499, 1501, "sell"),
+    (1499, 1501, 1499, "buy")
+])
+def test_stoploss_adjust_kraken(mocker, default_conf, sl1, sl2, sl3, side):
     exchange = get_patched_exchange(mocker, default_conf, id='kraken')
     order = {
         'type': STOPLOSS_ORDERTYPE,
         'price': 1500,
     }
-    assert exchange.stoploss_adjust(1501, order)
-    assert not exchange.stoploss_adjust(1499, order)
+    assert exchange.stoploss_adjust(sl1, order, side=side)
+    assert not exchange.stoploss_adjust(sl2, order, side=side)
     # Test with invalid order case ...
     order['type'] = 'stop_loss_limit'
-    assert not exchange.stoploss_adjust(1501, order)
+    assert not exchange.stoploss_adjust(sl3, order, side=side)
diff --git a/tests/exchange/test_kucoin.py b/tests/exchange/test_kucoin.py
new file mode 100644
index 000000000..8af1e83a3
--- /dev/null
+++ b/tests/exchange/test_kucoin.py
@@ -0,0 +1,127 @@
+from random import randint
+from unittest.mock import MagicMock
+
+import ccxt
+import pytest
+
+from freqtrade.exceptions import DependencyException, InvalidOrderException, OperationalException
+from tests.conftest import get_patched_exchange
+from tests.exchange.test_exchange import ccxt_exceptionhandlers
+
+
+@pytest.mark.parametrize('order_type', ['market', 'limit'])
+@pytest.mark.parametrize('limitratio,expected,side', [
+    (None, 220 * 0.99, "sell"),
+    (0.99, 220 * 0.99, "sell"),
+    (0.98, 220 * 0.98, "sell"),
+])
+def test_stoploss_order_kucoin(default_conf, mocker, limitratio, expected, side, order_type):
+    api_mock = MagicMock()
+    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
+
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kucoin')
+    if order_type == 'limit':
+        with pytest.raises(OperationalException):
+            order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
+                                      order_types={
+                                          'stoploss': order_type,
+                                          'stoploss_on_exchange_limit_ratio': 1.05},
+                                      side=side, leverage=1.0)
+
+    api_mock.create_order.reset_mock()
+    order_types = {'stoploss': order_type}
+    if limitratio is not None:
+        order_types.update({'stoploss_on_exchange_limit_ratio': limitratio})
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
+                              order_types=order_types, side=side, leverage=1.0)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
+    assert api_mock.create_order.call_args_list[0][1]['type'] == order_type
+    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
+    # Price should be 1% below stopprice
+    if order_type == 'limit':
+        assert api_mock.create_order.call_args_list[0][1]['price'] == expected
+    else:
+        assert api_mock.create_order.call_args_list[0][1]['price'] is None
+
+    assert api_mock.create_order.call_args_list[0][1]['params'] == {
+        'stopPrice': 220,
+        'stop': 'loss'
+    }
+
+    # test exception handling
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kucoin')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
+                          order_types={}, side=side, leverage=1.0)
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.create_order = MagicMock(
+            side_effect=ccxt.InvalidOrder("kucoin Order would trigger immediately."))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kucoin')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
+                          order_types={}, side=side, leverage=1.0)
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, "kucoin",
+                           "stoploss", "create_order", retries=1,
+                           pair='ETH/BTC', amount=1, stop_price=220, order_types={},
+                           side=side, leverage=1.0)
+
+
+def test_stoploss_order_dry_run_kucoin(default_conf, mocker):
+    api_mock = MagicMock()
+    order_type = 'market'
+    default_conf['dry_run'] = True
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kucoin')
+
+    with pytest.raises(OperationalException):
+        order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
+                                  order_types={'stoploss': 'limit',
+                                               'stoploss_on_exchange_limit_ratio': 1.05},
+                                  side='sell', leverage=1.0)
+
+    api_mock.create_order.reset_mock()
+
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
+                              order_types={}, side='sell', leverage=1.0)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert 'type' in order
+
+    assert order['type'] == order_type
+    assert order['price'] == 220
+    assert order['amount'] == 1
+
+
+def test_stoploss_adjust_kucoin(mocker, default_conf):
+    exchange = get_patched_exchange(mocker, default_conf, id='kucoin')
+    order = {
+        'type': 'limit',
+        'price': 1500,
+        'stopPrice': 1500,
+        'info': {'stopPrice': 1500, 'stop': "limit"},
+    }
+    assert exchange.stoploss_adjust(1501, order, 'sell')
+    assert not exchange.stoploss_adjust(1499, order, 'sell')
+    # Test with invalid order case
+    order['info']['stop'] = None
+    assert not exchange.stoploss_adjust(1501, order, 'sell')
diff --git a/tests/exchange/test_okx.py b/tests/exchange/test_okx.py
new file mode 100644
index 000000000..8ecdf6904
--- /dev/null
+++ b/tests/exchange/test_okx.py
@@ -0,0 +1,360 @@
+from unittest.mock import MagicMock, PropertyMock
+
+from freqtrade.enums import MarginMode, TradingMode
+from tests.conftest import get_patched_exchange
+
+
+def test_get_maintenance_ratio_and_amt_okx(
+    default_conf,
+    mocker,
+):
+    api_mock = MagicMock()
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    default_conf['dry_run'] = False
+    mocker.patch.multiple(
+        'freqtrade.exchange.Okx',
+        exchange_has=MagicMock(return_value=True),
+        load_leverage_tiers=MagicMock(return_value={
+            'ETH/USDT:USDT': [
+                {
+                    'tier': 1,
+                    'notionalFloor': 0,
+                    'notionalCap': 2000,
+                    'maintenanceMarginRate': 0.01,
+                    'maxLeverage': 75,
+                    'info': {
+                        'baseMaxLoan': '',
+                        'imr': '0.013',
+                        'instId': '',
+                        'maxLever': '75',
+                        'maxSz': '2000',
+                        'minSz': '0',
+                        'mmr': '0.01',
+                        'optMgnFactor': '0',
+                        'quoteMaxLoan': '',
+                        'tier': '1',
+                        'uly': 'ETH-USDT'
+                    }
+                },
+                {
+                    'tier': 2,
+                    'notionalFloor': 2001,
+                    'notionalCap': 4000,
+                    'maintenanceMarginRate': 0.015,
+                    'maxLeverage': 50,
+                    'info': {
+                        'baseMaxLoan': '',
+                        'imr': '0.02',
+                        'instId': '',
+                        'maxLever': '50',
+                        'maxSz': '4000',
+                        'minSz': '2001',
+                        'mmr': '0.015',
+                        'optMgnFactor': '0',
+                        'quoteMaxLoan': '',
+                        'tier': '2',
+                        'uly': 'ETH-USDT'
+                    }
+                },
+                {
+                    'tier': 3,
+                    'notionalFloor': 4001,
+                    'notionalCap': 8000,
+                    'maintenanceMarginRate': 0.02,
+                    'maxLeverage': 20,
+                    'info': {
+                        'baseMaxLoan': '',
+                        'imr': '0.05',
+                        'instId': '',
+                        'maxLever': '20',
+                        'maxSz': '8000',
+                        'minSz': '4001',
+                        'mmr': '0.02',
+                        'optMgnFactor': '0',
+                        'quoteMaxLoan': '',
+                        'tier': '3',
+                        'uly': 'ETH-USDT'
+                    }
+                },
+            ],
+            'ADA/USDT:USDT': [
+                {
+                    'tier': 1,
+                    'notionalFloor': 0,
+                    'notionalCap': 500,
+                    'maintenanceMarginRate': 0.02,
+                    'maxLeverage': 75,
+                    'info': {
+                        'baseMaxLoan': '',
+                        'imr': '0.013',
+                        'instId': '',
+                        'maxLever': '75',
+                        'maxSz': '500',
+                        'minSz': '0',
+                        'mmr': '0.01',
+                        'optMgnFactor': '0',
+                        'quoteMaxLoan': '',
+                        'tier': '1',
+                        'uly': 'ADA-USDT'
+                    }
+                },
+                {
+                    'tier': 2,
+                    'notionalFloor': 501,
+                    'notionalCap': 1000,
+                    'maintenanceMarginRate': 0.025,
+                    'maxLeverage': 50,
+                    'info': {
+                        'baseMaxLoan': '',
+                        'imr': '0.02',
+                        'instId': '',
+                        'maxLever': '50',
+                        'maxSz': '1000',
+                        'minSz': '501',
+                        'mmr': '0.015',
+                        'optMgnFactor': '0',
+                        'quoteMaxLoan': '',
+                        'tier': '2',
+                        'uly': 'ADA-USDT'
+                    }
+                },
+                {
+                    'tier': 3,
+                    'notionalFloor': 1001,
+                    'notionalCap': 2000,
+                    'maintenanceMarginRate': 0.03,
+                    'maxLeverage': 20,
+                    'info': {
+                        'baseMaxLoan': '',
+                        'imr': '0.05',
+                        'instId': '',
+                        'maxLever': '20',
+                        'maxSz': '2000',
+                        'minSz': '1001',
+                        'mmr': '0.02',
+                        'optMgnFactor': '0',
+                        'quoteMaxLoan': '',
+                        'tier': '3',
+                        'uly': 'ADA-USDT'
+                    }
+                },
+            ]
+        })
+    )
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="okx")
+    assert exchange.get_maintenance_ratio_and_amt('ETH/USDT:USDT', 2000) == (0.01, None)
+    assert exchange.get_maintenance_ratio_and_amt('ETH/USDT:USDT', 2001) == (0.015, None)
+    assert exchange.get_maintenance_ratio_and_amt('ETH/USDT:USDT', 4001) == (0.02, None)
+    assert exchange.get_maintenance_ratio_and_amt('ETH/USDT:USDT', 8000) == (0.02, None)
+
+    assert exchange.get_maintenance_ratio_and_amt('ADA/USDT:USDT', 1) == (0.02, None)
+    assert exchange.get_maintenance_ratio_and_amt('ADA/USDT:USDT', 2000) == (0.03, None)
+
+
+def test_get_max_pair_stake_amount_okx(default_conf, mocker, leverage_tiers):
+
+    exchange = get_patched_exchange(mocker, default_conf, id="okx")
+    assert exchange.get_max_pair_stake_amount('BNB/BUSD', 1.0) == float('inf')
+
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    exchange = get_patched_exchange(mocker, default_conf, id="okx")
+    exchange._leverage_tiers = leverage_tiers
+
+    assert exchange.get_max_pair_stake_amount('BNB/BUSD', 1.0) == 30000000
+    assert exchange.get_max_pair_stake_amount('BNB/USDT', 1.0) == 50000000
+    assert exchange.get_max_pair_stake_amount('BTC/USDT', 1.0) == 1000000000
+    assert exchange.get_max_pair_stake_amount('BTC/USDT', 1.0, 10.0) == 100000000
+
+    assert exchange.get_max_pair_stake_amount('TTT/USDT', 1.0) == float('inf')  # Not in tiers
+
+
+def test_load_leverage_tiers_okx(default_conf, mocker, markets):
+    api_mock = MagicMock()
+    type(api_mock).has = PropertyMock(return_value={
+        'fetchLeverageTiers': False,
+        'fetchMarketLeverageTiers': True,
+    })
+    api_mock.fetch_market_leverage_tiers = MagicMock(side_effect=[
+        [
+            {
+                'tier': 1,
+                'notionalFloor': 0,
+                'notionalCap': 500,
+                'maintenanceMarginRate': 0.02,
+                'maxLeverage': 75,
+                'info': {
+                    'baseMaxLoan': '',
+                    'imr': '0.013',
+                    'instId': '',
+                    'maxLever': '75',
+                    'maxSz': '500',
+                    'minSz': '0',
+                    'mmr': '0.01',
+                    'optMgnFactor': '0',
+                    'quoteMaxLoan': '',
+                    'tier': '1',
+                    'uly': 'ADA-USDT'
+                }
+            },
+            {
+                'tier': 2,
+                'notionalFloor': 501,
+                'notionalCap': 1000,
+                'maintenanceMarginRate': 0.025,
+                'maxLeverage': 50,
+                'info': {
+                    'baseMaxLoan': '',
+                    'imr': '0.02',
+                    'instId': '',
+                    'maxLever': '50',
+                    'maxSz': '1000',
+                    'minSz': '501',
+                    'mmr': '0.015',
+                    'optMgnFactor': '0',
+                    'quoteMaxLoan': '',
+                    'tier': '2',
+                    'uly': 'ADA-USDT'
+                }
+            },
+            {
+                'tier': 3,
+                'notionalFloor': 1001,
+                'notionalCap': 2000,
+                'maintenanceMarginRate': 0.03,
+                'maxLeverage': 20,
+                'info': {
+                    'baseMaxLoan': '',
+                    'imr': '0.05',
+                    'instId': '',
+                    'maxLever': '20',
+                    'maxSz': '2000',
+                    'minSz': '1001',
+                    'mmr': '0.02',
+                    'optMgnFactor': '0',
+                    'quoteMaxLoan': '',
+                    'tier': '3',
+                    'uly': 'ADA-USDT'
+                }
+            },
+        ],
+        [
+            {
+                'tier': 1,
+                'notionalFloor': 0,
+                'notionalCap': 2000,
+                'maintenanceMarginRate': 0.01,
+                'maxLeverage': 75,
+                'info': {
+                    'baseMaxLoan': '',
+                    'imr': '0.013',
+                    'instId': '',
+                    'maxLever': '75',
+                    'maxSz': '2000',
+                    'minSz': '0',
+                    'mmr': '0.01',
+                    'optMgnFactor': '0',
+                    'quoteMaxLoan': '',
+                    'tier': '1',
+                    'uly': 'ETH-USDT'
+                }
+            },
+            {
+                'tier': 2,
+                'notionalFloor': 2001,
+                'notionalCap': 4000,
+                'maintenanceMarginRate': 0.015,
+                'maxLeverage': 50,
+                'info': {
+                    'baseMaxLoan': '',
+                    'imr': '0.02',
+                    'instId': '',
+                    'maxLever': '50',
+                    'maxSz': '4000',
+                    'minSz': '2001',
+                    'mmr': '0.015',
+                    'optMgnFactor': '0',
+                    'quoteMaxLoan': '',
+                    'tier': '2',
+                    'uly': 'ETH-USDT'
+                }
+            },
+            {
+                'tier': 3,
+                'notionalFloor': 4001,
+                'notionalCap': 8000,
+                'maintenanceMarginRate': 0.02,
+                'maxLeverage': 20,
+                'info': {
+                    'baseMaxLoan': '',
+                    'imr': '0.05',
+                    'instId': '',
+                    'maxLever': '20',
+                    'maxSz': '8000',
+                    'minSz': '4001',
+                    'mmr': '0.02',
+                    'optMgnFactor': '0',
+                    'quoteMaxLoan': '',
+                    'tier': '3',
+                    'uly': 'ETH-USDT'
+                }
+            },
+        ]
+    ])
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    default_conf['stake_currency'] = 'USDT'
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="okx")
+    exchange.trading_mode = TradingMode.FUTURES
+    exchange.margin_mode = MarginMode.ISOLATED
+    exchange.markets = markets
+    # Initialization of load_leverage_tiers happens as part of exchange init.
+    assert exchange._leverage_tiers == {
+        'ADA/USDT:USDT': [
+            {
+                'min': 0,
+                'max': 500,
+                'mmr': 0.02,
+                'lev': 75,
+                'maintAmt': None
+            },
+            {
+                'min': 501,
+                'max': 1000,
+                'mmr': 0.025,
+                'lev': 50,
+                'maintAmt': None
+            },
+            {
+                'min': 1001,
+                'max': 2000,
+                'mmr': 0.03,
+                'lev': 20,
+                'maintAmt': None
+            },
+        ],
+        'ETH/USDT:USDT': [
+            {
+                'min': 0,
+                'max': 2000,
+                'mmr': 0.01,
+                'lev': 75,
+                'maintAmt': None
+            },
+            {
+                'min': 2001,
+                'max': 4000,
+                'mmr': 0.015,
+                'lev': 50,
+                'maintAmt': None
+            },
+            {
+                'min': 4001,
+                'max': 8000,
+                'mmr': 0.02,
+                'lev': 20,
+                'maintAmt': None
+            },
+        ],
+    }
diff --git a/tests/leverage/test_candletype.py b/tests/leverage/test_candletype.py
new file mode 100644
index 000000000..ed7991d26
--- /dev/null
+++ b/tests/leverage/test_candletype.py
@@ -0,0 +1,27 @@
+import pytest
+
+from freqtrade.enums import CandleType
+
+
+@pytest.mark.parametrize('input,expected', [
+    ('', CandleType.SPOT),
+    ('spot', CandleType.SPOT),
+    (CandleType.SPOT, CandleType.SPOT),
+    (CandleType.FUTURES, CandleType.FUTURES),
+    (CandleType.INDEX, CandleType.INDEX),
+    (CandleType.MARK, CandleType.MARK),
+    ('futures', CandleType.FUTURES),
+    ('mark', CandleType.MARK),
+    ('premiumIndex', CandleType.PREMIUMINDEX),
+])
+def test_CandleType_from_string(input, expected):
+    assert CandleType.from_string(input) == expected
+
+
+@pytest.mark.parametrize('input,expected', [
+    ('futures', CandleType.FUTURES),
+    ('spot', CandleType.SPOT),
+    ('margin', CandleType.SPOT),
+])
+def test_CandleType_get_default(input, expected):
+    assert CandleType.get_default(input) == expected
diff --git a/tests/leverage/test_interest.py b/tests/leverage/test_interest.py
new file mode 100644
index 000000000..6b189ce50
--- /dev/null
+++ b/tests/leverage/test_interest.py
@@ -0,0 +1,38 @@
+from decimal import Decimal
+from math import isclose
+
+import pytest
+
+from freqtrade.leverage import interest
+
+
+ten_mins = Decimal(1 / 6)
+five_hours = Decimal(5.0)
+twentyfive_hours = Decimal(25.0)
+
+
+@pytest.mark.parametrize('exchange,interest_rate,hours,expected', [
+    ('binance', 0.0005, ten_mins, 0.00125),
+    ('binance', 0.00025, ten_mins, 0.000625),
+    ('binance', 0.00025, five_hours, 0.003125),
+    ('binance', 0.00025, twentyfive_hours, 0.015625),
+    # Kraken
+    ('kraken', 0.0005, ten_mins, 0.06),
+    ('kraken', 0.00025, ten_mins, 0.03),
+    ('kraken', 0.00025, five_hours, 0.045),
+    ('kraken', 0.00025, twentyfive_hours, 0.12),
+    # FTX
+    ('ftx', 0.0005, ten_mins, 0.00125),
+    ('ftx', 0.00025, ten_mins, 0.000625),
+    ('ftx', 0.00025, five_hours, 0.003125),
+    ('ftx', 0.00025, twentyfive_hours, 0.015625),
+])
+def test_interest(exchange, interest_rate, hours, expected):
+    borrowed = Decimal(60.0)
+
+    assert isclose(interest(
+        exchange_name=exchange,
+        borrowed=borrowed,
+        rate=Decimal(interest_rate),
+        hours=hours
+    ), expected)
diff --git a/tests/optimize/__init__.py b/tests/optimize/__init__.py
index 6ad2d300b..fc4125a42 100644
--- a/tests/optimize/__init__.py
+++ b/tests/optimize/__init__.py
@@ -3,7 +3,7 @@ from typing import Dict, List, NamedTuple, Optional
 import arrow
 from pandas import DataFrame
 
-from freqtrade.enums import SellType
+from freqtrade.enums import ExitType
 from freqtrade.exchange import timeframe_to_minutes
 
 
@@ -15,10 +15,11 @@ class BTrade(NamedTuple):
     """
     Minimalistic Trade result used for functional backtesting
     """
-    sell_reason: SellType
+    exit_reason: ExitType
     open_tick: int
     close_tick: int
-    buy_tag: Optional[str] = None
+    enter_tag: Optional[str] = None
+    is_short: bool = False
 
 
 class BTContainer(NamedTuple):
@@ -34,8 +35,11 @@ class BTContainer(NamedTuple):
     trailing_only_offset_is_reached: bool = False
     trailing_stop_positive: Optional[float] = None
     trailing_stop_positive_offset: float = 0.0
-    use_sell_signal: bool = False
+    use_exit_signal: bool = False
     use_custom_stoploss: bool = False
+    custom_entry_price: Optional[float] = None
+    custom_exit_price: Optional[float] = None
+    leverage: float = 1.0
 
 
 def _get_frame_time_from_offset(offset):
@@ -44,14 +48,22 @@ def _get_frame_time_from_offset(offset):
 
 
 def _build_backtest_dataframe(data):
-    columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell']
-    columns = columns + ['buy_tag'] if len(data[0]) == 9 else columns
+    columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'enter_long', 'exit_long',
+               'enter_short', 'exit_short']
+    if len(data[0]) == 8:
+        # No short columns
+        data = [d + [0, 0] for d in data]
+    columns = columns + ['enter_tag'] if len(data[0]) == 11 else columns
 
     frame = DataFrame.from_records(data, columns=columns)
     frame['date'] = frame['date'].apply(_get_frame_time_from_offset)
     # Ensure floats are in place
     for column in ['open', 'high', 'low', 'close', 'volume']:
         frame[column] = frame[column].astype('float64')
-    if 'buy_tag' not in columns:
-        frame['buy_tag'] = None
+
+    # Ensure all candles make kindof sense
+    assert all(frame['low'] <= frame['close'])
+    assert all(frame['low'] <= frame['open'])
+    assert all(frame['high'] >= frame['close'])
+    assert all(frame['high'] >= frame['open'])
     return frame
diff --git a/tests/optimize/conftest.py b/tests/optimize/conftest.py
index 5c5171c3a..8a9e0cbf0 100644
--- a/tests/optimize/conftest.py
+++ b/tests/optimize/conftest.py
@@ -5,7 +5,7 @@ from pathlib import Path
 import pandas as pd
 import pytest
 
-from freqtrade.enums import RunMode, SellType
+from freqtrade.enums import ExitType, RunMode
 from freqtrade.optimize.hyperopt import Hyperopt
 from tests.conftest import patch_exchange
 
@@ -39,16 +39,25 @@ def hyperopt(hyperopt_conf, mocker):
 def hyperopt_results():
     return pd.DataFrame(
         {
-            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
-            'profit_ratio': [-0.1, 0.2, 0.3],
-            'profit_abs': [-0.2, 0.4, 0.6],
-            'trade_duration': [10, 30, 10],
-            'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.ROI],
+            'pair': ['ETH/USDT', 'ETH/USDT', 'ETH/USDT', 'ETH/USDT'],
+            'profit_ratio': [-0.1, 0.2, -0.1, 0.3],
+            'profit_abs': [-0.2, 0.4, -0.2, 0.6],
+            'trade_duration': [10, 30, 10, 10],
+            'amount': [0.1, 0.1, 0.1, 0.1],
+            'exit_reason': [ExitType.STOP_LOSS, ExitType.ROI, ExitType.STOP_LOSS, ExitType.ROI],
+            'open_date':
+            [
+                datetime(2019, 1, 1, 9, 15, 0),
+                datetime(2019, 1, 2, 8, 55, 0),
+                datetime(2019, 1, 3, 9, 15, 0),
+                datetime(2019, 1, 4, 9, 15, 0),
+            ],
             'close_date':
             [
-                datetime(2019, 1, 1, 9, 26, 3, 478039),
-                datetime(2019, 2, 1, 9, 26, 3, 478039),
-                datetime(2019, 3, 1, 9, 26, 3, 478039)
-            ]
+                datetime(2019, 1, 1, 9, 25, 0),
+                datetime(2019, 1, 2, 9, 25, 0),
+                datetime(2019, 1, 3, 9, 25, 0),
+                datetime(2019, 1, 4, 9, 25, 0),
+            ],
         }
     )
diff --git a/tests/optimize/test_backtest_detail.py b/tests/optimize/test_backtest_detail.py
index e5c037f3e..ea13de4c8 100644
--- a/tests/optimize/test_backtest_detail.py
+++ b/tests/optimize/test_backtest_detail.py
@@ -1,10 +1,11 @@
 # pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, C0330, unused-argument
 import logging
+from unittest.mock import MagicMock
 
 import pytest
 
 from freqtrade.data.history import get_timerange
-from freqtrade.enums import SellType
+from freqtrade.enums import ExitType
 from freqtrade.optimize.backtesting import Backtesting
 from tests.conftest import patch_exchange
 from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
@@ -14,36 +15,36 @@ from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
 # Test 0: Sell with signal sell in candle 3
 # Test with Stop-loss at 1%
 tc0 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5012, 4986, 4600, 6172, 0, 0],  # exit with stoploss hit
-    [3, 5010, 5000, 4980, 5010, 6172, 0, 1],
-    [4, 5010, 4987, 4977, 4995, 6172, 0, 0],
-    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
-    stop_loss=-0.01, roi={"0": 1}, profit_perc=0.002, use_sell_signal=True,
-    trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=4)]
+    [2, 4987, 5012, 4986, 4986, 6172, 0, 0],  # exit with stoploss hit
+    [3, 5010, 5010, 4980, 5010, 6172, 0, 1],
+    [4, 5010, 5011, 4977, 4995, 6172, 0, 0],
+    [5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
+    stop_loss=-0.01, roi={"0": 1}, profit_perc=0.002, use_exit_signal=True,
+    trades=[BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=4)]
 )
 
 # Test 1: Stop-Loss Triggered 1% loss
 # Test with Stop-loss at 1%
 tc1 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
     [2, 4987, 5012, 4600, 4600, 6172, 0, 0],  # exit with stoploss hit
-    [3, 4975, 5000, 4980, 4977, 6172, 0, 0],
-    [4, 4977, 4987, 4977, 4995, 6172, 0, 0],
-    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
+    [3, 4975, 5000, 4975, 4977, 6172, 0, 0],
+    [4, 4977, 4995, 4977, 4995, 6172, 0, 0],
+    [5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
     stop_loss=-0.01, roi={"0": 1}, profit_perc=-0.01,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=2)]
 )
 
 
 # Test 2: Minus 4% Low, minus 1% close
 # Test with Stop-Loss at 3%
 tc2 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
     [2, 4987, 5012, 4962, 4975, 6172, 0, 0],
@@ -51,7 +52,7 @@ tc2 = BTContainer(data=[
     [4, 4962, 4987, 4937, 4950, 6172, 0, 0],
     [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
     stop_loss=-0.03, roi={"0": 1}, profit_perc=-0.03,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=3)]
 )
 
 
@@ -62,17 +63,17 @@ tc2 = BTContainer(data=[
 #  Trade-A: Stop-Loss Triggered 2% Loss
 #           Trade-B: Stop-Loss Triggered 2% Loss
 tc3 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
     [2, 4987, 5012, 4800, 4975, 6172, 0, 0],  # exit with stoploss hit
     [3, 4975, 5000, 4950, 4962, 6172, 1, 0],
     [4, 4975, 5000, 4950, 4962, 6172, 0, 0],  # enter trade 2 (signal on last candle)
     [5, 4962, 4987, 4000, 4000, 6172, 0, 0],  # exit with stoploss hit
-    [6, 4950, 4975, 4975, 4950, 6172, 0, 0]],
+    [6, 4950, 4975, 4950, 4950, 6172, 0, 0]],
     stop_loss=-0.02, roi={"0": 1}, profit_perc=-0.04,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2),
-            BTrade(sell_reason=SellType.STOP_LOSS, open_tick=4, close_tick=5)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=2),
+            BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=4, close_tick=5)]
 )
 
 # Test 4: Minus 3% / recovery +15%
@@ -80,7 +81,7 @@ tc3 = BTContainer(data=[
 # Test with Stop-loss at 2% ROI 6%
 # Stop-Loss Triggered 2% Loss
 tc4 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
     [2, 4987, 5750, 4850, 5750, 6172, 0, 0],  # Exit with stoploss hit
@@ -88,197 +89,197 @@ tc4 = BTContainer(data=[
     [4, 4962, 4987, 4937, 4950, 6172, 0, 0],
     [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
     stop_loss=-0.02, roi={"0": 0.06}, profit_perc=-0.02,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=2)]
 )
 
 # Test 5: Drops 0.5% Closes +20%, ROI triggers 3% Gain
 # stop-loss: 1%, ROI: 3%
 tc5 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4980, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4980, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
     [2, 4987, 5025, 4975, 4987, 6172, 0, 0],
     [3, 4975, 6000, 4975, 6000, 6172, 0, 0],  # ROI
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [4, 4962, 4987, 4962, 4972, 6172, 0, 0],
     [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
     stop_loss=-0.01, roi={"0": 0.03}, profit_perc=0.03,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=3)]
 )
 
 # Test 6: Drops 3% / Recovers 6% Positive / Closes 1% positve, Stop-Loss triggers 2% Loss
 # stop-loss: 2% ROI: 5%
 tc6 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
     [2, 4987, 5300, 4850, 5050, 6172, 0, 0],  # Exit with stoploss
     [3, 4975, 5000, 4950, 4962, 6172, 0, 0],
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [4, 4962, 4987, 4950, 4950, 6172, 0, 0],
     [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
     stop_loss=-0.02, roi={"0": 0.05}, profit_perc=-0.02,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=2)]
 )
 
 # Test 7: 6% Positive / 1% Negative / Close 1% Positve, ROI Triggers 3% Gain
 # stop-loss: 2% ROI: 3%
 tc7 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
     [2, 4987, 5300, 4950, 5050, 6172, 0, 0],
     [3, 4975, 5000, 4950, 4962, 6172, 0, 0],
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [4, 4962, 4987, 4950, 4950, 6172, 0, 0],
     [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
     stop_loss=-0.02, roi={"0": 0.03}, profit_perc=0.03,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=2)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=2)]
 )
 
 
 # Test 8: trailing_stop should raise so candle 3 causes a stoploss.
 # stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted in candle 2
 tc8 = BTContainer(data=[
-    # D   O     H     L    C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
     [1, 5000, 5050, 4950, 5000, 6172, 0, 0],
     [2, 5000, 5250, 4750, 4850, 6172, 0, 0],
     [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.055, trailing_stop=True,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
 )
 
 
 # Test 9: trailing_stop should raise - high and low in same candle.
 # stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted in candle 3
 tc9 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
     [1, 5000, 5050, 4950, 5000, 6172, 0, 0],
     [2, 5000, 5050, 4950, 5000, 6172, 0, 0],
     [3, 5000, 5200, 4550, 4850, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.064, trailing_stop=True,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
 )
 
 # Test 10: trailing_stop should raise so candle 3 causes a stoploss
 # without applying trailing_stop_positive since stoploss_offset is at 10%.
 # stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2
 tc10 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [1, 5000, 5100, 4950, 5100, 6172, 0, 0],
     [2, 5100, 5251, 5100, 5100, 6172, 0, 0],
     [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.1, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.10,
     trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=4)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=4)]
 )
 
 # Test 11: trailing_stop should raise so candle 3 causes a stoploss
 # applying a positive trailing stop of 3% since stop_positive_offset is reached.
 # stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2
 tc11 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [1, 5000, 5100, 4950, 5100, 6172, 0, 0],
     [2, 5100, 5251, 5100, 5100, 6172, 0, 0],
     [3, 5000, 5150, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.019, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
     trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
 )
 
 # Test 12: trailing_stop should raise in candle 2 and cause a stoploss in the same candle
 # applying a positive trailing stop of 3% since stop_positive_offset is reached.
 # stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2
 tc12 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [1, 5000, 5100, 4950, 5100, 6172, 0, 0],
     [2, 5100, 5251, 4650, 5100, 6172, 0, 0],
     [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.019, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
     trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=2)]
+    trades=[BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=2)]
 )
 
 # Test 13: Buy and sell ROI on same candle
 # stop-loss: 10% (should not apply), ROI: 1%
 tc13 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
     [1, 5000, 5100, 4950, 5100, 6172, 0, 0],
     [2, 5100, 5251, 4850, 5100, 6172, 0, 0],
-    [3, 4850, 5050, 4850, 4750, 6172, 0, 0],
-    [4, 4750, 4950, 4850, 4750, 6172, 0, 0]],
+    [3, 4850, 5050, 4750, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4750, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.01}, profit_perc=0.01,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=1)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=1)]
 )
 
 # Test 14 - Buy and Stoploss on same candle
 # stop-loss: 5%, ROI: 10% (should not apply)
 tc14 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
     [1, 5000, 5100, 4600, 5100, 6172, 0, 0],
     [2, 5100, 5251, 4850, 5100, 6172, 0, 0],
-    [3, 4850, 5050, 4850, 4750, 6172, 0, 0],
+    [3, 4850, 5050, 4750, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.05, roi={"0": 0.10}, profit_perc=-0.05,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
 
 # Test 15 - Buy and ROI on same candle, followed by buy and Stoploss on next candle
 # stop-loss: 5%, ROI: 10% (should not apply)
 tc15 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
     [1, 5000, 5100, 4900, 5100, 6172, 1, 0],
     [2, 5100, 5251, 4650, 5100, 6172, 0, 0],
-    [3, 4850, 5050, 4850, 4750, 6172, 0, 0],
+    [3, 4850, 5050, 4750, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.05, roi={"0": 0.01}, profit_perc=-0.04,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=1),
-            BTrade(sell_reason=SellType.STOP_LOSS, open_tick=2, close_tick=2)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=1),
+            BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=2, close_tick=2)]
 )
 
-# Test 16: Buy, hold for 65 min, then forcesell using roi=-1
+# Test 16: Buy, hold for 65 min, then forceexit using roi=-1
 # Causes negative profit even though sell-reason is ROI.
 # stop-loss: 10%, ROI: 10% (should not apply), -100% after 65 minutes (limits trade duration)
 tc16 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
     [2, 4987, 5300, 4950, 5050, 6172, 0, 0],
-    [3, 4975, 5000, 4940, 4962, 6172, 0, 0],  # ForceSell on ROI (roi=-1)
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [3, 4975, 5000, 4940, 4962, 6172, 0, 0],  # Forceexit on ROI (roi=-1)
+    [4, 4962, 4987, 4950, 4950, 6172, 0, 0],
     [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10, "65": -1}, profit_perc=-0.012,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=3)]
 )
 
-# Test 17: Buy, hold for 120 mins, then forcesell using roi=-1
+# Test 17: Buy, hold for 120 mins, then forceexit using roi=-1
 # Causes negative profit even though sell-reason is ROI.
 # stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
 # Uses open as sell-rate (special case) - since the roi-time is a multiple of the timeframe.
 tc17 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
     [2, 4987, 5300, 4950, 5050, 6172, 0, 0],
-    [3, 4980, 5000, 4940, 4962, 6172, 0, 0],  # ForceSell on ROI (roi=-1)
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [3, 4980, 5000, 4940, 4962, 6172, 0, 0],  # Forceexit on ROI (roi=-1)
+    [4, 4962, 4987, 4950, 4950, 6172, 0, 0],
     [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10, "120": -1}, profit_perc=-0.004,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=3)]
 )
 
 
@@ -286,45 +287,45 @@ tc17 = BTContainer(data=[
 # stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
 # uses open_rate as sell-price
 tc18 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
     [2, 4987, 5300, 4950, 5200, 6172, 0, 0],
     [3, 5200, 5220, 4940, 4962, 6172, 0, 0],  # Sell on ROI (sells on open)
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [4, 4962, 4987, 4950, 4950, 6172, 0, 0],
     [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10, "120": 0.01}, profit_perc=0.04,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=3)]
 )
 
 # Test 19: Buy, hold for 119 mins, then drop ROI to 1%, causing a sell in candle 3.
 # stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
 # uses calculated ROI (1%) as sell rate, otherwise identical to tc18
 tc19 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
     [2, 4987, 5300, 4950, 5200, 6172, 0, 0],
     [3, 5000, 5300, 4940, 4962, 6172, 0, 0],  # Sell on ROI
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
-    [5, 4550, 4975, 4925, 4950, 6172, 0, 0]],
+    [4, 4962, 4987, 4950, 4950, 6172, 0, 0],
+    [5, 4550, 4975, 4550, 4950, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10, "120": 0.01}, profit_perc=0.01,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=3)]
 )
 
 # Test 20: Buy, hold for 119 mins, then drop ROI to 1%, causing a sell in candle 3.
 # stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
 # uses calculated ROI (1%) as sell rate, otherwise identical to tc18
 tc20 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
     [2, 4987, 5300, 4950, 5200, 6172, 0, 0],
     [3, 5200, 5300, 4940, 4962, 6172, 0, 0],  # Sell on ROI
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
-    [5, 4550, 4975, 4925, 4950, 6172, 0, 0]],
+    [4, 4962, 4987, 4950, 4950, 6172, 0, 0],
+    [5, 4925, 4975, 4925, 4950, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10, "119": 0.01}, profit_perc=0.01,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=3)]
 )
 
 # Test 21: trailing_stop ROI collision.
@@ -332,209 +333,427 @@ tc20 = BTContainer(data=[
 # which cannot happen in reality
 # stop-loss: 10%, ROI: 4%, Trailing stop adjusted at the sell candle
 tc21 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [1, 5000, 5100, 4950, 5100, 6172, 0, 0],
     [2, 5100, 5251, 4650, 5100, 6172, 0, 0],
     [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.04}, profit_perc=0.04, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
     trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=2)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=2)]
 )
 
 # Test 22: trailing_stop Raises in candle 2 - but ROI applies at the same time.
 # applying a positive trailing stop of 3% - ROI should apply before trailing stop.
 # stop-loss: 10%, ROI: 4%, stoploss adjusted candle 2
 tc22 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [1, 5000, 5100, 4950, 5100, 6172, 0, 0],
     [2, 5100, 5251, 5100, 5100, 6172, 0, 0],
     [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.04}, profit_perc=0.04, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
     trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=2)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=2)]
 )
 
-# Test 23: trailing_stop Raises in candle 2 (does not trigger)
+
+# Test 23: trailing_stop Raises in candle 2 - but ROI applies at the same time.
+# applying a positive trailing stop of 3% - ROI should apply before trailing stop.
+# stop-loss: 10%, ROI: 4%, stoploss adjusted candle 2
+tc23 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 0, 0, 1, 0],
+    [1, 5000, 5050, 4900, 4900, 6172, 0, 0, 0, 0],
+    [2, 4900, 4900, 4749, 4900, 6172, 0, 0, 0, 0],
+    [3, 4850, 5050, 4650, 4750, 6172, 0, 0, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.04}, profit_perc=0.04, trailing_stop=True,
+    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
+    trailing_stop_positive=0.03,
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=2, is_short=True)]
+)
+
+# Test 24: trailing_stop Raises in candle 2 (does not trigger)
 # applying a positive trailing stop of 3% since stop_positive_offset is reached.
 # ROI is changed after this to 4%, dropping ROI below trailing_stop_positive, causing a sell
 # in the candle after the raised stoploss candle with ROI reason.
 # Stoploss would trigger in this candle too, but it's no longer relevant.
 # stop-loss: 10%, ROI: 4%, stoploss adjusted candle 2, ROI adjusted in candle 3 (causing the sell)
-tc23 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+tc24 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [1, 5000, 5100, 4950, 5100, 6172, 0, 0],
     [2, 5100, 5251, 5100, 5100, 6172, 0, 0],
     [3, 4850, 5251, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.1, "119": 0.03}, profit_perc=0.03, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
     trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
-)
-
-# Test 24: Sell with signal sell in candle 3 (stoploss also triggers on this candle)
-# Stoploss at 1%.
-# Stoploss wins over Sell-signal (because sell-signal is acted on in the next candle)
-tc24 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
-    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5012, 4986, 4600, 6172, 0, 0],
-    [3, 5010, 5000, 4855, 5010, 6172, 0, 1],  # Triggers stoploss + sellsignal
-    [4, 5010, 4987, 4977, 4995, 6172, 0, 0],
-    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
-    stop_loss=-0.01, roi={"0": 1}, profit_perc=-0.01, use_sell_signal=True,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=3)]
 )
 
 # Test 25: Sell with signal sell in candle 3 (stoploss also triggers on this candle)
 # Stoploss at 1%.
-# Sell-signal wins over stoploss
+# Stoploss wins over Sell-signal (because sell-signal is acted on in the next candle)
 tc25 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5012, 4986, 4600, 6172, 0, 0],
-    [3, 5010, 5000, 4986, 5010, 6172, 0, 1],
-    [4, 5010, 4987, 4855, 4995, 6172, 0, 0],  # Triggers stoploss + sellsignal acted on
-    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
-    stop_loss=-0.01, roi={"0": 1}, profit_perc=0.002, use_sell_signal=True,
-    trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=4)]
+    [2, 4987, 5012, 4986, 4986, 6172, 0, 0],
+    [3, 5010, 5010, 4855, 5010, 6172, 0, 1],  # Triggers stoploss + sellsignal
+    [4, 5010, 5010, 4977, 4995, 6172, 0, 0],
+    [5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
+    stop_loss=-0.01, roi={"0": 1}, profit_perc=-0.01, use_exit_signal=True,
+    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=3)]
 )
 
-# Test 26: Sell with signal sell in candle 3 (ROI at signal candle)
-# Stoploss at 10% (irrelevant), ROI at 5% (will trigger)
+# Test 26: Sell with signal sell in candle 3 (stoploss also triggers on this candle)
+# Stoploss at 1%.
 # Sell-signal wins over stoploss
 tc26 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5012, 4986, 4600, 6172, 0, 0],
-    [3, 5010, 5251, 4986, 5010, 6172, 0, 1],  # Triggers ROI, sell-signal
-    [4, 5010, 4987, 4855, 4995, 6172, 0, 0],
-    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
-    stop_loss=-0.10, roi={"0": 0.05}, profit_perc=0.05, use_sell_signal=True,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+    [2, 4987, 5012, 4986, 4986, 6172, 0, 0],
+    [3, 5010, 5010, 4986, 5010, 6172, 0, 1],
+    [4, 5010, 5010, 4855, 4995, 6172, 0, 0],  # Triggers stoploss + sellsignal acted on
+    [5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
+    stop_loss=-0.01, roi={"0": 1}, profit_perc=0.002, use_exit_signal=True,
+    trades=[BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=4)]
 )
 
-# Test 27: Sell with signal sell in candle 3 (ROI at signal candle)
-# Stoploss at 10% (irrelevant), ROI at 5% (will trigger) - Wins over Sell-signal
-# TODO: figure out if sell-signal should win over ROI
+# Test 27: (copy of test26 with leverage)
+# Sell with signal sell in candle 3 (stoploss also triggers on this candle)
+# Stoploss at 1%.
 # Sell-signal wins over stoploss
 tc27 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5012, 4986, 4600, 6172, 0, 0],
-    [3, 5010, 5012, 4986, 5010, 6172, 0, 1],  # sell-signal
-    [4, 5010, 5251, 4855, 4995, 6172, 0, 0],  # Triggers ROI, sell-signal acted on
-    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
-    stop_loss=-0.10, roi={"0": 0.05}, profit_perc=0.05, use_sell_signal=True,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=4)]
+    [2, 4987, 5012, 4986, 4986, 6172, 0, 0],
+    [3, 5010, 5010, 4986, 5010, 6172, 0, 1],
+    [4, 5010, 5010, 4855, 4995, 6172, 0, 0],  # Triggers stoploss + sellsignal acted on
+    [5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
+    stop_loss=-0.05, roi={"0": 1}, profit_perc=0.002 * 5.0, use_exit_signal=True,
+    leverage=5.0,
+    trades=[BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=4)]
 )
 
-# Test 28: trailing_stop should raise so candle 3 causes a stoploss
+# Test 28: (copy of test26 with leverage and as short)
+# Sell with signal sell in candle 3 (stoploss also triggers on this candle)
+# Stoploss at 1%.
+# Sell-signal wins over stoploss
+tc28 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5025, 4975, 4987, 6172, 0, 0, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5012, 4986, 4986, 6172, 0, 0, 0, 0],
+    [3, 5010, 5010, 4986, 5010, 6172, 0, 0, 0, 1],
+    [4, 4990, 5010, 4855, 4995, 6172, 0, 0, 0, 0],  # Triggers stoploss + sellsignal acted on
+    [5, 4995, 4995, 4950, 4950, 6172, 0, 0, 0, 0]],
+    stop_loss=-0.05, roi={"0": 1}, profit_perc=0.002 * 5.0, use_exit_signal=True,
+    leverage=5.0,
+    trades=[BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=4, is_short=True)]
+)
+# Test 29: Sell with signal sell in candle 3 (ROI at signal candle)
+# Stoploss at 10% (irrelevant), ROI at 5% (will trigger)
+# Sell-signal wins over stoploss
+tc29 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5012, 4986, 4986, 6172, 0, 0],
+    [3, 5010, 5251, 4986, 5010, 6172, 0, 1],  # Triggers ROI, sell-signal
+    [4, 5010, 5010, 4855, 4995, 6172, 0, 0],
+    [5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.05}, profit_perc=0.05, use_exit_signal=True,
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=3)]
+)
+
+# Test 30: Sell with signal sell in candle 3 (ROI at signal candle)
+# Stoploss at 10% (irrelevant), ROI at 5% (will trigger) - Wins over Sell-signal
+tc30 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5012, 4986, 4986, 6172, 0, 0],
+    [3, 5010, 5012, 4986, 5010, 6172, 0, 1],  # sell-signal
+    [4, 5010, 5251, 4855, 4995, 6172, 0, 0],  # Triggers ROI, sell-signal acted on
+    [5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.05}, profit_perc=0.002, use_exit_signal=True,
+    trades=[BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=4)]
+)
+
+# Test 31: trailing_stop should raise so candle 3 causes a stoploss
 # Same case than tc11 - but candle 3 "gaps down" - the stoploss will be above the candle,
 # therefore "open" will be used
 # stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2
-tc28 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+tc31 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [1, 5000, 5100, 4950, 5100, 6172, 0, 0],
     [2, 5100, 5251, 5100, 5100, 6172, 0, 0],
     [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.03, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
     trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
+    trades=[BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
 )
 
-# Test 29: trailing_stop should be triggered by low of next candle, without adjusting stoploss using
+# Test 32: (Short of test 31) trailing_stop should raise so candle 3 causes a stoploss
+# Same case than tc11 - but candle 3 "gaps down" - the stoploss will be above the candle,
+# therefore "open" will be used
+# stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2
+tc32 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 0, 0, 1, 0],
+    [1, 5000, 5050, 4890, 4890, 6172, 0, 0, 0, 0],
+    [2, 4890, 4890, 4749, 4890, 6172, 0, 0, 0, 0],
+    [3, 5150, 5350, 4950, 4950, 6172, 0, 0, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.03, trailing_stop=True,
+    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
+    trailing_stop_positive=0.03,
+    trades=[
+        BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3, is_short=True)
+    ]
+)
+
+# Test 33: trailing_stop should be triggered by low of next candle, without adjusting stoploss using
 # high of stoploss candle.
 # stop-loss: 10%, ROI: 10% (should not apply)
-tc29 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+tc33 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 5000, 4900, 6172, 0, 0],    # enter trade (signal on last candle)
+    [1, 5000, 5050, 5000, 5000, 6172, 0, 0],    # enter trade (signal on last candle)
     [2, 4900, 5250, 4500, 5100, 6172, 0, 0],    # Triggers trailing-stoploss
     [3, 5100, 5100, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.02, trailing_stop=True,
     trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=2)]
+    trades=[BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=2)]
 )
 
-# Test 30: trailing_stop should be triggered immediately on trade open candle.
+# Test 34: trailing_stop should be triggered immediately on trade open candle.
 # stop-loss: 10%, ROI: 10% (should not apply)
-tc30 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+tc34 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5500, 5000, 4900, 6172, 0, 0],    # enter trade (signal on last candle) and stop
+    [1, 5000, 5500, 4900, 4900, 6172, 0, 0],    # enter trade (signal on last candle) and stop
     [2, 4900, 5250, 4500, 5100, 6172, 0, 0],
     [3, 5100, 5100, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.01, trailing_stop=True,
     trailing_stop_positive=0.01,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=1)]
+    trades=[BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
-# Test 31: trailing_stop should be triggered immediately on trade open candle.
+# Test 35: trailing_stop should be triggered immediately on trade open candle.
 # stop-loss: 10%, ROI: 10% (should not apply)
-tc31 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+tc35 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5500, 5000, 4900, 6172, 0, 0],    # enter trade (signal on last candle) and stop
+    [1, 5000, 5500, 4900, 4900, 6172, 0, 0],    # enter trade (signal on last candle) and stop
     [2, 4900, 5250, 4500, 5100, 6172, 0, 0],
     [3, 5100, 5100, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.01, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.02,
     trailing_stop_positive=0.01,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=1)]
+    trades=[BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
-# Test 32: trailing_stop should be triggered immediately on trade open candle.
+# Test 36: trailing_stop should be triggered immediately on trade open candle.
 # stop-loss: 1%, ROI: 10% (should not apply)
-tc32 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
+tc36 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
     [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5500, 5000, 4900, 6172, 0, 0],    # enter trade (signal on last candle) and stop
+    [1, 5000, 5500, 4951, 5000, 6172, 0, 0],    # enter trade and stop
     [2, 4900, 5250, 4500, 5100, 6172, 0, 0],
     [3, 5100, 5100, 4650, 4750, 6172, 0, 0],
     [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
     stop_loss=-0.01, roi={"0": 0.10}, profit_perc=-0.01, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.02,
     trailing_stop_positive=0.01, use_custom_stoploss=True,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=1)]
+    trades=[BTrade(exit_reason=ExitType.TRAILING_STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
-# Test 33: trailing_stop should be triggered immediately on trade open candle.
+# Test 37: trailing_stop should be triggered immediately on trade open candle.
 # stop-loss: 1%, ROI: 10% (should not apply)
-tc33 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S   BT
-    [0, 5000, 5050, 4950, 5000, 6172, 1, 0, 'buy_signal_01'],
-    [1, 5000, 5500, 5000, 4900, 6172, 0, 0, None],    # enter trade (signal on last candle) and stop
-    [2, 4900, 5250, 4500, 5100, 6172, 0, 0, None],
-    [3, 5100, 5100, 4650, 4750, 6172, 0, 0, None],
-    [4, 4750, 4950, 4350, 4750, 6172, 0, 0, None]],
+tc37 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0, 0, 0, 'buy_signal_01'],
+    [1, 5000, 5500, 4951, 5000, 6172, 0, 0, 0, 0, None],    # enter trade and stop
+    [2, 4900, 5250, 4500, 5100, 6172, 0, 0, 0, 0, None],
+    [3, 5100, 5100, 4650, 4750, 6172, 0, 0, 0, 0, None],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0, 0, 0, None]],
     stop_loss=-0.01, roi={"0": 0.10}, profit_perc=-0.01, trailing_stop=True,
     trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.02,
     trailing_stop_positive=0.01, use_custom_stoploss=True,
     trades=[BTrade(
-        sell_reason=SellType.TRAILING_STOP_LOSS,
+        exit_reason=ExitType.TRAILING_STOP_LOSS,
         open_tick=1,
         close_tick=1,
-        buy_tag='buy_signal_01'
+        enter_tag='buy_signal_01'
     )]
 )
+# Test 38: trailing_stop should be triggered immediately on trade open candle.
+# copy of Test37 using shorts.
+# stop-loss: 1%, ROI: 10% (should not apply)
+tc38 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 0, 0, 1, 0, 'short_signal_01'],
+    [1, 5000, 5049, 4500, 5000, 6172, 0, 0, 0, 0, None],    # enter trade and stop
+    [2, 4900, 5250, 4500, 5100, 6172, 0, 0, 0, 0, None],
+    [3, 5100, 5100, 4650, 4750, 6172, 0, 0, 0, 0, None],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0, 0, 0, None]],
+    stop_loss=-0.01, roi={"0": 0.10}, profit_perc=-0.01, trailing_stop=True,
+    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.02,
+    trailing_stop_positive=0.01, use_custom_stoploss=True,
+    trades=[BTrade(
+        exit_reason=ExitType.TRAILING_STOP_LOSS,
+        open_tick=1,
+        close_tick=1,
+        enter_tag='short_signal_01',
+        is_short=True,
+    )]
+)
+
+# Test 39: Custom-entry-price below all candles should timeout - so no trade happens.
+tc39 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5500, 4951, 5000, 6172, 0, 0],    # timeout
+    [2, 4900, 5250, 4500, 5100, 6172, 0, 0],
+    [3, 5100, 5100, 4650, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.01, roi={"0": 0.10}, profit_perc=0.0,
+    custom_entry_price=4200, trades=[]
+)
+
+# Test 40: Custom-entry-price above all candles should have rate adjusted to "entry candle high"
+tc40 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5500, 4951, 5000, 6172, 0, 0],    # Timeout
+    [2, 4900, 5250, 4500, 5100, 6172, 0, 0],
+    [3, 5100, 5100, 4650, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.01, roi={"0": 0.10}, profit_perc=-0.01,
+    custom_entry_price=7200, trades=[
+        BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)
+])
+
+# Test 41: Custom-entry-price above all candles should have rate adjusted to "entry candle high"
+tc41 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 0, 0, 1, 0],
+    [1, 5000, 5500, 4951, 5000, 6172, 0, 0, 0, 0],    # Timeout
+    [2, 4900, 5250, 4500, 5100, 6172, 0, 0, 0, 0],
+    [3, 5100, 5100, 4650, 4750, 6172, 0, 0, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0, 0, 0]],
+    stop_loss=-0.01, roi={"0": 0.10}, profit_perc=-0.01,
+    custom_entry_price=4000,
+    trades=[
+        BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1, is_short=True)
+    ]
+)
+
+# Test 42: Custom-entry-price around candle low
+# Would cause immediate ROI exit, but since the trade was entered
+# below open, we treat this as cheating, and delay the sell by 1 candle.
+# details: https://github.com/freqtrade/freqtrade/issues/6261
+tc42 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5500, 4951, 4999, 6172, 0, 0],    # Enter and immediate ROI
+    [2, 4900, 5250, 4500, 5100, 6172, 0, 0],
+    [3, 5100, 5100, 4650, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.01}, profit_perc=0.01,
+    custom_entry_price=4952,
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=2)]
+)
+
+# Test 43: Custom-entry-price around candle low
+# Would cause immediate ROI exit below close
+# details: https://github.com/freqtrade/freqtrade/issues/6261
+tc43 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5400, 5500, 4951, 5100, 6172, 0, 0],    # Enter and immediate ROI
+    [2, 4900, 5250, 4500, 5100, 6172, 0, 0],
+    [3, 5100, 5100, 4650, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.01}, profit_perc=0.01,
+    custom_entry_price=4952,
+    trades=[BTrade(exit_reason=ExitType.ROI, open_tick=1, close_tick=1)]
+)
+
+# Test 44: Custom exit price below all candles
+# Price adjusted to candle Low.
+tc44 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5500, 4951, 5000, 6172, 0, 0],
+    [2, 4900, 5250, 4900, 5100, 6172, 0, 1],  # exit - but timeout
+    [3, 5100, 5100, 4950, 4950, 6172, 0, 0],
+    [4, 5000, 5100, 4950, 4950, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.01,
+    use_exit_signal=True,
+    custom_exit_price=4552,
+    trades=[BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=3)]
+)
+
+# Test 45: Custom exit price above all candles
+# causes sell signal timeout
+tc45 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5500, 4951, 5000, 6172, 0, 0],
+    [2, 4950, 5250, 4900, 5100, 6172, 0, 1],  # exit - entry timeout
+    [3, 5100, 5100, 4950, 4950, 6172, 0, 0],
+    [4, 5000, 5100, 4950, 4950, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.0,
+    use_exit_signal=True,
+    custom_exit_price=6052,
+    trades=[BTrade(exit_reason=ExitType.FORCE_EXIT, open_tick=1, close_tick=4)]
+)
+
+# Test 46: (Short of tc45) Custom short exit price above below candles
+# causes sell signal timeout
+tc46 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 0, 0, 1, 0],
+    [1, 5000, 5000, 4951, 5000, 6172, 0, 0, 0, 0],
+    [2, 4910, 5150, 4910, 5100, 6172, 0, 0, 0, 1],  # exit - entry timeout
+    [3, 5100, 5100, 4950, 4950, 6172, 0, 0, 0, 0],
+    [4, 5000, 5100, 4950, 4950, 6172, 0, 0, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.0,
+    use_exit_signal=True,
+    custom_exit_price=4700,
+    trades=[BTrade(exit_reason=ExitType.FORCE_EXIT, open_tick=1, close_tick=4, is_short=True)]
+)
+
+# Test 47: Colliding long and short signal
+tc47 = BTContainer(data=[
+    # D   O     H     L     C    V    EL XL ES Xs  BT
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0, 1, 0],
+    [1, 5000, 5500, 4951, 5000, 6172, 0, 0, 0, 0],
+    [2, 4900, 5250, 4900, 5100, 6172, 0, 0, 0, 0],
+    [3, 5100, 5100, 4950, 4950, 6172, 0, 0, 0, 0],
+    [4, 5000, 5100, 4950, 4950, 6172, 0, 0, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.0,
+    use_exit_signal=True,
+    trades=[]
+)
+
 
 TESTS = [
     tc0,
@@ -571,11 +790,25 @@ TESTS = [
     tc31,
     tc32,
     tc33,
+    tc34,
+    tc35,
+    tc36,
+    tc37,
+    tc38,
+    tc39,
+    tc40,
+    tc41,
+    tc42,
+    tc43,
+    tc44,
+    tc45,
+    tc46,
+    tc47,
 ]
 
 
 @pytest.mark.parametrize("data", TESTS)
-def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
+def test_backtest_results(default_conf, fee, mocker, caplog, data: BTContainer) -> None:
     """
     run functional tests
     """
@@ -588,18 +821,27 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
     if data.trailing_stop_positive is not None:
         default_conf["trailing_stop_positive"] = data.trailing_stop_positive
     default_conf["trailing_stop_positive_offset"] = data.trailing_stop_positive_offset
-    default_conf["use_sell_signal"] = data.use_sell_signal
+    default_conf["use_exit_signal"] = data.use_exit_signal
 
     mocker.patch("freqtrade.exchange.Exchange.get_fee", return_value=0.0)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
+    mocker.patch("freqtrade.exchange.Binance.get_max_leverage", return_value=100)
     patch_exchange(mocker)
     frame = _build_backtest_dataframe(data.data)
     backtesting = Backtesting(default_conf)
+    # TODO: Should we initialize this properly??
+    backtesting._can_short = True
     backtesting._set_strategy(backtesting.strategylist[0])
     backtesting.required_startup = 0
-    backtesting.strategy.advise_buy = lambda a, m: frame
-    backtesting.strategy.advise_sell = lambda a, m: frame
+    backtesting.strategy.advise_entry = lambda a, m: frame
+    backtesting.strategy.advise_exit = lambda a, m: frame
+    if data.custom_entry_price:
+        backtesting.strategy.custom_entry_price = MagicMock(return_value=data.custom_entry_price)
+    if data.custom_exit_price:
+        backtesting.strategy.custom_exit_price = MagicMock(return_value=data.custom_exit_price)
     backtesting.strategy.use_custom_stoploss = data.use_custom_stoploss
+    backtesting.strategy.leverage = lambda **kwargs: data.leverage
     caplog.set_level(logging.DEBUG)
 
     pair = "UNITTEST/BTC"
@@ -618,8 +860,9 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
     assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3)
 
     for c, trade in enumerate(data.trades):
-        res = results.iloc[c]
-        assert res.sell_reason == trade.sell_reason.value
-        assert res.buy_tag == trade.buy_tag
+        res: BTrade = results.iloc[c]
+        assert res.exit_reason == trade.exit_reason.value
+        assert res.enter_tag == trade.enter_tag
         assert res.open_date == _get_frame_time_from_offset(trade.open_tick)
         assert res.close_date == _get_frame_time_from_offset(trade.close_tick)
+        assert res.is_short == trade.is_short
diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py
index 2248cd4c1..08957acf9 100644
--- a/tests/optimize/test_backtesting.py
+++ b/tests/optimize/test_backtesting.py
@@ -1,6 +1,7 @@
 # pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
 
 import random
+from copy import deepcopy
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from unittest.mock import MagicMock, PropertyMock
@@ -10,6 +11,7 @@ import pandas as pd
 import pytest
 from arrow import Arrow
 
+from freqtrade import constants
 from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_backtesting
 from freqtrade.configuration import TimeRange
 from freqtrade.data import history
@@ -17,25 +19,27 @@ from freqtrade.data.btanalysis import BT_DATA_COLUMNS, evaluate_result_multi
 from freqtrade.data.converter import clean_ohlcv_dataframe
 from freqtrade.data.dataprovider import DataProvider
 from freqtrade.data.history import get_timerange
-from freqtrade.enums import RunMode, SellType
+from freqtrade.enums import ExitType, RunMode
 from freqtrade.exceptions import DependencyException, OperationalException
+from freqtrade.exchange.exchange import timeframe_to_next_date
+from freqtrade.misc import get_strategy_run_id
 from freqtrade.optimize.backtesting import Backtesting
 from freqtrade.persistence import LocalTrade
 from freqtrade.resolvers import StrategyResolver
-from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
+from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, log_has, log_has_re, patch_exchange,
                             patched_configuration_load_config_file)
 
 
 ORDER_TYPES = [
     {
-        'buy': 'limit',
-        'sell': 'limit',
+        'entry': 'limit',
+        'exit': 'limit',
         'stoploss': 'limit',
         'stoploss_on_exchange': False
     },
     {
-        'buy': 'limit',
-        'sell': 'limit',
+        'entry': 'limit',
+        'exit': 'limit',
         'stoploss': 'limit',
         'stoploss_on_exchange': True
     }]
@@ -48,6 +52,13 @@ def trim_dictlist(dict_list, num):
     return new
 
 
+@pytest.fixture(autouse=True)
+def backtesting_cleanup() -> None:
+    yield None
+
+    Backtesting.cleanup()
+
+
 def load_data_test(what, testdatadir):
     timerange = TimeRange.parse_timerange('1510694220-1510700340')
     data = history.load_pair_history(pair='UNITTEST/BTC', datadir=testdatadir,
@@ -123,12 +134,14 @@ def _trend(signals, buy_value, sell_value):
     n = len(signals['low'])
     buy = np.zeros(n)
     sell = np.zeros(n)
-    for i in range(0, len(signals['buy'])):
+    for i in range(0, len(signals['date'])):
         if random.random() > 0.5:  # Both buy and sell signals at same timeframe
             buy[i] = buy_value
             sell[i] = sell_value
-    signals['buy'] = buy
-    signals['sell'] = sell
+    signals['enter_long'] = buy
+    signals['exit_long'] = sell
+    signals['enter_short'] = 0
+    signals['exit_short'] = 0
     return signals
 
 
@@ -143,8 +156,10 @@ def _trend_alternate(dataframe=None, metadata=None):
             buy[i] = 1
         else:
             sell[i] = 1
-    signals['buy'] = buy
-    signals['sell'] = sell
+    signals['enter_long'] = buy
+    signals['exit_long'] = sell
+    signals['enter_short'] = 0
+    signals['exit_short'] = 0
     return dataframe
 
 
@@ -155,7 +170,7 @@ def test_setup_optimize_configuration_without_arguments(mocker, default_conf, ca
     args = [
         'backtesting',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
         '--export', 'none'
     ]
 
@@ -190,7 +205,7 @@ def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) ->
     args = [
         'backtesting',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
         '--datadir', '/foo/bar',
         '--timeframe', '1m',
         '--enable-position-stacking',
@@ -240,7 +255,7 @@ def test_setup_optimize_configuration_stake_amount(mocker, default_conf, caplog)
     args = [
         'backtesting',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
         '--stake-amount', '1',
         '--starting-balance', '2'
     ]
@@ -251,7 +266,7 @@ def test_setup_optimize_configuration_stake_amount(mocker, default_conf, caplog)
     args = [
         'backtesting',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
         '--stake-amount', '1',
         '--starting-balance', '0.5'
     ]
@@ -269,7 +284,7 @@ def test_start(mocker, fee, default_conf, caplog) -> None:
     args = [
         'backtesting',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
     ]
     pargs = get_args(args)
     start_backtesting(pargs)
@@ -291,8 +306,8 @@ def test_backtesting_init(mocker, default_conf, order_types) -> None:
     assert backtesting.config == default_conf
     assert backtesting.timeframe == '5m'
     assert callable(backtesting.strategy.advise_all_indicators)
-    assert callable(backtesting.strategy.advise_buy)
-    assert callable(backtesting.strategy.advise_sell)
+    assert callable(backtesting.strategy.advise_entry)
+    assert callable(backtesting.strategy.advise_exit)
     assert isinstance(backtesting.strategy.dp, DataProvider)
     get_fee.assert_called()
     assert backtesting.fee == 0.5
@@ -302,17 +317,16 @@ def test_backtesting_init(mocker, default_conf, order_types) -> None:
 def test_backtesting_init_no_timeframe(mocker, default_conf, caplog) -> None:
     patch_exchange(mocker)
     del default_conf['timeframe']
-    default_conf['strategy_list'] = ['StrategyTestV2',
-                                     'SampleStrategy']
+    default_conf['strategy_list'] = [CURRENT_TEST_STRATEGY,
+                                     'HyperoptableStrategy']
 
     mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
-    with pytest.raises(OperationalException):
+    with pytest.raises(OperationalException,
+                       match=r"Timeframe needs to be set in either configuration"):
         Backtesting(default_conf)
-    log_has("Ticker-interval needs to be set in either configuration "
-            "or as cli argument `--ticker-interval 5m`", caplog)
 
 
-def test_data_with_fee(default_conf, mocker, testdatadir) -> None:
+def test_data_with_fee(default_conf, mocker) -> None:
     patch_exchange(mocker)
     default_conf['fee'] = 0.1234
 
@@ -340,7 +354,6 @@ def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
     assert len(processed['UNITTEST/BTC']) == 102
 
     # Load strategy to compare the result between Backtesting function and strategy are the same
-    default_conf.update({'strategy': 'StrategyTestV2'})
     strategy = StrategyResolver.load_strategy(default_conf)
 
     processed2 = strategy.advise_all_indicators(data)
@@ -438,7 +451,8 @@ def test_backtesting_no_pair_left(default_conf, mocker, caplog, testdatadir) ->
         Backtesting(default_conf)
 
     default_conf['pairlists'] = [{"method": "VolumePairList", "number_assets": 5}]
-    with pytest.raises(OperationalException, match='VolumePairList not allowed for backtesting.'):
+    with pytest.raises(OperationalException,
+                       match=r'VolumePairList not allowed for backtesting\..*StaticPairlist.*'):
         Backtesting(default_conf)
 
     default_conf.update({
@@ -470,7 +484,8 @@ def test_backtesting_pairlist_list(default_conf, mocker, caplog, testdatadir, ti
     default_conf['timerange'] = '20180101-20180102'
 
     default_conf['pairlists'] = [{"method": "VolumePairList", "number_assets": 5}]
-    with pytest.raises(OperationalException, match='VolumePairList not allowed for backtesting.'):
+    with pytest.raises(OperationalException,
+                       match=r'VolumePairList not allowed for backtesting\..*StaticPairlist.*'):
         Backtesting(default_conf)
 
     default_conf['pairlists'] = [{"method": "StaticPairList"}, {"method": "PerformanceFilter"}]
@@ -482,16 +497,17 @@ def test_backtesting_pairlist_list(default_conf, mocker, caplog, testdatadir, ti
     Backtesting(default_conf)
 
     # Multiple strategies
-    default_conf['strategy_list'] = ['StrategyTestV2', 'TestStrategyLegacyV1']
+    default_conf['strategy_list'] = [CURRENT_TEST_STRATEGY, 'TestStrategyLegacyV1']
     with pytest.raises(OperationalException,
                        match='PrecisionFilter not allowed for backtesting multiple strategies.'):
         Backtesting(default_conf)
 
 
 def test_backtest__enter_trade(default_conf, fee, mocker) -> None:
-    default_conf['use_sell_signal'] = False
+    default_conf['use_exit_signal'] = False
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
     patch_exchange(mocker)
     default_conf['stake_amount'] = 'unlimited'
     default_conf['max_open_trades'] = 2
@@ -508,50 +524,131 @@ def test_backtest__enter_trade(default_conf, fee, mocker) -> None:
         0.0012,  # High
         '',  # Buy Signal Name
     ]
-    trade = backtesting._enter_trade(pair, row=row)
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
     assert isinstance(trade, LocalTrade)
     assert trade.stake_amount == 495
 
     # Fake 2 trades, so there's not enough amount for the next trade left.
     LocalTrade.trades_open.append(trade)
     LocalTrade.trades_open.append(trade)
-    trade = backtesting._enter_trade(pair, row=row)
+    backtesting.wallets.update()
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
     assert trade is None
     LocalTrade.trades_open.pop()
-    trade = backtesting._enter_trade(pair, row=row)
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
     assert trade is not None
 
     backtesting.strategy.custom_stake_amount = lambda **kwargs: 123.5
-    trade = backtesting._enter_trade(pair, row=row)
+    backtesting.wallets.update()
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
     assert trade
     assert trade.stake_amount == 123.5
 
     # In case of error - use proposed stake
     backtesting.strategy.custom_stake_amount = lambda **kwargs: 20 / 0
-    trade = backtesting._enter_trade(pair, row=row)
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
     assert trade
     assert trade.stake_amount == 495
+    assert trade.is_short is False
+
+    trade = backtesting._enter_trade(pair, row=row, direction='short')
+    assert trade
+    assert trade.stake_amount == 495
+    assert trade.is_short is True
+
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=300.0)
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
+    assert trade
+    assert trade.stake_amount == 300.0
+
+
+def test_backtest__enter_trade_futures(default_conf_usdt, fee, mocker) -> None:
+    default_conf_usdt['use_exit_signal'] = False
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
+    mocker.patch("freqtrade.exchange.Exchange.get_max_leverage", return_value=100)
+    patch_exchange(mocker)
+    default_conf_usdt['stake_amount'] = 300
+    default_conf_usdt['max_open_trades'] = 2
+    default_conf_usdt['trading_mode'] = 'futures'
+    default_conf_usdt['margin_mode'] = 'isolated'
+    default_conf_usdt['stake_currency'] = 'USDT'
+    default_conf_usdt['exchange']['pair_whitelist'] = ['.*']
+    backtesting = Backtesting(default_conf_usdt)
+    backtesting._set_strategy(backtesting.strategylist[0])
+    pair = 'UNITTEST/USDT:USDT'
+    row = [
+        pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0),
+        0.001,  # Open
+        0.0012,  # High
+        0.00099,  # Low
+        0.0011,  # Close
+        1,  # enter_long
+        0,  # exit_long
+        1,  # enter_short
+        0,  # exit_hsort
+        '',  # Long Signal Name
+        '',  # Short Signal Name
+        '',  # Exit Signal Name
+    ]
+
+    backtesting.strategy.leverage = MagicMock(return_value=5.0)
+    mocker.patch("freqtrade.exchange.Exchange.get_maintenance_ratio_and_amt",
+                 return_value=(0.01, 0.01))
+
+    # leverage = 5
+    # ep1(trade.open_rate) = 0.001
+    # position(trade.amount) = 1500000
+    # stake_amount = 300 -> wb = 300 / 5 = 60
+    # mmr = 0.01
+    # cum_b = 0.01
+    # side_1: -1 if is_short else 1
+    # liq_buffer = 0.05
+    #
+    # Binance, Long
+    # liquidation_price
+    #   = ((wb + cum_b) - (side_1 * position * ep1)) / ((position * mmr_b) - (side_1 * position))
+    #   = ((300 + 0.01) - (1 * 1500000 * 0.001)) / ((1500000 * 0.01) - (1 * 1500000))
+    #   = 0.0008080740740740741
+    # freqtrade_liquidation_price = liq + (abs(open_rate - liq) * liq_buffer * side_1)
+    #   = 0.0008080740740740741 + ((0.001 - 0.0008080740740740741) * 0.05 * 1)
+    #   = 0.0008176703703703704
+
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
+    assert pytest.approx(trade.liquidation_price) == 0.00081767037
+
+    # Binance, Short
+    # liquidation_price
+    #   = ((wb + cum_b) - (side_1 * position * ep1)) / ((position * mmr_b) - (side_1 * position))
+    #   = ((300 + 0.01) - ((-1) * 1500000 * 0.001)) / ((1500000 * 0.01) - ((-1) * 1500000))
+    #   = 0.0011881254125412541
+    # freqtrade_liquidation_price = liq + (abs(open_rate - liq) * liq_buffer * side_1)
+    #   = 0.0011881254125412541 + (abs(0.001 - 0.0011881254125412541) * 0.05 * -1)
+    #   = 0.0011787191419141915
+
+    trade = backtesting._enter_trade(pair, row=row, direction='short')
+    assert pytest.approx(trade.liquidation_price) == 0.0011787191
 
     # Stake-amount too high!
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=600.0)
 
-    trade = backtesting._enter_trade(pair, row=row)
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
     assert trade is None
 
     # Stake-amount throwing error
     mocker.patch("freqtrade.wallets.Wallets.get_trade_stake_amount",
                  side_effect=DependencyException)
 
-    trade = backtesting._enter_trade(pair, row=row)
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
     assert trade is None
 
-    backtesting.cleanup()
-
 
 def test_backtest__get_sell_trade_entry(default_conf, fee, mocker) -> None:
-    default_conf['use_sell_signal'] = False
+    default_conf['use_exit_signal'] = False
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
     patch_exchange(mocker)
     default_conf['timeframe_detail'] = '1m'
     default_conf['max_open_trades'] = 2
@@ -560,61 +657,72 @@ def test_backtest__get_sell_trade_entry(default_conf, fee, mocker) -> None:
     pair = 'UNITTEST/BTC'
     row = [
         pd.Timestamp(year=2020, month=1, day=1, hour=4, minute=55, tzinfo=timezone.utc),
-        1,  # Buy
         200,  # Open
-        201,  # Close
-        0,  # Sell
-        195,  # Low
         201.5,  # High
-        '',  # Buy Signal Name
+        195,  # Low
+        201,  # Close
+        1,  # enter_long
+        0,  # exit_long
+        0,  # enter_short
+        0,  # exit_hsort
+        '',  # Long Signal Name
+        '',  # Short Signal Name
+        '',  # Exit Signal Name
     ]
 
-    trade = backtesting._enter_trade(pair, row=row)
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
     assert isinstance(trade, LocalTrade)
 
     row_sell = [
         pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0, tzinfo=timezone.utc),
-        0,  # Buy
         200,  # Open
-        201,  # Close
-        0,  # Sell
-        195,  # Low
         210.5,  # High
-        '',  # Buy Signal Name
+        195,  # Low
+        201,  # Close
+        0,  # enter_long
+        0,  # exit_long
+        0,  # enter_short
+        0,  # exit_short
+        '',  # long Signal Name
+        '',  # Short Signal Name
+        '',  # Exit Signal Name
+
     ]
     row_detail = pd.DataFrame(
         [
             [
                 pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0, tzinfo=timezone.utc),
-                1, 200, 199, 0, 197, 200.1, '',
+                200, 200.1, 197, 199, 1, 0, 0, 0, '', '', '',
             ], [
                 pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=1, tzinfo=timezone.utc),
-                0, 199, 199.5, 0, 199, 199.7, '',
+                199, 199.7, 199, 199.5, 0, 0, 0, 0, '', '', '',
             ], [
                 pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=2, tzinfo=timezone.utc),
-                0, 199.5, 200.5, 0, 199, 200.8, '',
+                199.5, 200.8, 199, 200.9, 0, 0, 0, 0, '', '', '',
             ], [
                 pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=3, tzinfo=timezone.utc),
-                0, 200.5, 210.5, 0, 193, 210.5, '',  # ROI sell (?)
+                200.5, 210.5, 193, 210.5, 0, 0, 0, 0, '', '', '',  # ROI sell (?)
             ], [
                 pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=4, tzinfo=timezone.utc),
-                0, 200, 199, 0, 193, 200.1, '',
+                200, 200.1, 193, 199, 0, 0, 0, 0, '', '', '',
             ],
-        ], columns=["date", "buy", "open", "close", "sell", "low", "high", "buy_tag"]
+        ], columns=['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
+                    'enter_short', 'exit_short', 'long_tag', 'short_tag', 'exit_tag']
     )
 
     # No data available.
     res = backtesting._get_sell_trade_entry(trade, row_sell)
     assert res is not None
-    assert res.sell_reason == SellType.ROI.value
+    assert res.exit_reason == ExitType.ROI.value
     assert res.close_date_utc == datetime(2020, 1, 1, 5, 0, tzinfo=timezone.utc)
 
     # Enter new trade
-    trade = backtesting._enter_trade(pair, row=row)
+    trade = backtesting._enter_trade(pair, row=row, direction='long')
     assert isinstance(trade, LocalTrade)
     # Assign empty ... no result.
     backtesting.detail_data[pair] = pd.DataFrame(
-        [], columns=["date", "buy", "open", "close", "sell", "low", "high", "buy_tag"])
+        [], columns=['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
+                     'enter_short', 'exit_short', 'long_tag', 'short_tag', 'exit_tag'])
 
     res = backtesting._get_sell_trade_entry(trade, row)
     assert res is None
@@ -624,16 +732,18 @@ def test_backtest__get_sell_trade_entry(default_conf, fee, mocker) -> None:
 
     res = backtesting._get_sell_trade_entry(trade, row_sell)
     assert res is not None
-    assert res.sell_reason == SellType.ROI.value
+    assert res.exit_reason == ExitType.ROI.value
     # Sell at minute 3 (not available above!)
     assert res.close_date_utc == datetime(2020, 1, 1, 5, 3, tzinfo=timezone.utc)
-    assert round(res.close_rate, 3) == round(209.0225, 3)
+    sell_order = res.select_order('sell', True)
+    assert sell_order is not None
 
 
 def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
-    default_conf['use_sell_signal'] = False
+    default_conf['use_exit_signal'] = False
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
     patch_exchange(mocker)
     backtesting = Backtesting(default_conf)
     backtesting._set_strategy(backtesting.strategylist[0])
@@ -643,8 +753,9 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
                              timerange=timerange)
     processed = backtesting.strategy.advise_all_indicators(data)
     min_date, max_date = get_timerange(processed)
+
     result = backtesting.backtest(
-        processed=processed,
+        processed=deepcopy(processed),
         start_date=min_date,
         end_date=max_date,
         max_open_trades=10,
@@ -670,7 +781,7 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
          'trade_duration': [235, 40],
          'profit_ratio': [0.0, 0.0],
          'profit_abs': [0.0, 0.0],
-         'sell_reason': [SellType.ROI.value, SellType.ROI.value],
+         'exit_reason': [ExitType.ROI.value, ExitType.ROI.value],
          'initial_stop_loss_abs': [0.0940005, 0.09272236],
          'initial_stop_loss_ratio': [-0.1, -0.1],
          'stop_loss_abs': [0.0940005, 0.09272236],
@@ -678,7 +789,8 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
          'min_rate': [0.10370188, 0.10300000000000001],
          'max_rate': [0.10501, 0.1038888],
          'is_open': [False, False],
-         'buy_tag': [None, None],
+         'enter_tag': [None, None],
+         "is_short": [False, False],
          })
     pd.testing.assert_frame_equal(results, expected)
     data_pair = processed[pair]
@@ -695,9 +807,10 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
 
 
 def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None:
-    default_conf['use_sell_signal'] = False
+    default_conf['use_exit_signal'] = False
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
     patch_exchange(mocker)
     backtesting = Backtesting(default_conf)
     backtesting._set_strategy(backtesting.strategylist[0])
@@ -719,6 +832,36 @@ def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None
     assert len(results['results']) == 1
 
 
+def test_backtest_trim_no_data_left(default_conf, fee, mocker, testdatadir) -> None:
+    default_conf['use_exit_signal'] = False
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
+    patch_exchange(mocker)
+    backtesting = Backtesting(default_conf)
+    backtesting._set_strategy(backtesting.strategylist[0])
+    timerange = TimeRange('date', None, 1517227800, 0)
+    backtesting.required_startup = 100
+    backtesting.timerange = timerange
+    data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
+                             timerange=timerange)
+    df = data['UNITTEST/BTC']
+    df.loc[:, 'date'] = df.loc[:, 'date'] - timedelta(days=1)
+    # Trimming 100 candles, so after 2nd trimming, no candle is left.
+    df = df.iloc[:100]
+    data['XRP/USDT'] = df
+    processed = backtesting.strategy.advise_all_indicators(data)
+    min_date, max_date = get_timerange(processed)
+
+    backtesting.backtest(
+        processed=deepcopy(processed),
+        start_date=min_date,
+        end_date=max_date,
+        max_open_trades=10,
+        position_stacking=False,
+    )
+
+
 def test_processed(default_conf, mocker, testdatadir) -> None:
     patch_exchange(mocker)
     backtesting = Backtesting(default_conf)
@@ -734,6 +877,47 @@ def test_processed(default_conf, mocker, testdatadir) -> None:
         assert col in cols
 
 
+def test_backtest_dataprovider_analyzed_df(default_conf, fee, mocker, testdatadir) -> None:
+    default_conf['use_exit_signal'] = False
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=100000)
+    patch_exchange(mocker)
+    backtesting = Backtesting(default_conf)
+    backtesting._set_strategy(backtesting.strategylist[0])
+    timerange = TimeRange('date', None, 1517227800, 0)
+    data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
+                             timerange=timerange)
+    processed = backtesting.strategy.advise_all_indicators(data)
+    min_date, max_date = get_timerange(processed)
+
+    global count
+    count = 0
+
+    def tmp_confirm_entry(pair, current_time, **kwargs):
+        dp = backtesting.strategy.dp
+        df, _ = dp.get_analyzed_dataframe(pair, backtesting.strategy.timeframe)
+        current_candle = df.iloc[-1].squeeze()
+        assert current_candle['enter_long'] == 1
+
+        candle_date = timeframe_to_next_date(backtesting.strategy.timeframe, current_candle['date'])
+        assert candle_date == current_time
+        # These asserts don't properly raise as they are nested,
+        # therefore we increment count and assert for that.
+        global count
+        count = count + 1
+
+    backtesting.strategy.confirm_trade_entry = tmp_confirm_entry
+    backtesting.backtest(
+        processed=deepcopy(processed),
+        start_date=min_date,
+        end_date=max_date,
+        max_open_trades=10,
+        position_stacking=False,
+    )
+    assert count == 5
+
+
 def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatadir) -> None:
     # While this test IS a copy of test_backtest_pricecontours, it's needed to ensure
     # results do not carry-over to the next run, which is not given by using parametrize.
@@ -746,6 +930,7 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad
     default_conf['enable_protections'] = True
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
     tests = [
         ['sine', 9],
         ['raise', 10],
@@ -753,9 +938,11 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad
         ['sine', 9],
         ['raise', 10],
     ]
-    # While buy-signals are unrealistic, running backtesting
+    # While entry-signals are unrealistic, running backtesting
     # over and over again should not cause different results
     for [contour, numres] in tests:
+        # Debug output for random test failure
+        print(f"{contour}, {numres}")
         assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == numres
 
 
@@ -778,14 +965,15 @@ def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir,
         default_conf['enable_protections'] = True
 
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
-    # While buy-signals are unrealistic, running backtesting
+    # While entry-signals are unrealistic, running backtesting
     # over and over again should not cause different results
     assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == expected
 
 
 def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir):
-    # Override the default buy trend function in our StrategyTestV2
+    # Override the default buy trend function in our StrategyTest
     def fun(dataframe=None, pair=None):
         buy_value = 1
         sell_value = 1
@@ -794,14 +982,14 @@ def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir):
     backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir)
     backtesting = Backtesting(default_conf)
     backtesting._set_strategy(backtesting.strategylist[0])
-    backtesting.strategy.advise_buy = fun  # Override
-    backtesting.strategy.advise_sell = fun  # Override
+    backtesting.strategy.advise_entry = fun  # Override
+    backtesting.strategy.advise_exit = fun  # Override
     result = backtesting.backtest(**backtest_conf)
     assert result['results'].empty
 
 
 def test_backtest_only_sell(mocker, default_conf, testdatadir):
-    # Override the default buy trend function in our StrategyTestV2
+    # Override the default buy trend function in our StrategyTest
     def fun(dataframe=None, pair=None):
         buy_value = 0
         sell_value = 1
@@ -810,14 +998,15 @@ def test_backtest_only_sell(mocker, default_conf, testdatadir):
     backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir)
     backtesting = Backtesting(default_conf)
     backtesting._set_strategy(backtesting.strategylist[0])
-    backtesting.strategy.advise_buy = fun  # Override
-    backtesting.strategy.advise_sell = fun  # Override
+    backtesting.strategy.advise_entry = fun  # Override
+    backtesting.strategy.advise_exit = fun  # Override
     result = backtesting.backtest(**backtest_conf)
     assert result['results'].empty
 
 
 def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     backtest_conf = _make_backtest_conf(mocker, conf=default_conf,
                                         pair='UNITTEST/BTC', datadir=testdatadir)
@@ -825,8 +1014,8 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
     backtesting = Backtesting(default_conf)
     backtesting.required_startup = 0
     backtesting._set_strategy(backtesting.strategylist[0])
-    backtesting.strategy.advise_buy = _trend_alternate  # Override
-    backtesting.strategy.advise_sell = _trend_alternate  # Override
+    backtesting.strategy.advise_entry = _trend_alternate  # Override
+    backtesting.strategy.advise_exit = _trend_alternate  # Override
     result = backtesting.backtest(**backtest_conf)
     # 200 candles in backtest data
     # won't buy on first (shifted by 1)
@@ -857,11 +1046,14 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
             multi = 20
         else:
             multi = 18
-        dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
-        dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
+        dataframe['enter_long'] = np.where(dataframe.index % multi == 0, 1, 0)
+        dataframe['exit_long'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
+        dataframe['enter_short'] = 0
+        dataframe['exit_short'] = 0
         return dataframe
 
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     patch_exchange(mocker)
 
@@ -877,13 +1069,13 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
 
     backtesting = Backtesting(default_conf)
     backtesting._set_strategy(backtesting.strategylist[0])
-    backtesting.strategy.advise_buy = _trend_alternate_hold  # Override
-    backtesting.strategy.advise_sell = _trend_alternate_hold  # Override
+    backtesting.strategy.advise_entry = _trend_alternate_hold  # Override
+    backtesting.strategy.advise_exit = _trend_alternate_hold  # Override
 
     processed = backtesting.strategy.advise_all_indicators(data)
     min_date, max_date = get_timerange(processed)
     backtest_conf = {
-        'processed': processed,
+        'processed': deepcopy(processed),
         'start_date': min_date,
         'end_date': max_date,
         'max_open_trades': 3,
@@ -901,11 +1093,12 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
     offset = 1 if tres == 0 else 0
     removed_candles = len(data[pair]) - offset - backtesting.strategy.startup_candle_count
     assert len(backtesting.dataprovider.get_analyzed_dataframe(pair, '5m')[0]) == removed_candles
-    assert len(backtesting.dataprovider.get_analyzed_dataframe(
-        'NXT/BTC', '5m')[0]) == len(data['NXT/BTC']) - 1 - backtesting.strategy.startup_candle_count
+    assert len(
+        backtesting.dataprovider.get_analyzed_dataframe('NXT/BTC', '5m')[0]
+    ) == len(data['NXT/BTC']) - 1 - backtesting.strategy.startup_candle_count
 
     backtest_conf = {
-        'processed': processed,
+        'processed': deepcopy(processed),
         'start_date': min_date,
         'end_date': max_date,
         'max_open_trades': 1,
@@ -928,7 +1121,7 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
     args = [
         'backtesting',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
         '--datadir', str(testdatadir),
         '--timeframe', '1m',
         '--timerange', '1510694220-1510700340',
@@ -958,10 +1151,10 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
 def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
 
     default_conf.update({
-        "use_sell_signal": True,
-        "sell_profit_only": False,
-        "sell_profit_offset": 0.0,
-        "ignore_roi_if_buy_signal": False,
+        "use_exit_signal": True,
+        "exit_profit_only": False,
+        "exit_profit_offset": 0.0,
+        "ignore_roi_if_entry_signal": False,
     })
     patch_exchange(mocker)
     backtestmock = MagicMock(return_value={
@@ -969,6 +1162,8 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
         'config': default_conf,
         'locks': [],
         'rejected_signals': 20,
+        'timedout_entry_orders': 0,
+        'timedout_exit_orders': 0,
         'final_balance': 1000,
     })
     mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
@@ -983,7 +1178,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
                           text_table_bt_results=text_table_mock,
                           text_table_strategy=strattable_mock,
                           generate_pair_metrics=MagicMock(),
-                          generate_sell_reason_stats=sell_reason_mock,
+                          generate_exit_reason_stats=sell_reason_mock,
                           generate_strategy_comparison=strat_summary,
                           generate_daily_stats=MagicMock(),
                           )
@@ -999,7 +1194,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
         '--enable-position-stacking',
         '--disable-max-market-positions',
         '--strategy-list',
-        'StrategyTestV2',
+        CURRENT_TEST_STRATEGY,
         'TestStrategyLegacyV1',
     ]
     args = get_args(args)
@@ -1022,7 +1217,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
         'Backtesting with data from 2017-11-14 21:17:00 '
         'up to 2017-11-14 22:58:00 (0 days).',
         'Parameter --enable-position-stacking detected ...',
-        'Running backtesting for Strategy StrategyTestV2',
+        f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}',
         'Running backtesting for Strategy TestStrategyLegacyV1',
     ]
 
@@ -1033,10 +1228,10 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
 @pytest.mark.filterwarnings("ignore:deprecated")
 def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdatadir, capsys):
     default_conf.update({
-        "use_sell_signal": True,
-        "sell_profit_only": False,
-        "sell_profit_offset": 0.0,
-        "ignore_roi_if_buy_signal": False,
+        "use_exit_signal": True,
+        "exit_profit_only": False,
+        "exit_profit_offset": 0.0,
+        "ignore_roi_if_entry_signal": False,
     })
     patch_exchange(mocker)
     result1 = pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC'],
@@ -1052,7 +1247,9 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
                             'stake_amount': [0.01, 0.01],
                             'open_rate': [0.104445, 0.10302485],
                             'close_rate': [0.104969, 0.103541],
-                            'sell_reason': [SellType.ROI, SellType.ROI]
+                            "is_short": [False, False],
+
+                            'exit_reason': [ExitType.ROI, ExitType.ROI]
                             })
     result2 = pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'],
                             'profit_ratio': [0.03, 0.01, 0.1],
@@ -1069,7 +1266,8 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
                             'stake_amount': [0.01, 0.01, 0.01],
                             'open_rate': [0.104445, 0.10302485, 0.122541],
                             'close_rate': [0.104969, 0.103541, 0.123541],
-                            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
+                            "is_short": [False, False, False],
+                            'exit_reason': [ExitType.ROI, ExitType.ROI, ExitType.STOP_LOSS]
                             })
     backtestmock = MagicMock(side_effect=[
         {
@@ -1077,6 +1275,8 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
             'config': default_conf,
             'locks': [],
             'rejected_signals': 20,
+            'timedout_entry_orders': 0,
+            'timedout_exit_orders': 0,
             'final_balance': 1000,
         },
         {
@@ -1084,6 +1284,8 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
             'config': default_conf,
             'locks': [],
             'rejected_signals': 20,
+            'timedout_entry_orders': 0,
+            'timedout_exit_orders': 0,
             'final_balance': 1000,
         }
     ])
@@ -1102,8 +1304,9 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
         '--timerange', '1510694220-1510700340',
         '--enable-position-stacking',
         '--disable-max-market-positions',
+        '--breakdown', 'day',
         '--strategy-list',
-        'StrategyTestV2',
+        CURRENT_TEST_STRATEGY,
         'TestStrategyLegacyV1',
     ]
     args = get_args(args)
@@ -1120,7 +1323,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
         'Backtesting with data from 2017-11-14 21:17:00 '
         'up to 2017-11-14 22:58:00 (0 days).',
         'Parameter --enable-position-stacking detected ...',
-        'Running backtesting for Strategy StrategyTestV2',
+        f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}',
         'Running backtesting for Strategy TestStrategyLegacyV1',
     ]
 
@@ -1129,21 +1332,128 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
 
     captured = capsys.readouterr()
     assert 'BACKTESTING REPORT' in captured.out
-    assert 'SELL REASON STATS' in captured.out
+    assert 'EXIT REASON STATS' in captured.out
+    assert 'DAY BREAKDOWN' in captured.out
     assert 'LEFT OPEN TRADES REPORT' in captured.out
     assert '2017-11-14 21:17:00 -> 2017-11-14 22:58:00 | Max open trades : 1' in captured.out
     assert 'STRATEGY SUMMARY' in captured.out
 
 
+@pytest.mark.filterwarnings("ignore:deprecated")
+def test_backtest_start_nomock_futures(default_conf_usdt, mocker,
+                                       caplog, testdatadir, capsys):
+    # Tests detail-data loading
+    default_conf_usdt.update({
+        "trading_mode": "futures",
+        "margin_mode": "isolated",
+        "use_exit_signal": True,
+        "exit_profit_only": False,
+        "exit_profit_offset": 0.0,
+        "ignore_roi_if_entry_signal": False,
+        "strategy": CURRENT_TEST_STRATEGY,
+    })
+    patch_exchange(mocker)
+    result1 = pd.DataFrame({'pair': ['XRP/USDT', 'XRP/USDT'],
+                            'profit_ratio': [0.0, 0.0],
+                            'profit_abs': [0.0, 0.0],
+                            'open_date': pd.to_datetime(['2021-11-18 18:00:00',
+                                                         '2021-11-18 03:00:00', ], utc=True
+                                                        ),
+                            'close_date': pd.to_datetime(['2021-11-18 20:00:00',
+                                                          '2021-11-18 05:00:00', ], utc=True),
+                            'trade_duration': [235, 40],
+                            'is_open': [False, False],
+                            'is_short': [False, False],
+                            'stake_amount': [0.01, 0.01],
+                            'open_rate': [0.104445, 0.10302485],
+                            'close_rate': [0.104969, 0.103541],
+                            'exit_reason': [ExitType.ROI, ExitType.ROI]
+                            })
+    result2 = pd.DataFrame({'pair': ['XRP/USDT', 'XRP/USDT', 'XRP/USDT'],
+                            'profit_ratio': [0.03, 0.01, 0.1],
+                            'profit_abs': [0.01, 0.02, 0.2],
+                            'open_date': pd.to_datetime(['2021-11-19 18:00:00',
+                                                         '2021-11-19 03:00:00',
+                                                         '2021-11-19 05:00:00'], utc=True
+                                                        ),
+                            'close_date': pd.to_datetime(['2021-11-19 20:00:00',
+                                                          '2021-11-19 05:00:00',
+                                                          '2021-11-19 08:00:00'], utc=True),
+                            'trade_duration': [47, 40, 20],
+                            'is_open': [False, False, False],
+                            'is_short': [False, False, False],
+                            'stake_amount': [0.01, 0.01, 0.01],
+                            'open_rate': [0.104445, 0.10302485, 0.122541],
+                            'close_rate': [0.104969, 0.103541, 0.123541],
+                            'exit_reason': [ExitType.ROI, ExitType.ROI, ExitType.STOP_LOSS]
+                            })
+    backtestmock = MagicMock(side_effect=[
+        {
+            'results': result1,
+            'config': default_conf_usdt,
+            'locks': [],
+            'rejected_signals': 20,
+            'timedout_entry_orders': 0,
+            'timedout_exit_orders': 0,
+            'final_balance': 1000,
+        },
+        {
+            'results': result2,
+            'config': default_conf_usdt,
+            'locks': [],
+            'rejected_signals': 20,
+            'timedout_entry_orders': 0,
+            'timedout_exit_orders': 0,
+            'final_balance': 1000,
+        }
+    ])
+    mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=['XRP/USDT']))
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
+
+    patched_configuration_load_config_file(mocker, default_conf_usdt)
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--datadir', str(testdatadir),
+        '--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'),
+        '--timeframe', '1h',
+    ]
+    args = get_args(args)
+    start_backtesting(args)
+
+    # check the logs, that will contain the backtest result
+    exists = [
+        'Parameter -i/--timeframe detected ... Using timeframe: 1h ...',
+        f'Using data directory: {testdatadir} ...',
+        'Loading data from 2021-11-17 01:00:00 '
+        'up to 2021-11-21 03:00:00 (4 days).',
+        'Backtesting with data from 2021-11-17 21:00:00 '
+        'up to 2021-11-21 03:00:00 (3 days).',
+        'XRP/USDT, funding_rate, 8h, data starts at 2021-11-18 00:00:00',
+        'XRP/USDT, mark, 8h, data starts at 2021-11-18 00:00:00',
+        f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}',
+    ]
+
+    for line in exists:
+        assert log_has(line, caplog)
+
+    captured = capsys.readouterr()
+    assert 'BACKTESTING REPORT' in captured.out
+    assert 'EXIT REASON STATS' in captured.out
+    assert 'LEFT OPEN TRADES REPORT' in captured.out
+
+
 @pytest.mark.filterwarnings("ignore:deprecated")
 def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
                                                   caplog, testdatadir, capsys):
     # Tests detail-data loading
     default_conf.update({
-        "use_sell_signal": True,
-        "sell_profit_only": False,
-        "sell_profit_offset": 0.0,
-        "ignore_roi_if_buy_signal": False,
+        "use_exit_signal": True,
+        "exit_profit_only": False,
+        "exit_profit_offset": 0.0,
+        "ignore_roi_if_entry_signal": False,
     })
     patch_exchange(mocker)
     result1 = pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC'],
@@ -1156,10 +1466,11 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
                                                           '2018-01-30 05:35:00', ], utc=True),
                             'trade_duration': [235, 40],
                             'is_open': [False, False],
+                            'is_short': [False, False],
                             'stake_amount': [0.01, 0.01],
                             'open_rate': [0.104445, 0.10302485],
                             'close_rate': [0.104969, 0.103541],
-                            'sell_reason': [SellType.ROI, SellType.ROI]
+                            'exit_reason': [ExitType.ROI, ExitType.ROI]
                             })
     result2 = pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'],
                             'profit_ratio': [0.03, 0.01, 0.1],
@@ -1173,10 +1484,11 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
                                                           '2018-01-30 08:30:00'], utc=True),
                             'trade_duration': [47, 40, 20],
                             'is_open': [False, False, False],
+                            'is_short': [False, False, False],
                             'stake_amount': [0.01, 0.01, 0.01],
                             'open_rate': [0.104445, 0.10302485, 0.122541],
                             'close_rate': [0.104969, 0.103541, 0.123541],
-                            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
+                            'exit_reason': [ExitType.ROI, ExitType.ROI, ExitType.STOP_LOSS]
                             })
     backtestmock = MagicMock(side_effect=[
         {
@@ -1184,6 +1496,8 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
             'config': default_conf,
             'locks': [],
             'rejected_signals': 20,
+            'timedout_entry_orders': 0,
+            'timedout_exit_orders': 0,
             'final_balance': 1000,
         },
         {
@@ -1191,6 +1505,8 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
             'config': default_conf,
             'locks': [],
             'rejected_signals': 20,
+            'timedout_entry_orders': 0,
+            'timedout_exit_orders': 0,
             'final_balance': 1000,
         }
     ])
@@ -1208,7 +1524,7 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
         '--timeframe', '5m',
         '--timeframe-detail', '1m',
         '--strategy-list',
-        'StrategyTestV2'
+        CURRENT_TEST_STRATEGY
     ]
     args = get_args(args)
     start_backtesting(args)
@@ -1222,7 +1538,7 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
         'up to 2019-10-13 11:10:00 (2 days).',
         'Backtesting with data from 2019-10-11 01:40:00 '
         'up to 2019-10-13 11:10:00 (2 days).',
-        'Running backtesting for Strategy StrategyTestV2',
+        f'Running backtesting for Strategy {CURRENT_TEST_STRATEGY}',
     ]
 
     for line in exists:
@@ -1230,5 +1546,134 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
 
     captured = capsys.readouterr()
     assert 'BACKTESTING REPORT' in captured.out
-    assert 'SELL REASON STATS' in captured.out
+    assert 'EXIT REASON STATS' in captured.out
     assert 'LEFT OPEN TRADES REPORT' in captured.out
+
+
+@pytest.mark.filterwarnings("ignore:deprecated")
+@pytest.mark.parametrize('run_id', ['2', 'changed'])
+@pytest.mark.parametrize('start_delta', [{'days': 0}, {'days': 1}, {'weeks': 1}, {'weeks': 4}])
+@pytest.mark.parametrize('cache', constants.BACKTEST_CACHE_AGE)
+def test_backtest_start_multi_strat_caching(default_conf, mocker, caplog, testdatadir, run_id,
+                                            start_delta, cache):
+    default_conf.update({
+        "use_exit_signal": True,
+        "exit_profit_only": False,
+        "exit_profit_offset": 0.0,
+        "ignore_roi_if_entry_signal": False,
+    })
+    patch_exchange(mocker)
+    backtestmock = MagicMock(return_value={
+        'results': pd.DataFrame(columns=BT_DATA_COLUMNS),
+        'config': default_conf,
+        'locks': [],
+        'rejected_signals': 20,
+        'timedout_entry_orders': 0,
+        'timedout_exit_orders': 0,
+        'final_balance': 1000,
+    })
+    mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=['UNITTEST/BTC']))
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
+    mocker.patch('freqtrade.optimize.backtesting.show_backtest_results', MagicMock())
+
+    now = min_backtest_date = datetime.now(tz=timezone.utc)
+    start_time = now - timedelta(**start_delta) + timedelta(hours=1)
+    if cache == 'none':
+        min_backtest_date = now + timedelta(days=1)
+    elif cache == 'day':
+        min_backtest_date = now - timedelta(days=1)
+    elif cache == 'week':
+        min_backtest_date = now - timedelta(weeks=1)
+    elif cache == 'month':
+        min_backtest_date = now - timedelta(weeks=4)
+    load_backtest_metadata = MagicMock(return_value={
+        'StrategyTestV2': {'run_id': '1', 'backtest_start_time': now.timestamp()},
+        'TestStrategyLegacyV1': {'run_id': run_id, 'backtest_start_time': start_time.timestamp()}
+    })
+    load_backtest_stats = MagicMock(side_effect=[
+        {
+            'metadata': {'StrategyTestV2': {'run_id': '1'}},
+            'strategy': {'StrategyTestV2': {}},
+            'strategy_comparison': [{'key': 'StrategyTestV2'}]
+        },
+        {
+            'metadata': {'TestStrategyLegacyV1': {'run_id': '2'}},
+            'strategy': {'TestStrategyLegacyV1': {}},
+            'strategy_comparison': [{'key': 'TestStrategyLegacyV1'}]
+        }
+    ])
+    mocker.patch('pathlib.Path.glob', return_value=[
+        Path(datetime.strftime(datetime.now(), 'backtest-result-%Y-%m-%d_%H-%M-%S.json'))])
+    mocker.patch.multiple('freqtrade.data.btanalysis',
+                          load_backtest_metadata=load_backtest_metadata,
+                          load_backtest_stats=load_backtest_stats)
+    mocker.patch('freqtrade.optimize.backtesting.get_strategy_run_id', side_effect=['1', '2', '2'])
+
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--datadir', str(testdatadir),
+        '--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'),
+        '--timeframe', '1m',
+        '--timerange', '1510694220-1510700340',
+        '--enable-position-stacking',
+        '--disable-max-market-positions',
+        '--cache', cache,
+        '--strategy-list',
+        'StrategyTestV2',
+        'TestStrategyLegacyV1',
+    ]
+    args = get_args(args)
+    start_backtesting(args)
+
+    # check the logs, that will contain the backtest result
+    exists = [
+        'Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
+        'Parameter --timerange detected: 1510694220-1510700340 ...',
+        f'Using data directory: {testdatadir} ...',
+        'Loading data from 2017-11-14 20:57:00 '
+        'up to 2017-11-14 22:58:00 (0 days).',
+        'Parameter --enable-position-stacking detected ...',
+    ]
+
+    for line in exists:
+        assert log_has(line, caplog)
+
+    if cache == 'none':
+        assert backtestmock.call_count == 2
+        exists = [
+            'Running backtesting for Strategy StrategyTestV2',
+            'Running backtesting for Strategy TestStrategyLegacyV1',
+            'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
+            'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:58:00 (0 days).',
+        ]
+    elif run_id == '2' and min_backtest_date < start_time:
+        assert backtestmock.call_count == 0
+        exists = [
+            'Reusing result of previous backtest for StrategyTestV2',
+            'Reusing result of previous backtest for TestStrategyLegacyV1',
+        ]
+    else:
+        exists = [
+            'Reusing result of previous backtest for StrategyTestV2',
+            'Running backtesting for Strategy TestStrategyLegacyV1',
+            'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
+            'Backtesting with data from 2017-11-14 21:17:00 up to 2017-11-14 22:58:00 (0 days).',
+        ]
+        assert backtestmock.call_count == 1
+
+    for line in exists:
+        assert log_has(line, caplog)
+
+
+def test_get_strategy_run_id(default_conf_usdt):
+    default_conf_usdt.update({
+        'strategy': 'StrategyTestV2',
+        'max_open_trades': float('inf')
+    })
+    strategy = StrategyResolver.load_strategy(default_conf_usdt)
+    x = get_strategy_run_id(strategy)
+    assert isinstance(x, str)
diff --git a/tests/optimize/test_backtesting_adjust_position.py b/tests/optimize/test_backtesting_adjust_position.py
new file mode 100644
index 000000000..5babfb548
--- /dev/null
+++ b/tests/optimize/test_backtesting_adjust_position.py
@@ -0,0 +1,84 @@
+# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
+
+from copy import deepcopy
+
+import pandas as pd
+from arrow import Arrow
+
+from freqtrade.configuration import TimeRange
+from freqtrade.data import history
+from freqtrade.data.history import get_timerange
+from freqtrade.enums import ExitType
+from freqtrade.optimize.backtesting import Backtesting
+from tests.conftest import patch_exchange
+
+
+def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) -> None:
+    default_conf['use_exit_signal'] = False
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
+    mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
+    patch_exchange(mocker)
+    default_conf.update({
+        "stake_amount": 100.0,
+        "dry_run_wallet": 1000.0,
+        "strategy": "StrategyTestV2"
+    })
+    backtesting = Backtesting(default_conf)
+    backtesting._set_strategy(backtesting.strategylist[0])
+    pair = 'UNITTEST/BTC'
+    timerange = TimeRange('date', None, 1517227800, 0)
+    data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
+                             timerange=timerange)
+    backtesting.strategy.position_adjustment_enable = True
+    processed = backtesting.strategy.advise_all_indicators(data)
+    min_date, max_date = get_timerange(processed)
+    result = backtesting.backtest(
+        processed=deepcopy(processed),
+        start_date=min_date,
+        end_date=max_date,
+        max_open_trades=10,
+        position_stacking=False,
+    )
+    results = result['results']
+    assert not results.empty
+    assert len(results) == 2
+
+    expected = pd.DataFrame(
+        {'pair': [pair, pair],
+         'stake_amount': [500.0, 100.0],
+         'amount': [4806.87657523, 970.63960782],
+         'open_date': pd.to_datetime([Arrow(2018, 1, 29, 18, 40, 0).datetime,
+                                      Arrow(2018, 1, 30, 3, 30, 0).datetime], utc=True
+                                     ),
+         'close_date': pd.to_datetime([Arrow(2018, 1, 29, 22, 00, 0).datetime,
+                                       Arrow(2018, 1, 30, 4, 10, 0).datetime], utc=True),
+         'open_rate': [0.10401764894444211, 0.10302485],
+         'close_rate': [0.10453904066847439, 0.103541],
+         'fee_open': [0.0025, 0.0025],
+         'fee_close': [0.0025, 0.0025],
+         'trade_duration': [200, 40],
+         'profit_ratio': [0.0, 0.0],
+         'profit_abs': [0.0, 0.0],
+         'exit_reason': [ExitType.ROI.value, ExitType.ROI.value],
+         'initial_stop_loss_abs': [0.0940005, 0.09272236],
+         'initial_stop_loss_ratio': [-0.1, -0.1],
+         'stop_loss_abs': [0.0940005, 0.09272236],
+         'stop_loss_ratio': [-0.1, -0.1],
+         'min_rate': [0.10370188, 0.10300000000000001],
+         'max_rate': [0.10481985, 0.1038888],
+         'is_open': [False, False],
+         'enter_tag': [None, None],
+         'is_short': [False, False],
+         })
+    pd.testing.assert_frame_equal(results, expected)
+    data_pair = processed[pair]
+    for _, t in results.iterrows():
+        ln = data_pair.loc[data_pair["date"] == t["open_date"]]
+        # Check open trade rate alignes to open rate
+        assert ln is not None
+        # check close trade rate alignes to close rate or is between high and low
+        ln = data_pair.loc[data_pair["date"] == t["close_date"]]
+        assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or
+                round(ln.iloc[0]["low"], 6) < round(
+                t["close_rate"], 6) < round(ln.iloc[0]["high"], 6))
diff --git a/tests/optimize/test_edge_cli.py b/tests/optimize/test_edge_cli.py
index 18d5f1c76..f0f436a43 100644
--- a/tests/optimize/test_edge_cli.py
+++ b/tests/optimize/test_edge_cli.py
@@ -6,7 +6,7 @@ from unittest.mock import MagicMock
 from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_edge
 from freqtrade.enums import RunMode
 from freqtrade.optimize.edge_cli import EdgeCli
-from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
+from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, log_has, patch_exchange,
                             patched_configuration_load_config_file)
 
 
@@ -16,7 +16,7 @@ def test_setup_optimize_configuration_without_arguments(mocker, default_conf, ca
     args = [
         'edge',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
     ]
 
     config = setup_optimize_configuration(get_args(args), RunMode.EDGE)
@@ -30,7 +30,6 @@ def test_setup_optimize_configuration_without_arguments(mocker, default_conf, ca
     assert 'datadir' in config
     assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
     assert 'timeframe' in config
-    assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
 
     assert 'timerange' not in config
     assert 'stoploss_range' not in config
@@ -46,7 +45,7 @@ def test_setup_edge_configuration_with_arguments(mocker, edge_conf, caplog) -> N
     args = [
         'edge',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
         '--datadir', '/foo/bar',
         '--timeframe', '1m',
         '--timerange', ':100',
@@ -80,7 +79,7 @@ def test_start(mocker, fee, edge_conf, caplog) -> None:
     args = [
         'edge',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
     ]
     pargs = get_args(args)
     start_edge(pargs)
diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py
index e4ce29d44..ce6ae1880 100644
--- a/tests/optimize/test_hyperopt.py
+++ b/tests/optimize/test_hyperopt.py
@@ -1,5 +1,5 @@
 # pragma pylint: disable=missing-docstring,W0212,C0103
-from datetime import datetime
+from datetime import datetime, timedelta
 from pathlib import Path
 from unittest.mock import ANY, MagicMock
 
@@ -10,7 +10,7 @@ from filelock import Timeout
 
 from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
 from freqtrade.data.history import load_data
-from freqtrade.enums import RunMode, SellType
+from freqtrade.enums import ExitType, RunMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.optimize.hyperopt import Hyperopt
 from freqtrade.optimize.hyperopt_auto import HyperOptAuto
@@ -18,10 +18,33 @@ from freqtrade.optimize.hyperopt_tools import HyperoptTools
 from freqtrade.optimize.optimize_reports import generate_strategy_stats
 from freqtrade.optimize.space import SKDecimal
 from freqtrade.strategy.hyper import IntParameter
-from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
+from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, log_has, log_has_re, patch_exchange,
                             patched_configuration_load_config_file)
 
 
+def generate_result_metrics():
+    return {
+        'trade_count': 1,
+        'total_trades': 1,
+        'avg_profit': 0.1,
+        'total_profit': 0.001,
+        'profit': 0.01,
+        'duration': 20.0,
+        'wins': 1,
+        'draws': 0,
+        'losses': 0,
+        'profit_mean': 0.01,
+        'profit_total_abs': 0.001,
+        'profit_total': 0.01,
+        'holding_avg': timedelta(minutes=20),
+        'max_drawdown': 0.001,
+        'max_drawdown_abs': 0.001,
+        'loss': 0.001,
+        'is_initial_point': 0.001,
+        'is_best': 1,
+    }
+
+
 def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
     patched_configuration_load_config_file(mocker, default_conf)
 
@@ -40,7 +63,6 @@ def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, ca
     assert 'datadir' in config
     assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
     assert 'timeframe' in config
-    assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
 
     assert 'position_stacking' not in config
     assert not log_has('Parameter --enable-position-stacking detected ...', caplog)
@@ -122,7 +144,7 @@ def test_setup_hyperopt_configuration_stake_amount(mocker, default_conf) -> None
     args = [
         'hyperopt',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
         '--stake-amount', '1',
         '--starting-balance', '0.5'
     ]
@@ -168,7 +190,8 @@ def test_start_no_hyperopt_allowed(mocker, hyperopt_conf, caplog) -> None:
         start_hyperopt(pargs)
 
 
-def test_start_no_data(mocker, hyperopt_conf) -> None:
+def test_start_no_data(mocker, hyperopt_conf, tmpdir) -> None:
+    hyperopt_conf['user_data_dir'] = Path(tmpdir)
     patched_configuration_load_config_file(mocker, hyperopt_conf)
     mocker.patch('freqtrade.data.history.load_pair_history', MagicMock(return_value=pd.DataFrame))
     mocker.patch(
@@ -177,7 +200,6 @@ def test_start_no_data(mocker, hyperopt_conf) -> None:
     )
 
     patch_exchange(mocker)
-    # TODO: migrate to strategy-based hyperopt
     args = [
         'hyperopt',
         '--config', 'config.json',
@@ -189,6 +211,12 @@ def test_start_no_data(mocker, hyperopt_conf) -> None:
     with pytest.raises(OperationalException, match='No data found. Terminating.'):
         start_hyperopt(pargs)
 
+    # Cleanup since that failed hyperopt start leaves a lockfile.
+    try:
+        Path(Hyperopt.get_lock_filename(hyperopt_conf)).unlink()
+    except Exception:
+        pass
+
 
 def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
     hyperopt_mock = MagicMock(side_effect=Timeout(Hyperopt.get_lock_filename(hyperopt_conf)))
@@ -215,14 +243,7 @@ def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
     hyperopt.print_results(
         {
             'loss': 1,
-            'results_metrics':
-                {
-                    'trade_count': 1,
-                    'avg_profit': 0.1,
-                    'total_profit': 0.001,
-                    'profit': 1.0,
-                    'duration': 20.0
-                },
+            'results_metrics': generate_result_metrics(),
             'total_profit': 0,
             'current_epoch': 2,  # This starts from 1 (in a human-friendly manner)
             'is_initial_point': False,
@@ -231,7 +252,7 @@ def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
     )
     out, err = capsys.readouterr()
     assert all(x in out
-               for x in ["Best", "2/2", " 1", "0.10%", "0.00100000 BTC    (1.00%)", "20.0 m"])
+               for x in ["Best", "2/2", " 1", "0.10%", "0.00100000 BTC    (1.00%)", "00:20:00"])
 
 
 def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
@@ -288,14 +309,7 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
         MagicMock(return_value=[{
             'loss': 1, 'results_explanation': 'foo result',
             'params': {'buy': {}, 'sell': {}, 'roi': {}, 'stoploss': 0.0},
-            'results_metrics':
-            {
-                'trade_count': 1,
-                'avg_profit': 0.1,
-                'total_profit': 0.001,
-                'profit': 1.0,
-                'duration': 20.0
-            },
+            'results_metrics': generate_result_metrics(),
         }])
     )
     patch_exchange(mocker)
@@ -315,8 +329,8 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
     # Should be called for historical candle data
     assert dumper.call_count == 1
     assert dumper2.call_count == 1
-    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
-    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_entry")
     assert hasattr(hyperopt, "max_open_trades")
     assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
     assert hasattr(hyperopt, "position_stacking")
@@ -341,18 +355,21 @@ def test_hyperopt_format_results(hyperopt):
                                  "close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
                                  "trade_duration": [123, 34, 31, 14],
                                  "is_open": [False, False, False, True],
+                                 "is_short": [False, False, False, False],
                                  "stake_amount": [0.01, 0.01, 0.01, 0.01],
-                                 "sell_reason": [SellType.ROI, SellType.STOP_LOSS,
-                                                 SellType.ROI, SellType.FORCE_SELL]
+                                 "exit_reason": [ExitType.ROI, ExitType.STOP_LOSS,
+                                                 ExitType.ROI, ExitType.FORCE_EXIT]
                                  }),
         'config': hyperopt.config,
         'locks': [],
         'final_balance': 0.02,
         'rejected_signals': 2,
+        'timedout_entry_orders': 0,
+        'timedout_exit_orders': 0,
         'backtest_start_time': 1619718665,
         'backtest_end_time': 1619718665,
     }
-    results_metrics = generate_strategy_stats({'XRP/BTC': None}, '', bt_result,
+    results_metrics = generate_strategy_stats(['XRP/BTC'], '', bt_result,
                                               Arrow(2017, 11, 14, 19, 32, 00),
                                               Arrow(2017, 12, 14, 19, 32, 00), market_change=0)
 
@@ -409,13 +426,16 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
                                  "close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
                                  "trade_duration": [123, 34, 31, 14],
                                  "is_open": [False, False, False, True],
+                                 "is_short": [False, False, False, False],
                                  "stake_amount": [0.01, 0.01, 0.01, 0.01],
-                                 "sell_reason": [SellType.ROI, SellType.STOP_LOSS,
-                                                 SellType.ROI, SellType.FORCE_SELL]
+                                 "exit_reason": [ExitType.ROI, ExitType.STOP_LOSS,
+                                                 ExitType.ROI, ExitType.FORCE_EXIT]
                                  }),
         'config': hyperopt_conf,
         'locks': [],
         'rejected_signals': 20,
+        'timedout_entry_orders': 0,
+        'timedout_exit_orders': 0,
         'final_balance': 1000,
     }
 
@@ -424,6 +444,7 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
                  return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
     patch_exchange(mocker)
     mocker.patch.object(Path, 'open')
+    mocker.patch('freqtrade.configuration.config_validation.validate_config_schema')
     mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None})
 
     optimizer_param = {
@@ -520,14 +541,7 @@ def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
                 'roi': {}, 'stoploss': {'stoploss': None},
                 'trailing': {'trailing_stop': None}
             },
-            'results_metrics':
-            {
-                'trade_count': 1,
-                'avg_profit': 0.1,
-                'total_profit': 0.001,
-                'profit': 1.0,
-                'duration': 20.0
-            }
+            'results_metrics': generate_result_metrics(),
         }])
     )
     patch_exchange(mocker)
@@ -576,14 +590,7 @@ def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
                 'sell': {'sell-mfi-value': None},
                 'roi': {}, 'stoploss': {'stoploss': None}
             },
-            'results_metrics':
-            {
-                'trade_count': 1,
-                'avg_profit': 0.1,
-                'total_profit': 0.001,
-                'profit': 1.0,
-                'duration': 20.0
-            }
+            'results_metrics': generate_result_metrics(),
         }])
     )
     patch_exchange(mocker)
@@ -621,14 +628,7 @@ def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
         MagicMock(return_value=[{
             'loss': 1, 'results_explanation': 'foo result', 'params': {},
             'params_details': {'roi': {}, 'stoploss': {'stoploss': None}},
-            'results_metrics':
-            {
-                'trade_count': 1,
-                'avg_profit': 0.1,
-                'total_profit': 0.001,
-                'profit': 1.0,
-                'duration': 20.0
-            }
+            'results_metrics': generate_result_metrics(),
         }])
     )
     patch_exchange(mocker)
@@ -668,14 +668,7 @@ def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> Non
         'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
         MagicMock(return_value=[{
             'loss': 1, 'results_explanation': 'foo result', 'params': {'stoploss': 0.0},
-            'results_metrics':
-            {
-                'trade_count': 1,
-                'avg_profit': 0.1,
-                'total_profit': 0.001,
-                'profit': 1.0,
-                'duration': 20.0
-            }
+            'results_metrics': generate_result_metrics(),
         }])
     )
     patch_exchange(mocker)
@@ -695,14 +688,14 @@ def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> Non
     assert dumper.call_count == 1
     assert dumper2.call_count == 1
 
-    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
-    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_entry")
     assert hasattr(hyperopt, "max_open_trades")
     assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
     assert hasattr(hyperopt, "position_stacking")
 
 
-def test_simplified_interface_all_failed(mocker, hyperopt_conf) -> None:
+def test_simplified_interface_all_failed(mocker, hyperopt_conf, caplog) -> None:
     mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
     mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
     mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
@@ -724,7 +717,13 @@ def test_simplified_interface_all_failed(mocker, hyperopt_conf) -> None:
     hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
 
     with pytest.raises(OperationalException, match=r"The 'protection' space is included into *"):
-        hyperopt.start()
+        hyperopt.init_spaces()
+
+    hyperopt.config['hyperopt_ignore_missing_space'] = True
+    caplog.clear()
+    hyperopt.init_spaces()
+    assert log_has_re(r"The 'protection' space is included into *", caplog)
+    assert hyperopt.protection_space == []
 
 
 def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
@@ -742,14 +741,7 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
         'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
         MagicMock(return_value=[{
             'loss': 1, 'results_explanation': 'foo result', 'params': {},
-            'results_metrics':
-            {
-                'trade_count': 1,
-                'avg_profit': 0.1,
-                'total_profit': 0.001,
-                'profit': 1.0,
-                'duration': 20.0
-            }
+            'results_metrics': generate_result_metrics(),
         }])
     )
     patch_exchange(mocker)
@@ -769,8 +761,8 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
     assert dumper.called
     assert dumper.call_count == 1
     assert dumper2.call_count == 1
-    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
-    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_entry")
     assert hasattr(hyperopt, "max_open_trades")
     assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
     assert hasattr(hyperopt, "position_stacking")
@@ -791,14 +783,7 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
         'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
         MagicMock(return_value=[{
             'loss': 1, 'results_explanation': 'foo result', 'params': {},
-            'results_metrics':
-            {
-                'trade_count': 1,
-                'avg_profit': 0.1,
-                'total_profit': 0.001,
-                'profit': 1.0,
-                'duration': 20.0
-            }
+            'results_metrics': generate_result_metrics(),
         }])
     )
     patch_exchange(mocker)
@@ -818,8 +803,8 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
     assert dumper.called
     assert dumper.call_count == 1
     assert dumper2.call_count == 1
-    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
-    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_entry")
     assert hasattr(hyperopt, "max_open_trades")
     assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
     assert hasattr(hyperopt, "position_stacking")
@@ -866,6 +851,7 @@ def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
         'spaces': ['all']
     })
     hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.exchange.get_max_leverage = MagicMock(return_value=1.0)
     assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
     assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)
 
diff --git a/tests/optimize/test_hyperopt_tools.py b/tests/optimize/test_hyperopt_tools.py
index 9c2b2e8fc..7d4fef3bd 100644
--- a/tests/optimize/test_hyperopt_tools.py
+++ b/tests/optimize/test_hyperopt_tools.py
@@ -10,7 +10,7 @@ import rapidjson
 from freqtrade.constants import FTHYPT_FILEVERSION
 from freqtrade.exceptions import OperationalException
 from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer
-from tests.conftest import log_has
+from tests.conftest import CURRENT_TEST_STRATEGY, log_has, log_has_re
 
 
 # Functions for recurrent object patching
@@ -24,6 +24,7 @@ def test_save_results_saves_epochs(hyperopt, tmpdir, caplog) -> None:
     hyperopt.results_file = Path(tmpdir / 'ut_results.fthypt')
 
     hyperopt_epochs = HyperoptTools.load_filtered_results(hyperopt.results_file, {})
+    assert log_has_re("Hyperopt file .* not found.", caplog)
     assert hyperopt_epochs == ([], 0)
 
     # Test writing to temp dir and reading again
@@ -167,9 +168,9 @@ def test__pprint_dict():
 
 def test_get_strategy_filename(default_conf):
 
-    x = HyperoptTools.get_strategy_filename(default_conf, 'StrategyTestV2')
+    x = HyperoptTools.get_strategy_filename(default_conf, 'StrategyTestV3')
     assert isinstance(x, Path)
-    assert x == Path(__file__).parents[1] / 'strategy/strats/strategy_test_v2.py'
+    assert x == Path(__file__).parents[1] / 'strategy/strats/strategy_test_v3.py'
 
     x = HyperoptTools.get_strategy_filename(default_conf, 'NonExistingStrategy')
     assert x is None
@@ -177,7 +178,7 @@ def test_get_strategy_filename(default_conf):
 
 def test_export_params(tmpdir):
 
-    filename = Path(tmpdir) / "StrategyTestV2.json"
+    filename = Path(tmpdir) / f"{CURRENT_TEST_STRATEGY}.json"
     assert not filename.is_file()
     params = {
         "params_details": {
@@ -205,12 +206,13 @@ def test_export_params(tmpdir):
         }
 
     }
-    HyperoptTools.export_params(params, "StrategyTestV2", filename)
+    HyperoptTools.export_params(params, CURRENT_TEST_STRATEGY, filename)
 
     assert filename.is_file()
 
-    content = rapidjson.load(filename.open('r'))
-    assert content['strategy_name'] == 'StrategyTestV2'
+    with filename.open('r') as f:
+        content = rapidjson.load(f)
+    assert content['strategy_name'] == CURRENT_TEST_STRATEGY
     assert 'params' in content
     assert "buy" in content["params"]
     assert "sell" in content["params"]
@@ -223,7 +225,7 @@ def test_try_export_params(default_conf, tmpdir, caplog, mocker):
     default_conf['disableparamexport'] = False
     export_mock = mocker.patch("freqtrade.optimize.hyperopt_tools.HyperoptTools.export_params")
 
-    filename = Path(tmpdir) / "StrategyTestV2.json"
+    filename = Path(tmpdir) / f"{CURRENT_TEST_STRATEGY}.json"
     assert not filename.is_file()
     params = {
         "params_details": {
@@ -252,17 +254,17 @@ def test_try_export_params(default_conf, tmpdir, caplog, mocker):
         FTHYPT_FILEVERSION: 2,
 
     }
-    HyperoptTools.try_export_params(default_conf, "StrategyTestV222", params)
+    HyperoptTools.try_export_params(default_conf, "StrategyTestVXXX", params)
 
     assert log_has("Strategy not found, not exporting parameter file.", caplog)
     assert export_mock.call_count == 0
     caplog.clear()
 
-    HyperoptTools.try_export_params(default_conf, "StrategyTestV2", params)
+    HyperoptTools.try_export_params(default_conf, CURRENT_TEST_STRATEGY, params)
 
     assert export_mock.call_count == 1
-    assert export_mock.call_args_list[0][0][1] == 'StrategyTestV2'
-    assert export_mock.call_args_list[0][0][2].name == 'strategy_test_v2.json'
+    assert export_mock.call_args_list[0][0][1] == CURRENT_TEST_STRATEGY
+    assert export_mock.call_args_list[0][0][2].name == 'strategy_test_v3.json'
 
 
 def test_params_print(capsys):
diff --git a/tests/optimize/test_hyperoptloss.py b/tests/optimize/test_hyperoptloss.py
index 0082bcc34..e3f6daf6c 100644
--- a/tests/optimize/test_hyperoptloss.py
+++ b/tests/optimize/test_hyperoptloss.py
@@ -35,6 +35,7 @@ def test_hyperoptlossresolver_wrongname(default_conf) -> None:
 
 
 def test_loss_calculation_prefer_correct_trade_count(hyperopt_conf, hyperopt_results) -> None:
+    hyperopt_conf.update({'hyperopt_loss': "ShortTradeDurHyperOptLoss"})
     hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
     correct = hl.hyperopt_loss_function(hyperopt_results, 600,
                                         datetime(2019, 1, 1), datetime(2019, 5, 1))
@@ -50,6 +51,7 @@ def test_loss_calculation_prefer_shorter_trades(hyperopt_conf, hyperopt_results)
     resultsb = hyperopt_results.copy()
     resultsb.loc[1, 'trade_duration'] = 20
 
+    hyperopt_conf.update({'hyperopt_loss': "ShortTradeDurHyperOptLoss"})
     hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
     longer = hl.hyperopt_loss_function(hyperopt_results, 100,
                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
@@ -64,6 +66,7 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
     results_under = hyperopt_results.copy()
     results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
 
+    hyperopt_conf.update({'hyperopt_loss': "ShortTradeDurHyperOptLoss"})
     hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
     correct = hl.hyperopt_loss_function(hyperopt_results, 600,
                                         datetime(2019, 1, 1), datetime(2019, 5, 1))
@@ -75,91 +78,53 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
     assert under > correct
 
 
-def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
+@pytest.mark.parametrize('lossfunction', [
+    "OnlyProfitHyperOptLoss",
+    "SortinoHyperOptLoss",
+    "SortinoHyperOptLossDaily",
+    "SharpeHyperOptLoss",
+    "SharpeHyperOptLossDaily",
+    "MaxDrawDownHyperOptLoss",
+    "CalmarHyperOptLoss",
+    "ProfitDrawDownHyperOptLoss",
+
+])
+def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunction) -> None:
     results_over = hyperopt_results.copy()
+    results_over['profit_abs'] = hyperopt_results['profit_abs'] * 2 + 0.2
     results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
     results_under = hyperopt_results.copy()
+    results_under['profit_abs'] = hyperopt_results['profit_abs'] / 2 - 0.2
     results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
 
-    default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'})
+    default_conf.update({'hyperopt_loss': lossfunction})
     hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
-    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
-                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
-    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
-                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
-    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
-                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
-    assert over < correct
-    assert under > correct
-
-
-def test_sharpe_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
-    results_over = hyperopt_results.copy()
-    results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
-    results_under = hyperopt_results.copy()
-    results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
-
-    default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
-    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
-    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
-                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
-    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
-                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
-    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
-                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
-    assert over < correct
-    assert under > correct
-
-
-def test_sortino_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
-    results_over = hyperopt_results.copy()
-    results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
-    results_under = hyperopt_results.copy()
-    results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
-
-    default_conf.update({'hyperopt_loss': 'SortinoHyperOptLoss'})
-    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
-    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
-                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
-    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
-                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
-    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
-                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
-    assert over < correct
-    assert under > correct
-
-
-def test_sortino_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
-    results_over = hyperopt_results.copy()
-    results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
-    results_under = hyperopt_results.copy()
-    results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
-
-    default_conf.update({'hyperopt_loss': 'SortinoHyperOptLossDaily'})
-    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
-    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
-                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
-    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
-                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
-    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
-                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
-    assert over < correct
-    assert under > correct
-
-
-def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
-    results_over = hyperopt_results.copy()
-    results_over['profit_abs'] = hyperopt_results['profit_abs'] * 2
-    results_under = hyperopt_results.copy()
-    results_under['profit_abs'] = hyperopt_results['profit_abs'] / 2
-
-    default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'})
-    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
-    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
-                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
-    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
-                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
-    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
-                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
+    correct = hl.hyperopt_loss_function(
+        hyperopt_results,
+        trade_count=len(hyperopt_results),
+        min_date=datetime(2019, 1, 1),
+        max_date=datetime(2019, 5, 1),
+        config=default_conf,
+        processed=None,
+        backtest_stats={'profit_total': hyperopt_results['profit_abs'].sum()}
+    )
+    over = hl.hyperopt_loss_function(
+        results_over,
+        trade_count=len(results_over),
+        min_date=datetime(2019, 1, 1),
+        max_date=datetime(2019, 5, 1),
+        config=default_conf,
+        processed=None,
+        backtest_stats={'profit_total': results_over['profit_abs'].sum()}
+    )
+    under = hl.hyperopt_loss_function(
+        results_under,
+        trade_count=len(results_under),
+        min_date=datetime(2019, 1, 1),
+        max_date=datetime(2019, 5, 1),
+        config=default_conf,
+        processed=None,
+        backtest_stats={'profit_total': results_under['profit_abs'].sum()}
+    )
     assert over < correct
     assert under > correct
diff --git a/tests/optimize/test_optimize_reports.py b/tests/optimize/test_optimize_reports.py
index 83caefd2d..05c0bf575 100644
--- a/tests/optimize/test_optimize_reports.py
+++ b/tests/optimize/test_optimize_reports.py
@@ -1,4 +1,3 @@
-import datetime
 import re
 from datetime import timedelta
 from pathlib import Path
@@ -10,17 +9,20 @@ from arrow import Arrow
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
 from freqtrade.data import history
-from freqtrade.data.btanalysis import get_latest_backtest_filename, load_backtest_data
+from freqtrade.data.btanalysis import (get_latest_backtest_filename, load_backtest_data,
+                                       load_backtest_stats)
 from freqtrade.edge import PairInfo
-from freqtrade.enums import SellType
-from freqtrade.optimize.optimize_reports import (generate_backtest_stats, generate_daily_stats,
-                                                 generate_edge_table, generate_pair_metrics,
-                                                 generate_sell_reason_stats,
+from freqtrade.enums import ExitType
+from freqtrade.optimize.optimize_reports import (_get_resample_from_period, generate_backtest_stats,
+                                                 generate_daily_stats, generate_edge_table,
+                                                 generate_exit_reason_stats, generate_pair_metrics,
+                                                 generate_periodic_breakdown_stats,
                                                  generate_strategy_comparison,
-                                                 generate_trading_stats, store_backtest_stats,
-                                                 text_table_bt_results, text_table_sell_reason,
-                                                 text_table_strategy)
+                                                 generate_trading_stats, show_sorted_pairlist,
+                                                 store_backtest_stats, text_table_bt_results,
+                                                 text_table_exit_reason, text_table_strategy)
 from freqtrade.resolvers.strategy_resolver import StrategyResolver
+from tests.conftest import CURRENT_TEST_STRATEGY
 from tests.data.test_history import _backup_file, _clean_test_file
 
 
@@ -46,13 +48,13 @@ def test_text_table_bt_results():
         '        0:20:00 |     2     0     1  66.7 |'
     )
 
-    pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC',
+    pair_results = generate_pair_metrics(['ETH/BTC'], stake_currency='BTC',
                                          starting_balance=4, results=results)
     assert text_table_bt_results(pair_results, stake_currency='BTC') == result_str
 
 
 def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
-    default_conf.update({'strategy': 'StrategyTestV2'})
+    default_conf.update({'strategy': CURRENT_TEST_STRATEGY})
     StrategyResolver.load_strategy(default_conf)
 
     results = {'DefStrat': {
@@ -72,16 +74,20 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
                                  "close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
                                  "trade_duration": [123, 34, 31, 14],
                                  "is_open": [False, False, False, True],
+                                 "is_short": [False, False, False, False],
                                  "stake_amount": [0.01, 0.01, 0.01, 0.01],
-                                 "sell_reason": [SellType.ROI, SellType.STOP_LOSS,
-                                                 SellType.ROI, SellType.FORCE_SELL]
+                                 "exit_reason": [ExitType.ROI, ExitType.STOP_LOSS,
+                                                 ExitType.ROI, ExitType.FORCE_EXIT]
                                  }),
         'config': default_conf,
         'locks': [],
         'final_balance': 1000.02,
         'rejected_signals': 20,
+        'timedout_entry_orders': 0,
+        'timedout_exit_orders': 0,
         'backtest_start_time': Arrow.utcnow().int_timestamp,
         'backtest_end_time': Arrow.utcnow().int_timestamp,
+        'run_id': '123',
         }
         }
     timerange = TimeRange.parse_timerange('1510688220-1510700340')
@@ -100,7 +106,7 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
     assert strat_stats['backtest_end'] == max_date.strftime(DATETIME_PRINT_FORMAT)
     assert strat_stats['total_trades'] == len(results['DefStrat']['results'])
     # Above sample had no loosing trade
-    assert strat_stats['max_drawdown'] == 0.0
+    assert strat_stats['max_drawdown_account'] == 0.0
 
     # Retry with losing trade
     results = {'DefStrat': {
@@ -120,16 +126,20 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
              "close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
              "trade_duration": [123, 34, 31, 14],
              "is_open": [False, False, False, True],
+             "is_short": [False, False, False, False],
              "stake_amount": [0.01, 0.01, 0.01, 0.01],
-             "sell_reason": [SellType.ROI, SellType.ROI,
-                             SellType.STOP_LOSS, SellType.FORCE_SELL]
+             "exit_reason": [ExitType.ROI, ExitType.ROI,
+                             ExitType.STOP_LOSS, ExitType.FORCE_EXIT]
              }),
         'config': default_conf,
         'locks': [],
         'final_balance': 1000.02,
         'rejected_signals': 20,
+        'timedout_entry_orders': 0,
+        'timedout_exit_orders': 0,
         'backtest_start_time': Arrow.utcnow().int_timestamp,
         'backtest_end_time': Arrow.utcnow().int_timestamp,
+        'run_id': '124',
         }
     }
 
@@ -140,7 +150,7 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
     assert 'strategy_comparison' in stats
     strat_stats = stats['strategy']['DefStrat']
 
-    assert strat_stats['max_drawdown'] == 0.013803
+    assert pytest.approx(strat_stats['max_drawdown_account']) == 1.399999e-08
     assert strat_stats['drawdown_start'] == '2017-11-14 22:10:00'
     assert strat_stats['drawdown_end'] == '2017-11-14 22:43:00'
     assert strat_stats['drawdown_end_ts'] == 1510699380000
@@ -162,7 +172,7 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
     filename1 = Path(tmpdir / last_fn)
     assert filename1.is_file()
     content = filename1.read_text()
-    assert 'max_drawdown' in content
+    assert 'max_drawdown_account' in content
     assert 'strategy' in content
     assert 'pairlist' in content
 
@@ -176,16 +186,16 @@ def test_store_backtest_stats(testdatadir, mocker):
 
     dump_mock = mocker.patch('freqtrade.optimize.optimize_reports.file_dump_json')
 
-    store_backtest_stats(testdatadir, {})
+    store_backtest_stats(testdatadir, {'metadata': {}})
 
-    assert dump_mock.call_count == 2
+    assert dump_mock.call_count == 3
     assert isinstance(dump_mock.call_args_list[0][0][0], Path)
-    assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir/'backtest-result'))
+    assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir / 'backtest-result'))
 
     dump_mock.reset_mock()
     filename = testdatadir / 'testresult.json'
-    store_backtest_stats(filename, {})
-    assert dump_mock.call_count == 2
+    store_backtest_stats(filename, {'metadata': {}})
+    assert dump_mock.call_count == 3
     assert isinstance(dump_mock.call_args_list[0][0][0], Path)
     # result will be testdatadir / testresult-<timestamp>.json
     assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir / 'testresult'))
@@ -205,7 +215,7 @@ def test_generate_pair_metrics():
         }
     )
 
-    pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC',
+    pair_results = generate_pair_metrics(['ETH/BTC'], stake_currency='BTC',
                                          starting_balance=2, results=results)
     assert isinstance(pair_results, list)
     assert len(pair_results) == 2
@@ -218,15 +228,15 @@ def test_generate_pair_metrics():
 
 def test_generate_daily_stats(testdatadir):
 
-    filename = testdatadir / "backtest-result_new.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
     res = generate_daily_stats(bt_data)
     assert isinstance(res, dict)
     assert round(res['backtest_best_day'], 4) == 0.1796
     assert round(res['backtest_worst_day'], 4) == -0.1468
-    assert res['winning_days'] == 14
-    assert res['draw_days'] == 4
-    assert res['losing_days'] == 3
+    assert res['winning_days'] == 19
+    assert res['draw_days'] == 0
+    assert res['losing_days'] == 2
 
     # Select empty dataframe!
     res = generate_daily_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :])
@@ -238,7 +248,7 @@ def test_generate_daily_stats(testdatadir):
 
 
 def test_generate_trading_stats(testdatadir):
-    filename = testdatadir / "backtest-result_new.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
     res = generate_trading_stats(bt_data)
     assert isinstance(res, dict)
@@ -254,7 +264,7 @@ def test_generate_trading_stats(testdatadir):
     assert res['losses'] == 0
 
 
-def test_text_table_sell_reason():
+def test_text_table_exit_reason():
 
     results = pd.DataFrame(
         {
@@ -265,12 +275,12 @@ def test_text_table_sell_reason():
             'wins': [2, 0, 0],
             'draws': [0, 0, 0],
             'losses': [0, 0, 1],
-            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
+            'exit_reason': [ExitType.ROI, ExitType.ROI, ExitType.STOP_LOSS]
         }
     )
 
     result_str = (
-        '|   Sell Reason |   Sells |   Win  Draws  Loss  Win% |   Avg Profit % |   Cum Profit % |'
+        '|   Exit Reason |   Exits |   Win  Draws  Loss  Win% |   Avg Profit % |   Cum Profit % |'
         '   Tot Profit BTC |   Tot Profit % |\n'
         '|---------------+---------+--------------------------+----------------+----------------+'
         '------------------+----------------|\n'
@@ -280,9 +290,9 @@ def test_text_table_sell_reason():
         '             -0.2 |             -5 |'
     )
 
-    sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
+    exit_reason_stats = generate_exit_reason_stats(max_open_trades=2,
                                                    results=results)
-    assert text_table_sell_reason(sell_reason_stats=sell_reason_stats,
+    assert text_table_exit_reason(exit_reason_stats=exit_reason_stats,
                                   stake_currency='BTC') == result_str
 
 
@@ -297,23 +307,23 @@ def test_generate_sell_reason_stats():
             'wins': [2, 0, 0],
             'draws': [0, 0, 0],
             'losses': [0, 0, 1],
-            'sell_reason': [SellType.ROI.value, SellType.ROI.value, SellType.STOP_LOSS.value]
+            'exit_reason': [ExitType.ROI.value, ExitType.ROI.value, ExitType.STOP_LOSS.value]
         }
     )
 
-    sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
+    exit_reason_stats = generate_exit_reason_stats(max_open_trades=2,
                                                    results=results)
-    roi_result = sell_reason_stats[0]
-    assert roi_result['sell_reason'] == 'roi'
+    roi_result = exit_reason_stats[0]
+    assert roi_result['exit_reason'] == 'roi'
     assert roi_result['trades'] == 2
     assert pytest.approx(roi_result['profit_mean']) == 0.15
     assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2)
     assert pytest.approx(roi_result['profit_mean']) == 0.15
     assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2)
 
-    stop_result = sell_reason_stats[1]
+    stop_result = exit_reason_stats[1]
 
-    assert stop_result['sell_reason'] == 'stop_loss'
+    assert stop_result['exit_reason'] == 'stop_loss'
     assert stop_result['trades'] == 1
     assert pytest.approx(stop_result['profit_mean']) == -0.1
     assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2)
@@ -321,51 +331,25 @@ def test_generate_sell_reason_stats():
     assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2)
 
 
-def test_text_table_strategy(default_conf):
-    default_conf['max_open_trades'] = 2
-    default_conf['dry_run_wallet'] = 3
-    results = {}
-    date = datetime.datetime(year=2020, month=1, day=1, hour=12, minute=30)
-    delta = datetime.timedelta(days=1)
-    results['TestStrategy1'] = {'results': pd.DataFrame(
-        {
-            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
-            'close_date': [date, date + delta, date + delta * 2],
-            'profit_ratio': [0.1, 0.2, 0.3],
-            'profit_abs': [0.2, 0.4, 0.5],
-            'trade_duration': [10, 30, 10],
-            'wins': [2, 0, 0],
-            'draws': [0, 0, 0],
-            'losses': [0, 0, 1],
-            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
-        }
-    ), 'config': default_conf}
-    results['TestStrategy2'] = {'results': pd.DataFrame(
-        {
-            'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
-            'close_date': [date, date + delta, date + delta * 2],
-            'profit_ratio': [0.4, 0.2, 0.3],
-            'profit_abs': [0.4, 0.4, 0.5],
-            'trade_duration': [15, 30, 15],
-            'wins': [4, 1, 0],
-            'draws': [0, 0, 0],
-            'losses': [0, 0, 1],
-            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
-        }
-    ), 'config': default_conf}
+def test_text_table_strategy(testdatadir):
+    filename = testdatadir / "backtest_results/backtest-result_multistrat.json"
+    bt_res_data = load_backtest_stats(filename)
+
+    bt_res_data_comparison = bt_res_data.pop('strategy_comparison')
 
     result_str = (
-        '|      Strategy |   Buys |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |'
+        '|       Strategy |   Buys |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |'
         '   Tot Profit % |   Avg Duration |   Win  Draw  Loss  Win% |              Drawdown |\n'
-        '|---------------+--------+----------------+----------------+------------------+'
+        '|----------------+--------+----------------+----------------+------------------+'
         '----------------+----------------+-------------------------+-----------------------|\n'
-        '| TestStrategy1 |      3 |          20.00 |          60.00 |       1.10000000 |'
-        '          36.67 |        0:17:00 |     3     0     0   100 | 0.00000000 BTC  0.00% |\n'
-        '| TestStrategy2 |      3 |          30.00 |          90.00 |       1.30000000 |'
-        '          43.33 |        0:20:00 |     3     0     0   100 | 0.00000000 BTC  0.00% |'
+        '| StrategyTestV2 |    179 |           0.08 |          14.39 |       0.02608550 |'
+        '         260.85 |        3:40:00 |   170     0     9  95.0 | 0.00308222 BTC  8.67% |\n'
+        '|   TestStrategy |    179 |           0.08 |          14.39 |       0.02608550 |'
+        '         260.85 |        3:40:00 |   170     0     9  95.0 | 0.00308222 BTC  8.67% |'
     )
 
-    strategy_results = generate_strategy_comparison(all_results=results)
+    strategy_results = generate_strategy_comparison(bt_stats=bt_res_data['strategy'])
+    assert strategy_results == bt_res_data_comparison
     assert text_table_strategy(strategy_results, 'BTC') == result_str
 
 
@@ -377,3 +361,44 @@ def test_generate_edge_table():
     assert generate_edge_table(results).count('| ETH/BTC |') == 1
     assert generate_edge_table(results).count(
         '|   Risk Reward Ratio |   Required Risk Reward |   Expectancy |') == 1
+
+
+def test_generate_periodic_breakdown_stats(testdatadir):
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
+    bt_data = load_backtest_data(filename).to_dict(orient='records')
+
+    res = generate_periodic_breakdown_stats(bt_data, 'day')
+    assert isinstance(res, list)
+    assert len(res) == 21
+    day = res[0]
+    assert 'date' in day
+    assert 'draws' in day
+    assert 'loses' in day
+    assert 'wins' in day
+    assert 'profit_abs' in day
+
+    # Select empty dataframe!
+    res = generate_periodic_breakdown_stats([], 'day')
+    assert res == []
+
+
+def test__get_resample_from_period():
+
+    assert _get_resample_from_period('day') == '1d'
+    assert _get_resample_from_period('week') == '1w'
+    assert _get_resample_from_period('month') == '1M'
+    with pytest.raises(ValueError, match=r"Period noooo is not supported."):
+        _get_resample_from_period('noooo')
+
+
+def test_show_sorted_pairlist(testdatadir, default_conf, capsys):
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
+    bt_data = load_backtest_stats(filename)
+    default_conf['backtest_show_pair_list'] = True
+
+    show_sorted_pairlist(default_conf, bt_data)
+
+    out, err = capsys.readouterr()
+    assert 'Pairs for Strategy StrategyTestV3: \n[' in out
+    assert 'TOTAL' not in out
+    assert '"ETH/BTC",  // ' in out
diff --git a/tests/plugins/test_pairlist.py b/tests/plugins/test_pairlist.py
index 1ce8d172c..d80f23c8a 100644
--- a/tests/plugins/test_pairlist.py
+++ b/tests/plugins/test_pairlist.py
@@ -1,19 +1,22 @@
 # pragma pylint: disable=missing-docstring,C0103,protected-access
 
+import logging
 import time
 from unittest.mock import MagicMock, PropertyMock
 
+import pandas as pd
 import pytest
 import time_machine
 
 from freqtrade.constants import AVAILABLE_PAIRLISTS
+from freqtrade.enums import CandleType, RunMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.persistence import Trade
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.plugins.pairlistmanager import PairListManager
 from freqtrade.resolvers import PairListResolver
-from tests.conftest import (create_mock_trades, get_patched_exchange, get_patched_freqtradebot,
-                            log_has, log_has_re)
+from tests.conftest import (create_mock_trades_usdt, get_patched_exchange, get_patched_freqtradebot,
+                            log_has, log_has_re, num_log_has)
 
 
 @pytest.fixture(scope="function")
@@ -131,9 +134,9 @@ def test_load_pairlist_noexist(mocker, markets, default_conf):
                                        default_conf, {}, 1)
 
 
-def test_load_pairlist_verify_multi(mocker, markets, default_conf):
+def test_load_pairlist_verify_multi(mocker, markets_static, default_conf):
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
+    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets_static))
     plm = PairListManager(freqtrade.exchange, default_conf)
     # Call different versions one after the other, should always consider what was passed in
     # and have no side-effects (therefore the same check multiple times)
@@ -216,6 +219,34 @@ def test_invalid_blacklist(mocker, markets, static_pl_conf, caplog):
     log_has_re(r"Pair blacklist contains an invalid Wildcard.*", caplog)
 
 
+def test_remove_logs_for_pairs_already_in_blacklist(mocker, markets, static_pl_conf, caplog):
+    logger = logging.getLogger(__name__)
+    freqtrade = get_patched_freqtradebot(mocker, static_pl_conf)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        exchange_has=MagicMock(return_value=True),
+        markets=PropertyMock(return_value=markets),
+    )
+    freqtrade.pairlists.refresh_pairlist()
+    whitelist = ['ETH/BTC', 'TKN/BTC']
+    caplog.clear()
+    caplog.set_level(logging.INFO)
+
+    # Ensure all except those in whitelist are removed.
+    assert set(whitelist) == set(freqtrade.pairlists.whitelist)
+    assert static_pl_conf['exchange']['pair_blacklist'] == freqtrade.pairlists.blacklist
+    # Ensure that log message wasn't generated.
+    assert not log_has('Pair BLK/BTC in your blacklist. Removing it from whitelist...', caplog)
+
+    for _ in range(3):
+        new_whitelist = freqtrade.pairlists.verify_blacklist(
+            whitelist + ['BLK/BTC'], logger.warning)
+        # Ensure that the pair is removed from the white list, and properly logged.
+        assert set(whitelist) == set(new_whitelist)
+    assert num_log_has('Pair BLK/BTC in your blacklist. Removing it from whitelist...',
+                       caplog) == 1
+
+
 def test_refresh_pairlist_dynamic(mocker, shitcoinmarkets, tickers, whitelist_conf):
 
     mocker.patch.multiple(
@@ -415,10 +446,10 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
     # SpreadFilter only
     ([{"method": "SpreadFilter", "max_spread_ratio": 0.005}],
      "BTC", 'filter_at_the_beginning'),  # OperationalException expected
-    # Static Pairlist after VolumePairList, on a non-first position
-    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+    # Static Pairlist after VolumePairList, on a non-first position (appends pairs)
+    ([{"method": "VolumePairList", "number_assets": 2, "sort_key": "quoteVolume"},
       {"method": "StaticPairList"}],
-        "BTC", 'static_in_the_middle'),
+        "BTC", ['ETH/BTC', 'TKN/BTC', 'TRST/BTC', 'SWT/BTC', 'BCC/BTC', 'HOT/BTC']),
     ([{"method": "VolumePairList", "number_assets": 20, "sort_key": "quoteVolume"},
       {"method": "PriceFilter", "low_price_ratio": 0.02}],
         "USDT", ['ETH/USDT', 'NANO/USDT']),
@@ -460,22 +491,15 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
     ohlcv_history_high_vola.loc[ohlcv_history_high_vola.index == 1, 'close'] = 0.00090
 
     ohlcv_data = {
-        ('ETH/BTC', '1d'): ohlcv_history,
-        ('TKN/BTC', '1d'): ohlcv_history,
-        ('LTC/BTC', '1d'): ohlcv_history.append(ohlcv_history),
-        ('XRP/BTC', '1d'): ohlcv_history,
-        ('HOT/BTC', '1d'): ohlcv_history_high_vola,
+        ('ETH/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('TKN/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('LTC/BTC', '1d', CandleType.SPOT): pd.concat([ohlcv_history, ohlcv_history]),
+        ('XRP/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('HOT/BTC', '1d', CandleType.SPOT): ohlcv_history_high_vola,
     }
 
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
 
-    if whitelist_result == 'static_in_the_middle':
-        with pytest.raises(OperationalException,
-                           match=r"StaticPairList can only be used in the first position "
-                                 r"in the list of Pairlist Handlers."):
-            freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
-        return
-
     freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
     mocker.patch.multiple('freqtrade.exchange.Exchange',
                           get_tickers=tickers,
@@ -542,36 +566,41 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
                 assert log_has_re(r'^Removed .* from whitelist, because volatility.*$', caplog)
 
 
-@pytest.mark.parametrize("pairlists,base_currency,volumefilter_result", [
+@pytest.mark.parametrize("pairlists,base_currency,exchange,volumefilter_result", [
     # default refresh of 1800 to small for daily candle lookback
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_days": 1}],
-     "BTC", "default_refresh_too_short"),  # OperationalException expected
+     "BTC", "binance", "default_refresh_too_short"),  # OperationalException expected
     # ambigous configuration with lookback days and period
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_days": 1, "lookback_period": 1}],
-     "BTC", "lookback_days_and_period"),  # OperationalException expected
+     "BTC", "binance", "lookback_days_and_period"),  # OperationalException expected
     # negative lookback period
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_timeframe": "1d", "lookback_period": -1}],
-     "BTC", "lookback_period_negative"),  # OperationalException expected
+     "BTC", "binance", "lookback_period_negative"),  # OperationalException expected
     # lookback range exceedes exchange limit
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_timeframe": "1m", "lookback_period": 2000, "refresh_period": 3600}],
-     "BTC", 'lookback_exceeds_exchange_request_size'),  # OperationalException expected
+     "BTC", "binance", "lookback_exceeds_exchange_request_size"),  # OperationalException expected
     # expecing pairs as given
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_timeframe": "1d", "lookback_period": 1, "refresh_period": 86400}],
-     "BTC", ['HOT/BTC', 'LTC/BTC', 'ETH/BTC', 'TKN/BTC', 'XRP/BTC']),
-    # expecting pairs from default tickers, because 1h candles are not available
+     "BTC", "binance", ['LTC/BTC', 'ETH/BTC', 'TKN/BTC', 'XRP/BTC', 'HOT/BTC']),
+    # expecting pairs as input, because 1h candles are not available
     ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
        "lookback_timeframe": "1h", "lookback_period": 2, "refresh_period": 3600}],
-     "BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'HOT/BTC', 'FUEL/BTC']),
+     "BTC", "binance", ['ETH/BTC', 'LTC/BTC', 'NEO/BTC', 'TKN/BTC', 'XRP/BTC']),
+    # ftx data is already in Quote currency, therefore won't require conversion
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
+       "lookback_timeframe": "1d", "lookback_period": 1, "refresh_period": 86400}],
+     "BTC", "ftx", ['HOT/BTC', 'LTC/BTC', 'ETH/BTC', 'TKN/BTC', 'XRP/BTC']),
 ])
 def test_VolumePairList_range(mocker, whitelist_conf, shitcoinmarkets, tickers, ohlcv_history,
-                              pairlists, base_currency, volumefilter_result, caplog) -> None:
+                              pairlists, base_currency, exchange, volumefilter_result) -> None:
     whitelist_conf['pairlists'] = pairlists
     whitelist_conf['stake_currency'] = base_currency
+    whitelist_conf['exchange']['name'] = exchange
 
     ohlcv_history_high_vola = ohlcv_history.copy()
     ohlcv_history_high_vola.loc[ohlcv_history_high_vola.index == 1, 'close'] = 0.00090
@@ -580,16 +609,21 @@ def test_VolumePairList_range(mocker, whitelist_conf, shitcoinmarkets, tickers,
     ohlcv_history_medium_volume = ohlcv_history.copy()
     ohlcv_history_medium_volume.loc[ohlcv_history_medium_volume.index == 2, 'volume'] = 5
 
-    # create candles for high volume with all candles high volume
+    # create candles for high volume with all candles high volume, but very low price.
     ohlcv_history_high_volume = ohlcv_history.copy()
     ohlcv_history_high_volume.loc[:, 'volume'] = 10
+    ohlcv_history_high_volume.loc[:, 'low'] = ohlcv_history_high_volume.loc[:, 'low'] * 0.01
+    ohlcv_history_high_volume.loc[:, 'high'] = ohlcv_history_high_volume.loc[:, 'high'] * 0.01
+    ohlcv_history_high_volume.loc[:, 'close'] = ohlcv_history_high_volume.loc[:, 'close'] * 0.01
+
+    mocker.patch('freqtrade.exchange.ftx.Ftx.market_is_tradable', return_value=True)
 
     ohlcv_data = {
-        ('ETH/BTC', '1d'): ohlcv_history,
-        ('TKN/BTC', '1d'): ohlcv_history,
-        ('LTC/BTC', '1d'): ohlcv_history_medium_volume,
-        ('XRP/BTC', '1d'): ohlcv_history_high_vola,
-        ('HOT/BTC', '1d'): ohlcv_history_high_volume,
+        ('ETH/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('TKN/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('LTC/BTC', '1d', CandleType.SPOT): ohlcv_history_medium_volume,
+        ('XRP/BTC', '1d', CandleType.SPOT): ohlcv_history_high_vola,
+        ('HOT/BTC', '1d', CandleType.SPOT): ohlcv_history_high_volume,
     }
 
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
@@ -664,29 +698,75 @@ def test_PerformanceFilter_error(mocker, whitelist_conf, caplog) -> None:
     assert log_has("PerformanceFilter is not available in this mode.", caplog)
 
 
-@pytest.mark.usefixtures("init_persistence")
-def test_PerformanceFilter_lookback(mocker, whitelist_conf, fee) -> None:
-    whitelist_conf['exchange']['pair_whitelist'].append('XRP/BTC')
+def test_ShuffleFilter_init(mocker, whitelist_conf, caplog) -> None:
     whitelist_conf['pairlists'] = [
         {"method": "StaticPairList"},
-        {"method": "PerformanceFilter", "minutes": 60}
+        {"method": "ShuffleFilter", "seed": 42}
+    ]
+
+    exchange = get_patched_exchange(mocker, whitelist_conf)
+    PairListManager(exchange, whitelist_conf)
+    assert log_has("Backtesting mode detected, applying seed value: 42", caplog)
+    caplog.clear()
+    whitelist_conf['runmode'] = RunMode.DRY_RUN
+    PairListManager(exchange, whitelist_conf)
+    assert not log_has("Backtesting mode detected, applying seed value: 42", caplog)
+    assert log_has("Live mode detected, not applying seed.", caplog)
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_PerformanceFilter_lookback(mocker, default_conf_usdt, fee, caplog) -> None:
+    default_conf_usdt['exchange']['pair_whitelist'].extend(['ADA/USDT', 'XRP/USDT', 'ETC/USDT'])
+    default_conf_usdt['pairlists'] = [
+        {"method": "StaticPairList"},
+        {"method": "PerformanceFilter", "minutes": 60, "min_profit": 0.01}
     ]
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
-    exchange = get_patched_exchange(mocker, whitelist_conf)
-    pm = PairListManager(exchange, whitelist_conf)
+    exchange = get_patched_exchange(mocker, default_conf_usdt)
+    pm = PairListManager(exchange, default_conf_usdt)
     pm.refresh_pairlist()
 
-    assert pm.whitelist == ['ETH/BTC', 'TKN/BTC', 'XRP/BTC']
+    assert pm.whitelist == ['ETH/USDT', 'XRP/USDT', 'NEO/USDT', 'TKN/USDT']
 
     with time_machine.travel("2021-09-01 05:00:00 +00:00") as t:
-        create_mock_trades(fee)
+        create_mock_trades_usdt(fee)
         pm.refresh_pairlist()
-        assert pm.whitelist == ['XRP/BTC', 'ETH/BTC', 'TKN/BTC']
+        assert pm.whitelist == ['XRP/USDT']
+        assert log_has_re(r'Removing pair .* since .* is below .*', caplog)
 
         # Move to "outside" of lookback window, so original sorting is restored.
         t.move_to("2021-09-01 07:00:00 +00:00")
         pm.refresh_pairlist()
-        assert pm.whitelist == ['ETH/BTC', 'TKN/BTC', 'XRP/BTC']
+        assert pm.whitelist == ['ETH/USDT', 'XRP/USDT', 'NEO/USDT', 'TKN/USDT']
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_PerformanceFilter_keep_mid_order(mocker, default_conf_usdt, fee, caplog) -> None:
+    default_conf_usdt['exchange']['pair_whitelist'].extend(['ADA/USDT', 'ETC/USDT'])
+    default_conf_usdt['pairlists'] = [
+        {"method": "StaticPairList", "allow_inactive": True},
+        {"method": "PerformanceFilter", "minutes": 60, }
+    ]
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    exchange = get_patched_exchange(mocker, default_conf_usdt)
+    pm = PairListManager(exchange, default_conf_usdt)
+    pm.refresh_pairlist()
+
+    assert pm.whitelist == ['ETH/USDT', 'LTC/USDT', 'XRP/USDT',
+                            'NEO/USDT', 'TKN/USDT', 'ADA/USDT', 'ETC/USDT']
+
+    with time_machine.travel("2021-09-01 05:00:00 +00:00") as t:
+        create_mock_trades_usdt(fee)
+        pm.refresh_pairlist()
+        assert pm.whitelist == ['XRP/USDT', 'ETC/USDT', 'ETH/USDT',
+                                'NEO/USDT', 'TKN/USDT', 'ADA/USDT', 'LTC/USDT']
+        # assert log_has_re(r'Removing pair .* since .* is below .*', caplog)
+
+        # Move to "outside" of lookback window, so original sorting is restored.
+        t.move_to("2021-09-01 07:00:00 +00:00")
+        pm.refresh_pairlist()
+        assert pm.whitelist == ['ETH/USDT', 'LTC/USDT', 'XRP/USDT',
+                                'NEO/USDT', 'TKN/USDT', 'ADA/USDT', 'ETC/USDT']
 
 
 def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None:
@@ -702,6 +782,19 @@ def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None
         get_patched_freqtradebot(mocker, default_conf)
 
 
+def test_pair_whitelist_not_supported_Spread(mocker, default_conf, tickers) -> None:
+    default_conf['pairlists'] = [{'method': 'StaticPairList'}, {'method': 'SpreadFilter'}]
+
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          get_tickers=tickers,
+                          exchange_has=MagicMock(return_value=False),
+                          )
+
+    with pytest.raises(OperationalException,
+                       match=r'Exchange does not support fetchTickers, .*'):
+        get_patched_freqtradebot(mocker, default_conf)
+
+
 @pytest.mark.parametrize("pairlist", AVAILABLE_PAIRLISTS)
 def test_pairlist_class(mocker, whitelist_conf, markets, pairlist):
     whitelist_conf['pairlists'][0]['method'] = pairlist
@@ -844,9 +937,9 @@ def test_agefilter_min_days_listed_too_large(mocker, default_conf, markets, tick
 def test_agefilter_caching(mocker, markets, whitelist_conf_agefilter, tickers, ohlcv_history):
     with time_machine.travel("2021-09-01 05:00:00 +00:00") as t:
         ohlcv_data = {
-            ('ETH/BTC', '1d'): ohlcv_history,
-            ('TKN/BTC', '1d'): ohlcv_history,
-            ('LTC/BTC', '1d'): ohlcv_history,
+            ('ETH/BTC', '1d', CandleType.SPOT): ohlcv_history,
+            ('TKN/BTC', '1d', CandleType.SPOT): ohlcv_history,
+            ('LTC/BTC', '1d', CandleType.SPOT): ohlcv_history,
         }
         mocker.patch.multiple(
             'freqtrade.exchange.Exchange',
@@ -868,10 +961,10 @@ def test_agefilter_caching(mocker, markets, whitelist_conf_agefilter, tickers, o
         assert freqtrade.exchange.refresh_latest_ohlcv.call_count == 2
 
         ohlcv_data = {
-            ('ETH/BTC', '1d'): ohlcv_history,
-            ('TKN/BTC', '1d'): ohlcv_history,
-            ('LTC/BTC', '1d'): ohlcv_history,
-            ('XRP/BTC', '1d'): ohlcv_history.iloc[[0]],
+            ('ETH/BTC', '1d', CandleType.SPOT): ohlcv_history,
+            ('TKN/BTC', '1d', CandleType.SPOT): ohlcv_history,
+            ('LTC/BTC', '1d', CandleType.SPOT): ohlcv_history,
+            ('XRP/BTC', '1d', CandleType.SPOT): ohlcv_history.iloc[[0]],
         }
         mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv', return_value=ohlcv_data)
         freqtrade.pairlists.refresh_pairlist()
@@ -889,10 +982,10 @@ def test_agefilter_caching(mocker, markets, whitelist_conf_agefilter, tickers, o
         t.move_to("2021-09-03 01:00:00 +00:00")
         # Called once for XRP/BTC
         ohlcv_data = {
-            ('ETH/BTC', '1d'): ohlcv_history,
-            ('TKN/BTC', '1d'): ohlcv_history,
-            ('LTC/BTC', '1d'): ohlcv_history,
-            ('XRP/BTC', '1d'): ohlcv_history,
+            ('ETH/BTC', '1d', CandleType.SPOT): ohlcv_history,
+            ('TKN/BTC', '1d', CandleType.SPOT): ohlcv_history,
+            ('LTC/BTC', '1d', CandleType.SPOT): ohlcv_history,
+            ('XRP/BTC', '1d', CandleType.SPOT): ohlcv_history,
         }
         mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv', return_value=ohlcv_data)
         freqtrade.pairlists.refresh_pairlist()
@@ -953,12 +1046,12 @@ def test_rangestabilityfilter_caching(mocker, markets, default_conf, tickers, oh
                           get_tickers=tickers
                           )
     ohlcv_data = {
-        ('ETH/BTC', '1d'): ohlcv_history,
-        ('TKN/BTC', '1d'): ohlcv_history,
-        ('LTC/BTC', '1d'): ohlcv_history,
-        ('XRP/BTC', '1d'): ohlcv_history,
-        ('HOT/BTC', '1d'): ohlcv_history,
-        ('BLK/BTC', '1d'): ohlcv_history,
+        ('ETH/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('TKN/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('LTC/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('XRP/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('HOT/BTC', '1d', CandleType.SPOT): ohlcv_history,
+        ('BLK/BTC', '1d', CandleType.SPOT): ohlcv_history,
     }
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
@@ -1095,34 +1188,35 @@ def test_pairlistmanager_no_pairlist(mocker, whitelist_conf):
     # Happy path: Descending order, all values filled
     ([{"method": "StaticPairList"}, {"method": "PerformanceFilter"}],
      ['ETH/BTC', 'TKN/BTC'],
-     [{'pair': 'TKN/BTC', 'profit': 5, 'count': 3}, {'pair': 'ETH/BTC', 'profit': 4, 'count': 2}],
+     [{'pair': 'TKN/BTC', 'profit_ratio': 0.05, 'count': 3},
+      {'pair': 'ETH/BTC', 'profit_ratio': 0.04, 'count': 2}],
      ['TKN/BTC', 'ETH/BTC']),
     # Performance data outside allow list ignored
     ([{"method": "StaticPairList"}, {"method": "PerformanceFilter"}],
      ['ETH/BTC', 'TKN/BTC'],
-     [{'pair': 'OTHER/BTC', 'profit': 5, 'count': 3},
-      {'pair': 'ETH/BTC', 'profit': 4, 'count': 2}],
+     [{'pair': 'OTHER/BTC', 'profit_ratio': 0.05, 'count': 3},
+      {'pair': 'ETH/BTC', 'profit_ratio': 0.04, 'count': 2}],
      ['ETH/BTC', 'TKN/BTC']),
     # Partial performance data missing and sorted between positive and negative profit
     ([{"method": "StaticPairList"}, {"method": "PerformanceFilter"}],
      ['ETH/BTC', 'TKN/BTC', 'LTC/BTC'],
-     [{'pair': 'ETH/BTC', 'profit': -5, 'count': 100},
-      {'pair': 'TKN/BTC', 'profit': 4, 'count': 2}],
+     [{'pair': 'ETH/BTC', 'profit_ratio': -0.05, 'count': 100},
+      {'pair': 'TKN/BTC', 'profit_ratio': 0.04, 'count': 2}],
      ['TKN/BTC', 'LTC/BTC', 'ETH/BTC']),
     # Tie in performance data broken by count (ascending)
     ([{"method": "StaticPairList"}, {"method": "PerformanceFilter"}],
      ['ETH/BTC', 'TKN/BTC', 'LTC/BTC'],
-     [{'pair': 'LTC/BTC', 'profit': -5.01, 'count': 101},
-      {'pair': 'TKN/BTC', 'profit': -5.01, 'count': 2},
-      {'pair': 'ETH/BTC', 'profit': -5.01, 'count': 100}],
+     [{'pair': 'LTC/BTC', 'profit_ratio': -0.0501, 'count': 101},
+      {'pair': 'TKN/BTC', 'profit_ratio': -0.0501, 'count': 2},
+      {'pair': 'ETH/BTC', 'profit_ratio': -0.0501, 'count': 100}],
      ['TKN/BTC', 'ETH/BTC', 'LTC/BTC']),
-    # Tie in performance and count, broken by alphabetical sort
+    # Tie in performance and count, broken by prior sorting sort
     ([{"method": "StaticPairList"}, {"method": "PerformanceFilter"}],
      ['ETH/BTC', 'TKN/BTC', 'LTC/BTC'],
-     [{'pair': 'LTC/BTC', 'profit': -5.01, 'count': 1},
-      {'pair': 'TKN/BTC', 'profit': -5.01, 'count': 1},
-      {'pair': 'ETH/BTC', 'profit': -5.01, 'count': 1}],
-     ['ETH/BTC', 'LTC/BTC', 'TKN/BTC']),
+     [{'pair': 'LTC/BTC', 'profit_ratio': -0.0501, 'count': 1},
+      {'pair': 'TKN/BTC', 'profit_ratio': -0.0501, 'count': 1},
+      {'pair': 'ETH/BTC', 'profit_ratio': -0.0501, 'count': 1}],
+     ['ETH/BTC', 'TKN/BTC', 'LTC/BTC']),
 ])
 def test_performance_filter(mocker, whitelist_conf, pairlists, pair_allowlist, overall_performance,
                             allowlist_result, tickers, markets, ohlcv_history_list):
diff --git a/tests/plugins/test_pairlocks.py b/tests/plugins/test_pairlocks.py
index c694fd7c1..f9e5583ed 100644
--- a/tests/plugins/test_pairlocks.py
+++ b/tests/plugins/test_pairlocks.py
@@ -116,3 +116,28 @@ def test_PairLocks_getlongestlock(use_db):
 
     PairLocks.reset_locks()
     PairLocks.use_db = True
+
+
+@pytest.mark.parametrize('use_db', (False, True))
+@pytest.mark.usefixtures("init_persistence")
+def test_PairLocks_reason(use_db):
+    PairLocks.timeframe = '5m'
+    PairLocks.use_db = use_db
+    # No lock should be present
+    if use_db:
+        assert len(PairLock.query.all()) == 0
+
+    assert PairLocks.use_db == use_db
+
+    PairLocks.lock_pair('XRP/USDT', arrow.utcnow().shift(minutes=4).datetime, 'TestLock1')
+    PairLocks.lock_pair('ETH/USDT', arrow.utcnow().shift(minutes=4).datetime, 'TestLock2')
+
+    assert PairLocks.is_pair_locked('XRP/USDT')
+    assert PairLocks.is_pair_locked('ETH/USDT')
+
+    PairLocks.unlock_reason('TestLock1')
+    assert not PairLocks.is_pair_locked('XRP/USDT')
+    assert PairLocks.is_pair_locked('ETH/USDT')
+
+    PairLocks.reset_locks()
+    PairLocks.use_db = True
diff --git a/tests/plugins/test_protections.py b/tests/plugins/test_protections.py
index a3cb29c9d..6b69f5481 100644
--- a/tests/plugins/test_protections.py
+++ b/tests/plugins/test_protections.py
@@ -4,14 +4,14 @@ from datetime import datetime, timedelta
 import pytest
 
 from freqtrade import constants
-from freqtrade.enums import SellType
+from freqtrade.enums import ExitType
 from freqtrade.persistence import PairLocks, Trade
 from freqtrade.plugins.protectionmanager import ProtectionManager
 from tests.conftest import get_patched_freqtradebot, log_has_re
 
 
 def generate_mock_trade(pair: str, fee: float, is_open: bool,
-                        sell_reason: str = SellType.SELL_SIGNAL,
+                        sell_reason: str = ExitType.EXIT_SIGNAL,
                         min_ago_open: int = None, min_ago_close: int = None,
                         profit_rate: float = 0.9
                         ):
@@ -32,7 +32,7 @@ def generate_mock_trade(pair: str, fee: float, is_open: bool,
     trade.recalc_open_trade_value()
     if not is_open:
         trade.close(open_rate * profit_rate)
-        trade.sell_reason = sell_reason
+        trade.exit_reason = sell_reason
 
     return trade
 
@@ -91,7 +91,7 @@ def test_stoploss_guard(mocker, default_conf, fee, caplog):
     caplog.clear()
 
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=200, min_ago_close=30,
     ))
 
@@ -100,12 +100,12 @@ def test_stoploss_guard(mocker, default_conf, fee, caplog):
     caplog.clear()
     # This trade does not count, as it's closed too long ago
     Trade.query.session.add(generate_mock_trade(
-        'BCH/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'BCH/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=250, min_ago_close=100,
     ))
 
     Trade.query.session.add(generate_mock_trade(
-        'ETH/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'ETH/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=240, min_ago_close=30,
     ))
     # 3 Trades closed - but the 2nd has been closed too long ago.
@@ -114,7 +114,7 @@ def test_stoploss_guard(mocker, default_conf, fee, caplog):
     caplog.clear()
 
     Trade.query.session.add(generate_mock_trade(
-        'LTC/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'LTC/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=180, min_ago_close=30,
     ))
 
@@ -148,7 +148,7 @@ def test_stoploss_guard_perpair(mocker, default_conf, fee, caplog, only_per_pair
     caplog.clear()
 
     Trade.query.session.add(generate_mock_trade(
-        pair, fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        pair, fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=200, min_ago_close=30, profit_rate=0.9,
     ))
 
@@ -158,12 +158,12 @@ def test_stoploss_guard_perpair(mocker, default_conf, fee, caplog, only_per_pair
     caplog.clear()
     # This trade does not count, as it's closed too long ago
     Trade.query.session.add(generate_mock_trade(
-        pair, fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        pair, fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=250, min_ago_close=100, profit_rate=0.9,
     ))
     # Trade does not count for per pair stop as it's the wrong pair.
     Trade.query.session.add(generate_mock_trade(
-        'ETH/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'ETH/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=240, min_ago_close=30, profit_rate=0.9,
     ))
     # 3 Trades closed - but the 2nd has been closed too long ago.
@@ -178,7 +178,7 @@ def test_stoploss_guard_perpair(mocker, default_conf, fee, caplog, only_per_pair
 
     # 2nd Trade that counts with correct pair
     Trade.query.session.add(generate_mock_trade(
-        pair, fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        pair, fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=180, min_ago_close=30, profit_rate=0.9,
     ))
 
@@ -203,7 +203,7 @@ def test_CooldownPeriod(mocker, default_conf, fee, caplog):
     caplog.clear()
 
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=200, min_ago_close=30,
     ))
 
@@ -213,7 +213,7 @@ def test_CooldownPeriod(mocker, default_conf, fee, caplog):
     assert not PairLocks.is_global_lock()
 
     Trade.query.session.add(generate_mock_trade(
-        'ETH/BTC', fee.return_value, False, sell_reason=SellType.ROI.value,
+        'ETH/BTC', fee.return_value, False, sell_reason=ExitType.ROI.value,
         min_ago_open=205, min_ago_close=35,
     ))
 
@@ -242,7 +242,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog):
     caplog.clear()
 
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=800, min_ago_close=450, profit_rate=0.9,
     ))
 
@@ -253,7 +253,7 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog):
     assert not PairLocks.is_global_lock()
 
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=200, min_ago_close=120, profit_rate=0.9,
     ))
 
@@ -265,14 +265,14 @@ def test_LowProfitPairs(mocker, default_conf, fee, caplog):
 
     # Add positive trade
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.ROI.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.ROI.value,
         min_ago_open=20, min_ago_close=10, profit_rate=1.15,
     ))
     assert not freqtrade.protections.stop_per_pair('XRP/BTC')
     assert not PairLocks.is_pair_locked('XRP/BTC')
 
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=110, min_ago_close=20, profit_rate=0.8,
     ))
 
@@ -300,15 +300,15 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog):
     caplog.clear()
 
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=1000, min_ago_close=900, profit_rate=1.1,
     ))
     Trade.query.session.add(generate_mock_trade(
-        'ETH/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'ETH/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=1000, min_ago_close=900, profit_rate=1.1,
     ))
     Trade.query.session.add(generate_mock_trade(
-        'NEO/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'NEO/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=1000, min_ago_close=900, profit_rate=1.1,
     ))
     # No losing trade yet ... so max_drawdown will raise exception
@@ -316,7 +316,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog):
     assert not freqtrade.protections.stop_per_pair('XRP/BTC')
 
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=500, min_ago_close=400, profit_rate=0.9,
     ))
     # Not locked with one trade
@@ -326,7 +326,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog):
     assert not PairLocks.is_global_lock()
 
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.STOP_LOSS.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.STOP_LOSS.value,
         min_ago_open=1200, min_ago_close=1100, profit_rate=0.5,
     ))
 
@@ -339,7 +339,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog):
 
     # Winning trade ... (should not lock, does not change drawdown!)
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.ROI.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.ROI.value,
         min_ago_open=320, min_ago_close=410, profit_rate=1.5,
     ))
     assert not freqtrade.protections.global_stop()
@@ -349,7 +349,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog):
 
     # Add additional negative trade, causing a loss of > 15%
     Trade.query.session.add(generate_mock_trade(
-        'XRP/BTC', fee.return_value, False, sell_reason=SellType.ROI.value,
+        'XRP/BTC', fee.return_value, False, sell_reason=ExitType.ROI.value,
         min_ago_open=20, min_ago_close=10, profit_rate=0.8,
     ))
     assert not freqtrade.protections.stop_per_pair('XRP/BTC')
diff --git a/tests/rpc/test_fiat_convert.py b/tests/rpc/test_fiat_convert.py
index 2fe5d4a56..0dfa20185 100644
--- a/tests/rpc/test_fiat_convert.py
+++ b/tests/rpc/test_fiat_convert.py
@@ -137,7 +137,7 @@ def test_fiat_too_many_requests_response(mocker, caplog):
     assert len(fiat_convert._coinlistings) == 0
     assert fiat_convert._backoff > datetime.datetime.now().timestamp()
     assert log_has(
-        'Too many requests for Coingecko API, backing off and trying again later.',
+        'Too many requests for CoinGecko API, backing off and trying again later.',
         caplog
     )
 
@@ -148,12 +148,15 @@ def test_fiat_multiple_coins(mocker, caplog):
         {'id': 'helium', 'symbol': 'hnt', 'name': 'Helium'},
         {'id': 'hymnode', 'symbol': 'hnt', 'name': 'Hymnode'},
         {'id': 'bitcoin', 'symbol': 'btc', 'name': 'Bitcoin'},
+        {'id': 'ethereum', 'symbol': 'eth', 'name': 'Ethereum'},
+        {'id': 'ethereum-wormhole', 'symbol': 'eth', 'name': 'Ethereum Wormhole'},
     ]
 
     assert fiat_convert._get_gekko_id('btc') == 'bitcoin'
     assert fiat_convert._get_gekko_id('hnt') is None
+    assert fiat_convert._get_gekko_id('eth') == 'ethereum'
 
-    assert log_has('Found multiple mappings in goingekko for hnt.', caplog)
+    assert log_has('Found multiple mappings in CoinGecko for hnt.', caplog)
 
 
 def test_fiat_invalid_response(mocker, caplog):
diff --git a/tests/rpc/test_rpc.py b/tests/rpc/test_rpc.py
index 0ba42c4ce..f4a2f6099 100644
--- a/tests/rpc/test_rpc.py
+++ b/tests/rpc/test_rpc.py
@@ -8,9 +8,10 @@ import pytest
 from numpy import isnan
 
 from freqtrade.edge import PairInfo
-from freqtrade.enums import State
+from freqtrade.enums import SignalDirection, State, TradingMode
 from freqtrade.exceptions import ExchangeError, InvalidOrderException, TemporaryError
 from freqtrade.persistence import Trade
+from freqtrade.persistence.models import Order
 from freqtrade.persistence.pairlock_middleware import PairLocks
 from freqtrade.rpc import RPC, RPCException
 from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
@@ -51,7 +52,8 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
     assert results[0] == {
         'trade_id': 1,
         'pair': 'ETH/BTC',
-        'base_currency': 'BTC',
+        'base_currency': 'ETH',
+        'quote_currency': 'BTC',
         'open_date': ANY,
         'open_timestamp': ANY,
         'is_open': ANY,
@@ -65,11 +67,13 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'open_trade_value': 0.0010025,
         'close_rate_requested': ANY,
         'sell_reason': ANY,
-        'sell_order_status': ANY,
+        'exit_reason': ANY,
+        'exit_order_status': ANY,
         'min_rate': ANY,
         'max_rate': ANY,
         'strategy': ANY,
         'buy_tag': ANY,
+        'enter_tag': ANY,
         'timeframe': 5,
         'open_order_id': ANY,
         'close_date': None,
@@ -78,7 +82,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'close_rate': None,
         'current_rate': 1.099e-05,
         'amount': 91.07468123,
-        'amount_requested': 91.07468123,
+        'amount_requested': 91.07468124,
         'stake_amount': 0.001,
         'trade_duration': None,
         'trade_duration_s': None,
@@ -108,6 +112,20 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'stoploss_entry_dist_ratio': -0.10448878,
         'open_order': None,
         'exchange': 'binance',
+        'leverage': 1.0,
+        'interest_rate': 0.0,
+        'liquidation_price': None,
+        'is_short': False,
+        'funding_fees': 0.0,
+        'trading_mode': TradingMode.SPOT,
+        'orders': [{
+            'amount': 91.07468123, 'average': 1.098e-05, 'safe_price': 1.098e-05,
+            'cost': 0.0009999999999054, 'filled': 91.07468123, 'ft_order_side': 'buy',
+            'order_date': ANY, 'order_timestamp': ANY, 'order_filled_date': ANY,
+            'order_filled_timestamp': ANY, 'order_type': 'limit', 'price': 1.098e-05,
+            'is_open': False, 'pair': 'ETH/BTC', 'order_id': ANY,
+            'remaining': ANY, 'status': ANY, 'ft_is_entry': True,
+        }],
     }
 
     mocker.patch('freqtrade.exchange.Exchange.get_rate',
@@ -118,7 +136,8 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
     assert results[0] == {
         'trade_id': 1,
         'pair': 'ETH/BTC',
-        'base_currency': 'BTC',
+        'base_currency': 'ETH',
+        'quote_currency': 'BTC',
         'open_date': ANY,
         'open_timestamp': ANY,
         'is_open': ANY,
@@ -132,11 +151,13 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'open_trade_value': ANY,
         'close_rate_requested': ANY,
         'sell_reason': ANY,
-        'sell_order_status': ANY,
+        'exit_reason': ANY,
+        'exit_order_status': ANY,
         'min_rate': ANY,
         'max_rate': ANY,
         'strategy': ANY,
         'buy_tag': ANY,
+        'enter_tag': ANY,
         'timeframe': ANY,
         'open_order_id': ANY,
         'close_date': None,
@@ -145,7 +166,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'close_rate': None,
         'current_rate': ANY,
         'amount': 91.07468123,
-        'amount_requested': 91.07468123,
+        'amount_requested': 91.07468124,
         'trade_duration': ANY,
         'trade_duration_s': ANY,
         'stake_amount': 0.001,
@@ -175,6 +196,20 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'stoploss_entry_dist_ratio': -0.10448878,
         'open_order': None,
         'exchange': 'binance',
+        'leverage': 1.0,
+        'interest_rate': 0.0,
+        'liquidation_price': None,
+        'is_short': False,
+        'funding_fees': 0.0,
+        'trading_mode': TradingMode.SPOT,
+        'orders': [{
+            'amount': 91.07468123, 'average': 1.098e-05, 'safe_price': 1.098e-05,
+            'cost': 0.0009999999999054, 'filled': 91.07468123, 'ft_order_side': 'buy',
+            'order_date': ANY, 'order_timestamp': ANY, 'order_filled_date': ANY,
+            'order_filled_timestamp': ANY, 'order_type': 'limit', 'price': 1.098e-05,
+            'is_open': False, 'pair': 'ETH/BTC', 'order_id': ANY,
+            'remaining': ANY, 'status': ANY, 'ft_is_entry': True,
+        }],
     }
 
 
@@ -214,11 +249,21 @@ def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None:
     result, headers, fiat_profit_sum = rpc._rpc_status_table(default_conf['stake_currency'], 'USD')
     assert "Since" in headers
     assert "Pair" in headers
+    assert len(result[0]) == 4
     assert 'instantly' == result[0][2]
     assert 'ETH/BTC' in result[0][1]
     assert '-0.41% (-0.06)' == result[0][3]
     assert '-0.06' == f'{fiat_profit_sum:.2f}'
 
+    rpc._config['position_adjustment_enable'] = True
+    rpc._config['max_entry_position_adjustment'] = 3
+    result, headers, fiat_profit_sum = rpc._rpc_status_table(default_conf['stake_currency'], 'USD')
+    assert "# Entries" in headers
+    assert len(result[0]) == 5
+    # 4th column should be 1/4 - as 1 order filled (a total of 4 is possible)
+    # 3 on top of the initial one.
+    assert result[0][4] == '1/4'
+
     mocker.patch('freqtrade.exchange.Exchange.get_rate',
                  MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available")))
     result, headers, fiat_profit_sum = rpc._rpc_status_table(default_conf['stake_currency'], 'USD')
@@ -251,8 +296,10 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
     assert trade
 
     # Simulate buy & sell
-    trade.update(limit_buy_order)
-    trade.update(limit_sell_order)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
     trade.close_date = datetime.utcnow()
     trade.is_open = False
 
@@ -277,7 +324,8 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
         rpc._rpc_daily_profit(0, stake_currency, fiat_display_currency)
 
 
-def test_rpc_trade_history(mocker, default_conf, markets, fee):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_rpc_trade_history(mocker, default_conf, markets, fee, is_short):
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
@@ -285,7 +333,7 @@ def test_rpc_trade_history(mocker, default_conf, markets, fee):
     )
 
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short)
     rpc = RPC(freqtradebot)
     rpc._fiat_converter = CryptoToFiatConverter()
     trades = rpc._rpc_trade_history(2)
@@ -302,7 +350,8 @@ def test_rpc_trade_history(mocker, default_conf, markets, fee):
     assert trades['trades'][0]['pair'] == 'XRP/BTC'
 
 
-def test_rpc_delete_trade(mocker, default_conf, fee, markets, caplog):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_rpc_delete_trade(mocker, default_conf, fee, markets, caplog, is_short):
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     stoploss_mock = MagicMock()
     cancel_mock = MagicMock()
@@ -315,7 +364,7 @@ def test_rpc_delete_trade(mocker, default_conf, fee, markets, caplog):
 
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     freqtradebot.strategy.order_types['stoploss_on_exchange'] = True
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short)
     rpc = RPC(freqtradebot)
     with pytest.raises(RPCException, match='invalid argument'):
         rpc._rpc_delete('200')
@@ -389,28 +438,32 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
     freqtradebot.enter_positions()
     trade = Trade.query.first()
     # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'sell')
+    trade.update_trade(oobj)
 
     # Update the ticker with a market going up
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=ticker_sell_up
     )
-    trade.update(limit_sell_order)
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
     trade.close_date = datetime.utcnow()
     trade.is_open = False
 
     freqtradebot.enter_positions()
     trade = Trade.query.first()
     # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
 
     # Update the ticker with a market going up
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=ticker_sell_up
     )
-    trade.update(limit_sell_order)
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
     trade.close_date = datetime.utcnow()
     trade.is_open = False
 
@@ -424,7 +477,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
     assert stats['trade_count'] == 2
     assert stats['first_trade_date'] == 'just now'
     assert stats['latest_trade_date'] == 'just now'
-    assert stats['avg_duration'] in ('0:00:00', '0:00:01')
+    assert stats['avg_duration'] in ('0:00:00', '0:00:01', '0:00:02')
     assert stats['best_pair'] == 'ETH/BTC'
     assert prec_satoshi(stats['best_rate'], 6.2)
 
@@ -435,7 +488,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
     assert stats['trade_count'] == 2
     assert stats['first_trade_date'] == 'just now'
     assert stats['latest_trade_date'] == 'just now'
-    assert stats['avg_duration'] in ('0:00:00', '0:00:01')
+    assert stats['avg_duration'] in ('0:00:00', '0:00:01', '0:00:02')
     assert stats['best_pair'] == 'ETH/BTC'
     assert prec_satoshi(stats['best_rate'], 6.2)
     assert isnan(stats['profit_all_coin'])
@@ -469,14 +522,16 @@ def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee,
     freqtradebot.enter_positions()
     trade = Trade.query.first()
     # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
     # Update the ticker with a market going up
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=ticker_sell_up,
         get_fee=fee
     )
-    trade.update(limit_sell_order)
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
     trade.close_date = datetime.utcnow()
     trade.is_open = False
 
@@ -551,6 +606,30 @@ def test_rpc_balance_handle(default_conf, mocker, tickers):
             'used': 5.0,
         }
     }
+    mock_pos = [
+        {
+            "symbol": "ETH/USDT:USDT",
+            "timestamp": None,
+            "datetime": None,
+            "initialMargin": 0.0,
+            "initialMarginPercentage": None,
+            "maintenanceMargin": 0.0,
+            "maintenanceMarginPercentage": 0.005,
+            "entryPrice": 0.0,
+            "notional": 100.0,
+            "leverage": 5.0,
+            "unrealizedPnl": 0.0,
+            "contracts": 100.0,
+            "contractSize": 1,
+            "marginRatio": None,
+            "liquidationPrice": 0.0,
+            "markPrice": 2896.41,
+            "collateral": 20,
+            "marginType": "isolated",
+            "side": 'short',
+            "percentage": None
+        }
+    ]
 
     mocker.patch.multiple(
         'freqtrade.rpc.fiat_convert.CoinGeckoAPI',
@@ -560,48 +639,77 @@ def test_rpc_balance_handle(default_conf, mocker, tickers):
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
+        validate_trading_mode_and_margin_mode=MagicMock(),
         get_balances=MagicMock(return_value=mock_balance),
+        fetch_positions=MagicMock(return_value=mock_pos),
         get_tickers=tickers,
         get_valid_pair_combination=MagicMock(
             side_effect=lambda a, b: f"{b}/{a}" if a == "USDT" else f"{a}/{b}")
     )
     default_conf['dry_run'] = False
+    default_conf['trading_mode'] = 'futures'
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot)
     rpc = RPC(freqtradebot)
     rpc._fiat_converter = CryptoToFiatConverter()
 
     result = rpc._rpc_balance(default_conf['stake_currency'], default_conf['fiat_display_currency'])
-    assert prec_satoshi(result['total'], 12.309096315)
-    assert prec_satoshi(result['value'], 184636.44472997)
+    assert prec_satoshi(result['total'], 30.30909624)
+    assert prec_satoshi(result['value'], 454636.44360691)
     assert tickers.call_count == 1
     assert tickers.call_args_list[0][1]['cached'] is True
     assert 'USD' == result['symbol']
     assert result['currencies'] == [
-        {'currency': 'BTC',
-         'free': 10.0,
-         'balance': 12.0,
-         'used': 2.0,
-         'est_stake': 12.0,
-         'stake': 'BTC',
-         },
-        {'free': 1.0,
-         'balance': 5.0,
-         'currency': 'ETH',
-         'est_stake': 0.30794,
-         'used': 4.0,
-         'stake': 'BTC',
+        {
+            'currency': 'BTC',
+            'free': 10.0,
+            'balance': 12.0,
+            'used': 2.0,
+            'est_stake': 10.0,  # In futures mode, "free" is used here.
+            'stake': 'BTC',
+            'is_position': False,
+            'leverage': 1.0,
+            'position': 0.0,
+            'side': 'long',
+        },
+        {
+            'free': 1.0,
+            'balance': 5.0,
+            'currency': 'ETH',
+            'est_stake': 0.30794,
+            'used': 4.0,
+            'stake': 'BTC',
+            'is_position': False,
+            'leverage': 1.0,
+            'position': 0.0,
+            'side': 'long',
 
-         },
-        {'free': 5.0,
-         'balance': 10.0,
-         'currency': 'USDT',
-         'est_stake': 0.0011563153318162476,
-         'used': 5.0,
-         'stake': 'BTC',
-         }
+        },
+        {
+            'free': 5.0,
+            'balance': 10.0,
+            'currency': 'USDT',
+            'est_stake': 0.0011562404610161968,
+            'used': 5.0,
+            'stake': 'BTC',
+            'is_position': False,
+            'leverage': 1.0,
+            'position': 0.0,
+            'side': 'long',
+        },
+        {
+            'free': 0.0,
+            'balance': 0.0,
+            'currency': 'ETH/USDT:USDT',
+            'est_stake': 20,
+            'used': 0,
+            'stake': 'BTC',
+            'is_position': True,
+            'leverage': 5.0,
+            'position': 1000.0,
+            'side': 'short',
+        }
     ]
-    assert result['total'] == 12.309096315331816
 
 
 def test_rpc_start(mocker, default_conf) -> None:
@@ -665,7 +773,7 @@ def test_rpc_stopbuy(mocker, default_conf) -> None:
     assert freqtradebot.config['max_open_trades'] == 0
 
 
-def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
+def test_rpc_force_exit(default_conf, ticker, fee, mocker) -> None:
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
 
     cancel_order_mock = MagicMock()
@@ -692,29 +800,29 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
 
     freqtradebot.state = State.STOPPED
     with pytest.raises(RPCException, match=r'.*trader is not running*'):
-        rpc._rpc_forcesell(None)
+        rpc._rpc_force_exit(None)
 
     freqtradebot.state = State.RUNNING
     with pytest.raises(RPCException, match=r'.*invalid argument*'):
-        rpc._rpc_forcesell(None)
+        rpc._rpc_force_exit(None)
 
-    msg = rpc._rpc_forcesell('all')
+    msg = rpc._rpc_force_exit('all')
     assert msg == {'result': 'Created sell orders for all open trades.'}
 
     freqtradebot.enter_positions()
-    msg = rpc._rpc_forcesell('all')
+    msg = rpc._rpc_force_exit('all')
     assert msg == {'result': 'Created sell orders for all open trades.'}
 
     freqtradebot.enter_positions()
-    msg = rpc._rpc_forcesell('2')
+    msg = rpc._rpc_force_exit('2')
     assert msg == {'result': 'Created sell order for trade 2.'}
 
     freqtradebot.state = State.STOPPED
     with pytest.raises(RPCException, match=r'.*trader is not running*'):
-        rpc._rpc_forcesell(None)
+        rpc._rpc_force_exit(None)
 
     with pytest.raises(RPCException, match=r'.*trader is not running*'):
-        rpc._rpc_forcesell('all')
+        rpc._rpc_force_exit('all')
 
     freqtradebot.state = State.RUNNING
     assert cancel_order_mock.call_count == 0
@@ -728,13 +836,13 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
     mocker.patch(
         'freqtrade.exchange.Exchange.fetch_order',
         side_effect=[{
-            'id': '1234',
+            'id': trade.orders[0].order_id,
             'status': 'open',
             'type': 'limit',
             'side': 'buy',
             'filled': filled_amount
         }, {
-            'id': '1234',
+            'id': trade.orders[0].order_id,
             'status': 'closed',
             'type': 'limit',
             'side': 'buy',
@@ -743,7 +851,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
     )
     # check that the trade is called, which is done by ensuring exchange.cancel_order is called
     # and trade amount is updated
-    rpc._rpc_forcesell('3')
+    rpc._rpc_force_exit('3')
     assert cancel_order_mock.call_count == 1
     assert trade.amount == filled_amount
 
@@ -771,7 +879,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
         }
     )
     # check that the trade is called, which is done by ensuring exchange.cancel_order is called
-    msg = rpc._rpc_forcesell('4')
+    msg = rpc._rpc_force_exit('4')
     assert msg == {'result': 'Created sell order for trade 4.'}
     assert cancel_order_mock.call_count == 2
     assert trade.amount == amount
@@ -788,7 +896,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
             'filled': 0.0
         }
     )
-    msg = rpc._rpc_forcesell('3')
+    msg = rpc._rpc_force_exit('3')
     assert msg == {'result': 'Created sell order for trade 3.'}
     # status quo, no exchange calls
     assert cancel_order_mock.call_count == 3
@@ -814,10 +922,12 @@ def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
     assert trade
 
     # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
 
     # Simulate fulfilled LIMIT_SELL order for trade
-    trade.update(limit_sell_order)
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
 
     trade.close_date = datetime.utcnow()
     trade.is_open = False
@@ -825,7 +935,231 @@ def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
     assert len(res) == 1
     assert res[0]['pair'] == 'ETH/BTC'
     assert res[0]['count'] == 1
-    assert prec_satoshi(res[0]['profit'], 6.2)
+    assert prec_satoshi(res[0]['profit_pct'], 6.2)
+
+
+def test_enter_tag_performance_handle(default_conf, ticker, limit_buy_order, fee,
+                                      limit_sell_order, mocker) -> None:
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value=ticker),
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    patch_get_signal(freqtradebot)
+    rpc = RPC(freqtradebot)
+
+    # Create some test data
+    freqtradebot.enter_positions()
+    trade = Trade.query.first()
+    assert trade
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+
+    # Simulate fulfilled LIMIT_SELL order for trade
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
+
+    trade.close_date = datetime.utcnow()
+    trade.is_open = False
+    res = rpc._rpc_enter_tag_performance(None)
+
+    assert len(res) == 1
+    assert res[0]['enter_tag'] == 'Other'
+    assert res[0]['count'] == 1
+    assert prec_satoshi(res[0]['profit_pct'], 6.2)
+
+    trade.enter_tag = "TEST_TAG"
+    res = rpc._rpc_enter_tag_performance(None)
+
+    assert len(res) == 1
+    assert res[0]['enter_tag'] == 'TEST_TAG'
+    assert res[0]['count'] == 1
+    assert prec_satoshi(res[0]['profit_pct'], 6.2)
+
+
+def test_enter_tag_performance_handle_2(mocker, default_conf, markets, fee):
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        markets=PropertyMock(return_value=markets)
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    create_mock_trades(fee)
+    rpc = RPC(freqtradebot)
+
+    res = rpc._rpc_enter_tag_performance(None)
+
+    assert len(res) == 2
+    assert res[0]['enter_tag'] == 'TEST1'
+    assert res[0]['count'] == 1
+    assert prec_satoshi(res[0]['profit_pct'], 0.5)
+    assert res[1]['enter_tag'] == 'Other'
+    assert res[1]['count'] == 1
+    assert prec_satoshi(res[1]['profit_pct'], 1.0)
+
+    # Test for a specific pair
+    res = rpc._rpc_enter_tag_performance('ETC/BTC')
+    assert len(res) == 1
+    assert res[0]['count'] == 1
+    assert res[0]['enter_tag'] == 'TEST1'
+    assert prec_satoshi(res[0]['profit_pct'], 0.5)
+
+
+def test_exit_reason_performance_handle(default_conf, ticker, limit_buy_order, fee,
+                                        limit_sell_order, mocker) -> None:
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value=ticker),
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    patch_get_signal(freqtradebot)
+    rpc = RPC(freqtradebot)
+
+    # Create some test data
+    freqtradebot.enter_positions()
+    trade = Trade.query.first()
+    assert trade
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+
+    # Simulate fulfilled LIMIT_SELL order for trade
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
+
+    trade.close_date = datetime.utcnow()
+    trade.is_open = False
+    res = rpc._rpc_exit_reason_performance(None)
+
+    assert len(res) == 1
+    assert res[0]['exit_reason'] == 'Other'
+    assert res[0]['count'] == 1
+    assert prec_satoshi(res[0]['profit_pct'], 6.2)
+
+    trade.exit_reason = "TEST1"
+    res = rpc._rpc_exit_reason_performance(None)
+
+    assert len(res) == 1
+    assert res[0]['exit_reason'] == 'TEST1'
+    assert res[0]['count'] == 1
+    assert prec_satoshi(res[0]['profit_pct'], 6.2)
+
+
+def test_exit_reason_performance_handle_2(mocker, default_conf, markets, fee):
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        markets=PropertyMock(return_value=markets)
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    create_mock_trades(fee)
+    rpc = RPC(freqtradebot)
+
+    res = rpc._rpc_exit_reason_performance(None)
+
+    assert len(res) == 2
+    assert res[0]['exit_reason'] == 'sell_signal'
+    assert res[0]['count'] == 1
+    assert prec_satoshi(res[0]['profit_pct'], 0.5)
+    assert res[1]['exit_reason'] == 'roi'
+    assert res[1]['count'] == 1
+    assert prec_satoshi(res[1]['profit_pct'], 1.0)
+
+    # Test for a specific pair
+    res = rpc._rpc_exit_reason_performance('ETC/BTC')
+    assert len(res) == 1
+    assert res[0]['count'] == 1
+    assert res[0]['exit_reason'] == 'sell_signal'
+    assert prec_satoshi(res[0]['profit_pct'], 0.5)
+
+
+def test_mix_tag_performance_handle(default_conf, ticker, limit_buy_order, fee,
+                                    limit_sell_order, mocker) -> None:
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value=ticker),
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    patch_get_signal(freqtradebot)
+    rpc = RPC(freqtradebot)
+
+    # Create some test data
+    freqtradebot.enter_positions()
+    trade = Trade.query.first()
+    assert trade
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+
+    # Simulate fulfilled LIMIT_SELL order for trade
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
+
+    trade.close_date = datetime.utcnow()
+    trade.is_open = False
+    res = rpc._rpc_mix_tag_performance(None)
+
+    assert len(res) == 1
+    assert res[0]['mix_tag'] == 'Other Other'
+    assert res[0]['count'] == 1
+    assert prec_satoshi(res[0]['profit_pct'], 6.2)
+
+    trade.enter_tag = "TESTBUY"
+    trade.exit_reason = "TESTSELL"
+    res = rpc._rpc_mix_tag_performance(None)
+
+    assert len(res) == 1
+    assert res[0]['mix_tag'] == 'TESTBUY TESTSELL'
+    assert res[0]['count'] == 1
+    assert prec_satoshi(res[0]['profit_pct'], 6.2)
+
+
+def test_mix_tag_performance_handle_2(mocker, default_conf, markets, fee):
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        markets=PropertyMock(return_value=markets)
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    create_mock_trades(fee)
+    rpc = RPC(freqtradebot)
+
+    res = rpc._rpc_mix_tag_performance(None)
+
+    assert len(res) == 2
+    assert res[0]['mix_tag'] == 'TEST1 sell_signal'
+    assert res[0]['count'] == 1
+    assert prec_satoshi(res[0]['profit_pct'], 0.5)
+    assert res[1]['mix_tag'] == 'Other roi'
+    assert res[1]['count'] == 1
+    assert prec_satoshi(res[1]['profit_pct'], 1.0)
+
+    # Test for a specific pair
+    res = rpc._rpc_mix_tag_performance('ETC/BTC')
+
+    assert len(res) == 1
+    assert res[0]['count'] == 1
+    assert res[0]['mix_tag'] == 'TEST1 sell_signal'
+    assert prec_satoshi(res[0]['profit_pct'], 0.5)
 
 
 def test_rpc_count(mocker, default_conf, ticker, fee) -> None:
@@ -850,8 +1184,8 @@ def test_rpc_count(mocker, default_conf, ticker, fee) -> None:
     assert counts["current"] == 1
 
 
-def test_rpcforcebuy(mocker, default_conf, ticker, fee, limit_buy_order_open) -> None:
-    default_conf['forcebuy_enable'] = True
+def test_rpc_force_entry(mocker, default_conf, ticker, fee, limit_buy_order_open) -> None:
+    default_conf['force_entry_enable'] = True
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     buy_mm = MagicMock(return_value=limit_buy_order_open)
     mocker.patch.multiple(
@@ -866,16 +1200,16 @@ def test_rpcforcebuy(mocker, default_conf, ticker, fee, limit_buy_order_open) ->
     patch_get_signal(freqtradebot)
     rpc = RPC(freqtradebot)
     pair = 'ETH/BTC'
-    trade = rpc._rpc_forcebuy(pair, None)
+    trade = rpc._rpc_force_entry(pair, None)
     assert isinstance(trade, Trade)
     assert trade.pair == pair
     assert trade.open_rate == ticker()['bid']
 
     # Test buy duplicate
     with pytest.raises(RPCException, match=r'position for ETH/BTC already open - id: 1'):
-        rpc._rpc_forcebuy(pair, 0.0001)
+        rpc._rpc_force_entry(pair, 0.0001)
     pair = 'XRP/BTC'
-    trade = rpc._rpc_forcebuy(pair, 0.0001)
+    trade = rpc._rpc_force_entry(pair, 0.0001, order_type='limit')
     assert isinstance(trade, Trade)
     assert trade.pair == pair
     assert trade.open_rate == 0.0001
@@ -883,21 +1217,27 @@ def test_rpcforcebuy(mocker, default_conf, ticker, fee, limit_buy_order_open) ->
     # Test buy pair not with stakes
     with pytest.raises(RPCException,
                        match=r'Wrong pair selected. Only pairs with stake-currency.*'):
-        rpc._rpc_forcebuy('LTC/ETH', 0.0001)
-    pair = 'XRP/BTC'
+        rpc._rpc_force_entry('LTC/ETH', 0.0001)
+
+    # Test with defined stake_amount
+    pair = 'LTC/BTC'
+    trade = rpc._rpc_force_entry(pair, 0.0001, order_type='limit', stake_amount=0.05)
+    assert trade.stake_amount == 0.05
+    assert trade.buy_tag == 'force_entry'
 
     # Test not buying
+    pair = 'XRP/BTC'
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     freqtradebot.config['stake_amount'] = 0
     patch_get_signal(freqtradebot)
     rpc = RPC(freqtradebot)
     pair = 'TKN/BTC'
-    trade = rpc._rpc_forcebuy(pair, None)
-    assert trade is None
+    with pytest.raises(RPCException, match=r"Failed to enter position for TKN/BTC."):
+        trade = rpc._rpc_force_entry(pair, None)
 
 
-def test_rpcforcebuy_stopped(mocker, default_conf) -> None:
-    default_conf['forcebuy_enable'] = True
+def test_rpc_force_entry_stopped(mocker, default_conf) -> None:
+    default_conf['force_entry_enable'] = True
     default_conf['initial_state'] = 'stopped'
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
 
@@ -906,18 +1246,30 @@ def test_rpcforcebuy_stopped(mocker, default_conf) -> None:
     rpc = RPC(freqtradebot)
     pair = 'ETH/BTC'
     with pytest.raises(RPCException, match=r'trader is not running'):
-        rpc._rpc_forcebuy(pair, None)
+        rpc._rpc_force_entry(pair, None)
 
 
-def test_rpcforcebuy_disabled(mocker, default_conf) -> None:
+def test_rpc_force_entry_disabled(mocker, default_conf) -> None:
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
 
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot)
     rpc = RPC(freqtradebot)
     pair = 'ETH/BTC'
-    with pytest.raises(RPCException, match=r'Forcebuy not enabled.'):
-        rpc._rpc_forcebuy(pair, None)
+    with pytest.raises(RPCException, match=r'Force_entry not enabled.'):
+        rpc._rpc_force_entry(pair, None)
+
+
+def test_rpc_force_entry_wrong_mode(mocker, default_conf) -> None:
+    default_conf['force_entry_enable'] = True
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    patch_get_signal(freqtradebot)
+    rpc = RPC(freqtradebot)
+    pair = 'ETH/BTC'
+    with pytest.raises(RPCException, match="Can't go short on Spot markets."):
+        rpc._rpc_force_entry(pair, None, order_side=SignalDirection.SHORT)
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -1003,7 +1355,17 @@ def test_rpc_blacklist(mocker, default_conf) -> None:
     assert len(ret['blacklist']) == 4
     assert ret['blacklist'] == default_conf['exchange']['pair_blacklist']
     assert ret['blacklist'] == ['DOGE/BTC', 'HOT/BTC', 'ETH/BTC', 'XRP/.*']
-    assert ret['blacklist_expanded'] == ['ETH/BTC', 'XRP/BTC']
+    assert ret['blacklist_expanded'] == ['ETH/BTC', 'XRP/BTC', 'XRP/USDT']
+    assert 'errors' in ret
+    assert isinstance(ret['errors'], dict)
+
+    ret = rpc._rpc_blacklist_delete(["DOGE/BTC", 'HOT/BTC'])
+
+    assert 'StaticPairList' in ret['method']
+    assert len(ret['blacklist']) == 2
+    assert ret['blacklist'] == default_conf['exchange']['pair_blacklist']
+    assert ret['blacklist'] == ['ETH/BTC', 'XRP/.*']
+    assert ret['blacklist_expanded'] == ['ETH/BTC', 'XRP/BTC', 'XRP/USDT']
     assert 'errors' in ret
     assert isinstance(ret['errors'], dict)
 
@@ -1033,3 +1395,13 @@ def test_rpc_edge_enabled(mocker, edge_conf) -> None:
     assert ret[0]['Winrate'] == 0.66
     assert ret[0]['Expectancy'] == 1.71
     assert ret[0]['Stoploss'] == -0.02
+
+
+def test_rpc_health(mocker, default_conf) -> None:
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    rpc = RPC(freqtradebot)
+    result = rpc._health()
+    assert result['last_process'] == '1970-01-01 00:00:00+00:00'
+    assert result['last_process_ts'] == 0
diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py
index 7c98b2df7..af8361571 100644
--- a/tests/rpc/test_rpc_apiserver.py
+++ b/tests/rpc/test_rpc_apiserver.py
@@ -7,6 +7,7 @@ from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from unittest.mock import ANY, MagicMock, PropertyMock
 
+import pandas as pd
 import pytest
 import uvicorn
 from fastapi import FastAPI
@@ -16,7 +17,7 @@ from numpy import isnan
 from requests.auth import _basic_auth_str
 
 from freqtrade.__init__ import __version__
-from freqtrade.enums import RunMode, State
+from freqtrade.enums import CandleType, RunMode, State, TradingMode
 from freqtrade.exceptions import DependencyException, ExchangeError, OperationalException
 from freqtrade.loggers import setup_logging, setup_logging_pre
 from freqtrade.persistence import PairLocks, Trade
@@ -24,8 +25,8 @@ from freqtrade.rpc import RPC
 from freqtrade.rpc.api_server import ApiServer
 from freqtrade.rpc.api_server.api_auth import create_token, get_user_from_token
 from freqtrade.rpc.api_server.uvicorn_threaded import UvicornServer
-from tests.conftest import (create_mock_trades, get_mock_coro, get_patched_freqtradebot, log_has,
-                            log_has_re, patch_get_signal)
+from tests.conftest import (CURRENT_TEST_STRATEGY, create_mock_trades, get_mock_coro,
+                            get_patched_freqtradebot, log_has, log_has_re, patch_get_signal)
 
 
 BASE_URI = "/api/v1"
@@ -95,7 +96,7 @@ def test_api_not_found(botclient):
     assert rc.json() == {"detail": "Not Found"}
 
 
-def test_api_ui_fallback(botclient):
+def test_api_ui_fallback(botclient, mocker):
     ftbot, client = botclient
 
     rc = client_get(client, "/favicon.ico")
@@ -109,9 +110,16 @@ def test_api_ui_fallback(botclient):
     rc = client_get(client, "/something")
     assert rc.status_code == 200
 
-    # Test directory traversal
+    # Test directory traversal without mock
     rc = client_get(client, '%2F%2F%2Fetc/passwd')
     assert rc.status_code == 200
+    # Allow both fallback or real UI
+    assert '`freqtrade install-ui`' in rc.text or '<!DOCTYPE html>' in rc.text
+
+    mocker.patch.object(Path, 'is_file', MagicMock(side_effect=[True, False]))
+    rc = client_get(client, '%2F%2F%2Fetc/passwd')
+    assert rc.status_code == 200
+
     assert '`freqtrade install-ui`' in rc.text
 
 
@@ -444,6 +452,10 @@ def test_api_balance(botclient, mocker, rpc_balance, tickers):
         'used': 0.0,
         'est_stake': 12.0,
         'stake': 'BTC',
+        'is_position': False,
+        'leverage': 1.0,
+        'position': 0.0,
+        'side': 'long',
     }
     assert 'starting_capital' in response
     assert 'starting_capital_fiat' in response
@@ -451,7 +463,8 @@ def test_api_balance(botclient, mocker, rpc_balance, tickers):
     assert 'starting_capital_ratio' in response
 
 
-def test_api_count(botclient, mocker, ticker, fee, markets):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_api_count(botclient, mocker, ticker, fee, markets, is_short):
     ftbot, client = botclient
     patch_get_signal(ftbot)
     mocker.patch.multiple(
@@ -468,7 +481,7 @@ def test_api_count(botclient, mocker, ticker, fee, markets):
     assert rc.json()["max"] == 1
 
     # Create some test data
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
     rc = client_get(client, f"{BASE_URI}/count")
     assert_response(rc)
     assert rc.json()["current"] == 4
@@ -513,22 +526,29 @@ def test_api_locks(botclient):
     assert rc.json()['lock_count'] == 0
 
 
-def test_api_show_config(botclient, mocker):
+def test_api_show_config(botclient):
     ftbot, client = botclient
     patch_get_signal(ftbot)
 
     rc = client_get(client, f"{BASE_URI}/show_config")
     assert_response(rc)
-    assert 'dry_run' in rc.json()
-    assert rc.json()['exchange'] == 'binance'
-    assert rc.json()['timeframe'] == '5m'
-    assert rc.json()['timeframe_ms'] == 300000
-    assert rc.json()['timeframe_min'] == 5
-    assert rc.json()['state'] == 'running'
-    assert rc.json()['bot_name'] == 'freqtrade'
-    assert not rc.json()['trailing_stop']
-    assert 'bid_strategy' in rc.json()
-    assert 'ask_strategy' in rc.json()
+    response = rc.json()
+    assert 'dry_run' in response
+    assert response['exchange'] == 'binance'
+    assert response['timeframe'] == '5m'
+    assert response['timeframe_ms'] == 300000
+    assert response['timeframe_min'] == 5
+    assert response['state'] == 'running'
+    assert response['bot_name'] == 'freqtrade'
+    assert response['trading_mode'] == 'spot'
+    assert response['strategy_version'] is None
+    assert not response['trailing_stop']
+    assert 'entry_pricing' in response
+    assert 'exit_pricing' in response
+    assert 'unfilledtimeout' in response
+    assert 'version' in response
+    assert 'api_version' in response
+    assert 2.1 <= response['api_version'] <= 2.2
 
 
 def test_api_daily(botclient, mocker, ticker, fee, markets):
@@ -549,7 +569,8 @@ def test_api_daily(botclient, mocker, ticker, fee, markets):
     assert rc.json()['data'][0]['date'] == str(datetime.utcnow().date())
 
 
-def test_api_trades(botclient, mocker, fee, markets):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_api_trades(botclient, mocker, fee, markets, is_short):
     ftbot, client = botclient
     patch_get_signal(ftbot)
     mocker.patch.multiple(
@@ -562,7 +583,7 @@ def test_api_trades(botclient, mocker, fee, markets):
     assert rc.json()['trades_count'] == 0
     assert rc.json()['total_trades'] == 0
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
     Trade.query.session.flush()
 
     rc = client_get(client, f"{BASE_URI}/trades")
@@ -570,6 +591,7 @@ def test_api_trades(botclient, mocker, fee, markets):
     assert len(rc.json()['trades']) == 2
     assert rc.json()['trades_count'] == 2
     assert rc.json()['total_trades'] == 2
+    assert rc.json()['trades'][0]['is_short'] == is_short
     rc = client_get(client, f"{BASE_URI}/trades?limit=1")
     assert_response(rc)
     assert len(rc.json()['trades']) == 1
@@ -577,9 +599,10 @@ def test_api_trades(botclient, mocker, fee, markets):
     assert rc.json()['total_trades'] == 2
 
 
-def test_api_trade_single(botclient, mocker, fee, ticker, markets):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_api_trade_single(botclient, mocker, fee, ticker, markets, is_short):
     ftbot, client = botclient
-    patch_get_signal(ftbot)
+    patch_get_signal(ftbot, enter_long=not is_short, enter_short=is_short)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         markets=PropertyMock(return_value=markets),
@@ -589,17 +612,19 @@ def test_api_trade_single(botclient, mocker, fee, ticker, markets):
     assert_response(rc, 404)
     assert rc.json()['detail'] == 'Trade not found.'
 
-    create_mock_trades(fee)
-    Trade.query.session.flush()
+    Trade.query.session.rollback()
+    create_mock_trades(fee, is_short=is_short)
 
     rc = client_get(client, f"{BASE_URI}/trade/3")
     assert_response(rc)
     assert rc.json()['trade_id'] == 3
+    assert rc.json()['is_short'] == is_short
 
 
-def test_api_delete_trade(botclient, mocker, fee, markets):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_api_delete_trade(botclient, mocker, fee, markets, is_short):
     ftbot, client = botclient
-    patch_get_signal(ftbot)
+    patch_get_signal(ftbot, enter_long=not is_short, enter_short=is_short)
     stoploss_mock = MagicMock()
     cancel_mock = MagicMock()
     mocker.patch.multiple(
@@ -608,15 +633,13 @@ def test_api_delete_trade(botclient, mocker, fee, markets):
         cancel_order=cancel_mock,
         cancel_stoploss_order=stoploss_mock,
     )
-    rc = client_delete(client, f"{BASE_URI}/trades/1")
-    # Error - trade won't exist yet.
-    assert_response(rc, 502)
 
-    create_mock_trades(fee)
-    Trade.query.session.flush()
+    create_mock_trades(fee, is_short=is_short)
+
     ftbot.strategy.order_types['stoploss_on_exchange'] = True
     trades = Trade.query.all()
     trades[1].stoploss_order_id = '1234'
+    Trade.commit()
     assert len(trades) > 2
 
     rc = client_delete(client, f"{BASE_URI}/trades/1")
@@ -638,6 +661,10 @@ def test_api_delete_trade(botclient, mocker, fee, markets):
     assert len(trades) - 2 == len(Trade.query.all())
     assert stoploss_mock.call_count == 1
 
+    rc = client_delete(client, f"{BASE_URI}/trades/502")
+    # Error - trade won't exist.
+    assert_response(rc, 502)
+
 
 def test_api_logs(botclient):
     ftbot, client = botclient
@@ -686,8 +713,48 @@ def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
     assert rc.json() == {"error": "Error querying /api/v1/edge: Edge is not enabled."}
 
 
-@pytest.mark.usefixtures("init_persistence")
-def test_api_profit(botclient, mocker, ticker, fee, markets):
+@pytest.mark.parametrize('is_short,expected', [
+    (
+        True,
+        {'best_pair': 'ETC/BTC', 'best_rate': -0.5, 'best_pair_profit_ratio': -0.005,
+         'profit_all_coin': 43.61269123,
+         'profit_all_fiat': 538398.67323435, 'profit_all_percent_mean': 66.41,
+         'profit_all_ratio_mean': 0.664109545, 'profit_all_percent_sum': 398.47,
+         'profit_all_ratio_sum': 3.98465727, 'profit_all_percent': 4.36,
+         'profit_all_ratio': 0.043612222872799825, 'profit_closed_coin': -0.00673913,
+         'profit_closed_fiat': -83.19455985, 'profit_closed_ratio_mean': -0.0075,
+         'profit_closed_percent_mean': -0.75, 'profit_closed_ratio_sum': -0.015,
+         'profit_closed_percent_sum': -1.5, 'profit_closed_ratio': -6.739057628404269e-06,
+         'profit_closed_percent': -0.0, 'winning_trades': 0, 'losing_trades': 2}
+    ),
+    (
+        False,
+        {'best_pair': 'XRP/BTC', 'best_rate': 1.0, 'best_pair_profit_ratio': 0.01,
+         'profit_all_coin': -44.0631579,
+         'profit_all_fiat': -543959.6842755, 'profit_all_percent_mean': -66.41,
+         'profit_all_ratio_mean': -0.6641100666666667, 'profit_all_percent_sum': -398.47,
+         'profit_all_ratio_sum': -3.9846604, 'profit_all_percent': -4.41,
+         'profit_all_ratio': -0.044063014216106644, 'profit_closed_coin': 0.00073913,
+         'profit_closed_fiat': 9.124559849999999, 'profit_closed_ratio_mean': 0.0075,
+         'profit_closed_percent_mean': 0.75, 'profit_closed_ratio_sum': 0.015,
+         'profit_closed_percent_sum': 1.5, 'profit_closed_ratio': 7.391275897987988e-07,
+         'profit_closed_percent': 0.0, 'winning_trades': 2, 'losing_trades': 0}
+    ),
+    (
+        None,
+        {'best_pair': 'XRP/BTC', 'best_rate': 1.0, 'best_pair_profit_ratio': 0.01,
+         'profit_all_coin': -14.43790415,
+         'profit_all_fiat': -178235.92673175, 'profit_all_percent_mean': 0.08,
+         'profit_all_ratio_mean': 0.000835751666666662, 'profit_all_percent_sum': 0.5,
+         'profit_all_ratio_sum': 0.005014509999999972, 'profit_all_percent': -1.44,
+         'profit_all_ratio': -0.014437768014451796, 'profit_closed_coin': -0.00542913,
+         'profit_closed_fiat': -67.02260985, 'profit_closed_ratio_mean': 0.0025,
+         'profit_closed_percent_mean': 0.25, 'profit_closed_ratio_sum': 0.005,
+         'profit_closed_percent_sum': 0.5, 'profit_closed_ratio': -5.429078808526421e-06,
+         'profit_closed_percent': -0.0, 'winning_trades': 1, 'losing_trades': 1}
+    )
+])
+def test_api_profit(botclient, mocker, ticker, fee, markets, is_short, expected):
     ftbot, client = botclient
     patch_get_signal(ftbot)
     mocker.patch.multiple(
@@ -702,45 +769,48 @@ def test_api_profit(botclient, mocker, ticker, fee, markets):
     assert_response(rc, 200)
     assert rc.json()['trade_count'] == 0
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
     # Simulate fulfilled LIMIT_BUY order for trade
 
     rc = client_get(client, f"{BASE_URI}/profit")
     assert_response(rc)
-    assert rc.json() == {'avg_duration': ANY,
-                         'best_pair': 'XRP/BTC',
-                         'best_rate': 1.0,
-                         'first_trade_date': ANY,
-                         'first_trade_timestamp': ANY,
-                         'latest_trade_date': '5 minutes ago',
-                         'latest_trade_timestamp': ANY,
-                         'profit_all_coin': -44.0631579,
-                         'profit_all_fiat': -543959.6842755,
-                         'profit_all_percent_mean': -66.41,
-                         'profit_all_ratio_mean': -0.6641100666666667,
-                         'profit_all_percent_sum': -398.47,
-                         'profit_all_ratio_sum': -3.9846604,
-                         'profit_all_percent': -4.41,
-                         'profit_all_ratio': -0.044063014216106644,
-                         'profit_closed_coin': 0.00073913,
-                         'profit_closed_fiat': 9.124559849999999,
-                         'profit_closed_ratio_mean': 0.0075,
-                         'profit_closed_percent_mean': 0.75,
-                         'profit_closed_ratio_sum': 0.015,
-                         'profit_closed_percent_sum': 1.5,
-                         'profit_closed_ratio': 7.391275897987988e-07,
-                         'profit_closed_percent': 0.0,
-                         'trade_count': 6,
-                         'closed_trade_count': 2,
-                         'winning_trades': 2,
-                         'losing_trades': 0,
-                         }
+    # raise ValueError(rc.json())
+    assert rc.json() == {
+        'avg_duration': ANY,
+        'best_pair': expected['best_pair'],
+        'best_pair_profit_ratio': expected['best_pair_profit_ratio'],
+        'best_rate': expected['best_rate'],
+        'first_trade_date': ANY,
+        'first_trade_timestamp': ANY,
+        'latest_trade_date': '5 minutes ago',
+        'latest_trade_timestamp': ANY,
+        'profit_all_coin': expected['profit_all_coin'],
+        'profit_all_fiat': expected['profit_all_fiat'],
+        'profit_all_percent_mean': expected['profit_all_percent_mean'],
+        'profit_all_ratio_mean': expected['profit_all_ratio_mean'],
+        'profit_all_percent_sum': expected['profit_all_percent_sum'],
+        'profit_all_ratio_sum': expected['profit_all_ratio_sum'],
+        'profit_all_percent': expected['profit_all_percent'],
+        'profit_all_ratio': expected['profit_all_ratio'],
+        'profit_closed_coin': expected['profit_closed_coin'],
+        'profit_closed_fiat': expected['profit_closed_fiat'],
+        'profit_closed_ratio_mean': expected['profit_closed_ratio_mean'],
+        'profit_closed_percent_mean': expected['profit_closed_percent_mean'],
+        'profit_closed_ratio_sum': expected['profit_closed_ratio_sum'],
+        'profit_closed_percent_sum': expected['profit_closed_percent_sum'],
+        'profit_closed_ratio': expected['profit_closed_ratio'],
+        'profit_closed_percent': expected['profit_closed_percent'],
+        'trade_count': 6,
+        'closed_trade_count': 2,
+        'winning_trades': expected['winning_trades'],
+        'losing_trades': expected['losing_trades'],
+    }
 
 
-@pytest.mark.usefixtures("init_persistence")
-def test_api_stats(botclient, mocker, ticker, fee, markets,):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_api_stats(botclient, mocker, ticker, fee, markets, is_short):
     ftbot, client = botclient
-    patch_get_signal(ftbot)
+    patch_get_signal(ftbot, enter_long=not is_short, enter_short=is_short)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         get_balances=MagicMock(return_value=ticker),
@@ -752,14 +822,14 @@ def test_api_stats(botclient, mocker, ticker, fee, markets,):
     rc = client_get(client, f"{BASE_URI}/stats")
     assert_response(rc, 200)
     assert 'durations' in rc.json()
-    assert 'sell_reasons' in rc.json()
+    assert 'exit_reasons' in rc.json()
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
 
     rc = client_get(client, f"{BASE_URI}/stats")
     assert_response(rc, 200)
     assert 'durations' in rc.json()
-    assert 'sell_reasons' in rc.json()
+    assert 'exit_reasons' in rc.json()
 
     assert 'wins' in rc.json()['durations']
     assert 'losses' in rc.json()['durations']
@@ -803,16 +873,23 @@ def test_api_performance(botclient, fee):
     trade.close_profit_abs = trade.calc_profit()
 
     Trade.query.session.add(trade)
-    Trade.query.session.flush()
+    Trade.commit()
 
     rc = client_get(client, f"{BASE_URI}/performance")
     assert_response(rc)
     assert len(rc.json()) == 2
-    assert rc.json() == [{'count': 1, 'pair': 'LTC/ETH', 'profit': 7.61, 'profit_abs': 0.01872279},
-                         {'count': 1, 'pair': 'XRP/ETH', 'profit': -5.57, 'profit_abs': -0.1150375}]
+    assert rc.json() == [{'count': 1, 'pair': 'LTC/ETH', 'profit': 7.61, 'profit_pct': 7.61,
+                          'profit_ratio': 0.07609203, 'profit_abs': 0.01872279},
+                         {'count': 1, 'pair': 'XRP/ETH', 'profit': -5.57, 'profit_pct': -5.57,
+                          'profit_ratio': -0.05570419, 'profit_abs': -0.1150375}]
 
 
-def test_api_status(botclient, mocker, ticker, fee, markets):
+@pytest.mark.parametrize(
+    'is_short,current_rate,open_order_id,open_trade_value',
+    [(True, 1.098e-05, 'dry_run_buy_short_12345', 15.0911775),
+     (False, 1.099e-05, 'dry_run_buy_long_12345', 15.1668225)])
+def test_api_status(botclient, mocker, ticker, fee, markets, is_short,
+                    current_rate, open_order_id, open_trade_value):
     ftbot, client = botclient
     patch_get_signal(ftbot)
     mocker.patch.multiple(
@@ -827,7 +904,7 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
     rc = client_get(client, f"{BASE_URI}/status")
     assert_response(rc, 200)
     assert rc.json() == []
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
 
     rc = client_get(client, f"{BASE_URI}/status")
     assert_response(rc)
@@ -848,12 +925,14 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
         'profit_pct': ANY,
         'profit_abs': ANY,
         'profit_fiat': ANY,
-        'current_rate': 1.099e-05,
+        'current_rate': current_rate,
         'open_date': ANY,
         'open_timestamp': ANY,
         'open_order': None,
         'open_rate': 0.123,
         'pair': 'ETH/BTC',
+        'base_currency': 'ETH',
+        'quote_currency': 'BTC',
         'stake_amount': 0.001,
         'stop_loss_abs': ANY,
         'stop_loss_pct': ANY,
@@ -878,17 +957,25 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
         'fee_open_cost': None,
         'fee_open_currency': None,
         'is_open': True,
+        "is_short": is_short,
         'max_rate': ANY,
         'min_rate': ANY,
-        'open_order_id': 'dry_run_buy_12345',
+        'open_order_id': open_order_id,
         'open_rate_requested': ANY,
-        'open_trade_value': 15.1668225,
+        'open_trade_value': open_trade_value,
         'sell_reason': None,
-        'sell_order_status': None,
-        'strategy': 'StrategyTestV2',
+        'exit_reason': None,
+        'exit_order_status': None,
+        'strategy': CURRENT_TEST_STRATEGY,
         'buy_tag': None,
+        'enter_tag': None,
         'timeframe': 5,
         'exchange': 'binance',
+        'leverage': 1.0,
+        'interest_rate': 0.0,
+        'funding_fees': None,
+        'trading_mode': ANY,
+        'orders': [ANY],
     }
 
     mocker.patch('freqtrade.exchange.Exchange.get_rate',
@@ -937,12 +1024,44 @@ def test_api_blacklist(botclient, mocker):
                      data='{"blacklist": ["XRP/.*"]}')
     assert_response(rc)
     assert rc.json() == {"blacklist": ["DOGE/BTC", "HOT/BTC", "ETH/BTC", "XRP/.*"],
-                         "blacklist_expanded": ["ETH/BTC", "XRP/BTC"],
+                         "blacklist_expanded": ["ETH/BTC", "XRP/BTC", "XRP/USDT"],
                          "length": 4,
                          "method": ["StaticPairList"],
                          "errors": {},
                          }
 
+    rc = client_delete(client, f"{BASE_URI}/blacklist?pairs_to_delete=DOGE/BTC")
+    assert_response(rc)
+    assert rc.json() == {"blacklist": ["HOT/BTC", "ETH/BTC", "XRP/.*"],
+                         "blacklist_expanded": ["ETH/BTC", "XRP/BTC", "XRP/USDT"],
+                         "length": 3,
+                         "method": ["StaticPairList"],
+                         "errors": {},
+                         }
+
+    rc = client_delete(client, f"{BASE_URI}/blacklist?pairs_to_delete=NOTHING/BTC")
+    assert_response(rc)
+    assert rc.json() == {"blacklist": ["HOT/BTC", "ETH/BTC", "XRP/.*"],
+                         "blacklist_expanded": ["ETH/BTC", "XRP/BTC", "XRP/USDT"],
+                         "length": 3,
+                         "method": ["StaticPairList"],
+                         "errors": {
+                             "NOTHING/BTC": {
+                                 "error_msg": "Pair NOTHING/BTC is not in the current blacklist."
+                             }
+    },
+    }
+    rc = client_delete(
+        client,
+        f"{BASE_URI}/blacklist?pairs_to_delete=HOT/BTC&pairs_to_delete=ETH/BTC")
+    assert_response(rc)
+    assert rc.json() == {"blacklist": ["XRP/.*"],
+                         "blacklist_expanded": ["XRP/BTC", "XRP/USDT"],
+                         "length": 1,
+                         "method": ["StaticPairList"],
+                         "errors": {},
+                         }
+
 
 def test_api_whitelist(botclient):
     ftbot, client = botclient
@@ -956,27 +1075,31 @@ def test_api_whitelist(botclient):
     }
 
 
-def test_api_forcebuy(botclient, mocker, fee):
+@pytest.mark.parametrize('endpoint', [
+    'forcebuy',
+    'forceenter',
+])
+def test_api_force_entry(botclient, mocker, fee, endpoint):
     ftbot, client = botclient
 
-    rc = client_post(client, f"{BASE_URI}/forcebuy",
+    rc = client_post(client, f"{BASE_URI}/{endpoint}",
                      data='{"pair": "ETH/BTC"}')
     assert_response(rc, 502)
-    assert rc.json() == {"error": "Error querying /api/v1/forcebuy: Forcebuy not enabled."}
+    assert rc.json() == {"error": f"Error querying /api/v1/{endpoint}: Force_entry not enabled."}
 
     # enable forcebuy
-    ftbot.config['forcebuy_enable'] = True
+    ftbot.config['force_entry_enable'] = True
 
     fbuy_mock = MagicMock(return_value=None)
-    mocker.patch("freqtrade.rpc.RPC._rpc_forcebuy", fbuy_mock)
-    rc = client_post(client, f"{BASE_URI}/forcebuy",
+    mocker.patch("freqtrade.rpc.RPC._rpc_force_entry", fbuy_mock)
+    rc = client_post(client, f"{BASE_URI}/{endpoint}",
                      data='{"pair": "ETH/BTC"}')
     assert_response(rc)
-    assert rc.json() == {"status": "Error buying pair ETH/BTC."}
+    assert rc.json() == {"status": "Error entering long trade for pair ETH/BTC."}
 
     # Test creating trade
     fbuy_mock = MagicMock(return_value=Trade(
-        pair='ETH/ETH',
+        pair='ETH/BTC',
         amount=1,
         amount_requested=1,
         exchange='binance',
@@ -985,21 +1108,23 @@ def test_api_forcebuy(botclient, mocker, fee):
         open_order_id="123456",
         open_date=datetime.utcnow(),
         is_open=False,
+        is_short=False,
         fee_close=fee.return_value,
         fee_open=fee.return_value,
         close_rate=0.265441,
         id=22,
         timeframe=5,
-        strategy="StrategyTestV2"
+        strategy=CURRENT_TEST_STRATEGY,
+        trading_mode=TradingMode.SPOT
     ))
-    mocker.patch("freqtrade.rpc.RPC._rpc_forcebuy", fbuy_mock)
+    mocker.patch("freqtrade.rpc.RPC._rpc_force_entry", fbuy_mock)
 
-    rc = client_post(client, f"{BASE_URI}/forcebuy",
+    rc = client_post(client, f"{BASE_URI}/{endpoint}",
                      data='{"pair": "ETH/BTC"}')
     assert_response(rc)
     assert rc.json() == {
-        'amount': 1,
-        'amount_requested': 1,
+        'amount': 1.0,
+        'amount_requested': 1.0,
         'trade_id': 22,
         'close_date': None,
         'close_timestamp': None,
@@ -1007,7 +1132,9 @@ def test_api_forcebuy(botclient, mocker, fee):
         'open_date': ANY,
         'open_timestamp': ANY,
         'open_rate': 0.245441,
-        'pair': 'ETH/ETH',
+        'pair': 'ETH/BTC',
+        'base_currency': 'ETH',
+        'quote_currency': 'BTC',
         'stake_amount': 1,
         'stop_loss_abs': None,
         'stop_loss_pct': None,
@@ -1033,21 +1160,29 @@ def test_api_forcebuy(botclient, mocker, fee):
         'fee_open_cost': None,
         'fee_open_currency': None,
         'is_open': False,
+        'is_short': False,
         'max_rate': None,
         'min_rate': None,
         'open_order_id': '123456',
         'open_rate_requested': None,
         'open_trade_value': 0.24605460,
         'sell_reason': None,
-        'sell_order_status': None,
-        'strategy': 'StrategyTestV2',
+        'exit_reason': None,
+        'exit_order_status': None,
+        'strategy': CURRENT_TEST_STRATEGY,
         'buy_tag': None,
+        'enter_tag': None,
         'timeframe': 5,
         'exchange': 'binance',
+        'leverage': None,
+        'interest_rate': None,
+        'funding_fees': None,
+        'trading_mode': 'spot',
+        'orders': [],
     }
 
 
-def test_api_forcesell(botclient, mocker, ticker, fee, markets):
+def test_api_forceexit(botclient, mocker, ticker, fee, markets):
     ftbot, client = botclient
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
@@ -1059,14 +1194,15 @@ def test_api_forcesell(botclient, mocker, ticker, fee, markets):
     )
     patch_get_signal(ftbot)
 
-    rc = client_post(client, f"{BASE_URI}/forcesell",
+    rc = client_post(client, f"{BASE_URI}/forceexit",
                      data='{"tradeid": "1"}')
     assert_response(rc, 502)
-    assert rc.json() == {"error": "Error querying /api/v1/forcesell: invalid argument"}
+    assert rc.json() == {"error": "Error querying /api/v1/forceexit: invalid argument"}
+    Trade.query.session.rollback()
 
     ftbot.enter_positions()
 
-    rc = client_post(client, f"{BASE_URI}/forcesell",
+    rc = client_post(client, f"{BASE_URI}/forceexit",
                      data='{"tradeid": "1"}')
     assert_response(rc)
     assert rc.json() == {'result': 'Created sell order for trade 1.'}
@@ -1097,17 +1233,19 @@ def test_api_pair_candles(botclient, ohlcv_history):
     assert 'data_stop_ts' in rc.json()
     assert len(rc.json()['data']) == 0
     ohlcv_history['sma'] = ohlcv_history['close'].rolling(2).mean()
-    ohlcv_history['buy'] = 0
-    ohlcv_history.loc[1, 'buy'] = 1
-    ohlcv_history['sell'] = 0
+    ohlcv_history['enter_long'] = 0
+    ohlcv_history.loc[1, 'enter_long'] = 1
+    ohlcv_history['exit_long'] = 0
+    ohlcv_history['enter_short'] = 0
+    ohlcv_history['exit_short'] = 0
 
-    ftbot.dataprovider._set_cached_df("XRP/BTC", timeframe, ohlcv_history)
+    ftbot.dataprovider._set_cached_df("XRP/BTC", timeframe, ohlcv_history, CandleType.SPOT)
 
     rc = client_get(client,
                     f"{BASE_URI}/pair_candles?limit={amount}&pair=XRP%2FBTC&timeframe={timeframe}")
     assert_response(rc)
     assert 'strategy' in rc.json()
-    assert rc.json()['strategy'] == 'StrategyTestV2'
+    assert rc.json()['strategy'] == CURRENT_TEST_STRATEGY
     assert 'columns' in rc.json()
     assert 'data_start_ts' in rc.json()
     assert 'data_start' in rc.json()
@@ -1118,9 +1256,12 @@ def test_api_pair_candles(botclient, ohlcv_history):
     assert rc.json()['data_stop'] == '2017-11-26 09:00:00+00:00'
     assert rc.json()['data_stop_ts'] == 1511686800000
     assert isinstance(rc.json()['columns'], list)
-    assert rc.json()['columns'] == ['date', 'open', 'high',
-                                    'low', 'close', 'volume', 'sma', 'buy', 'sell',
-                                    '__date_ts', '_buy_signal_open', '_sell_signal_open']
+    assert set(rc.json()['columns']) == {
+        'date', 'open', 'high', 'low', 'close', 'volume',
+        'sma', 'enter_long', 'exit_long', 'enter_short', 'exit_short', '__date_ts',
+        '_enter_long_signal_close', '_exit_long_signal_close',
+        '_enter_short_signal_close', '_exit_short_signal_close'
+    }
     assert 'pair' in rc.json()
     assert rc.json()['pair'] == 'XRP/BTC'
 
@@ -1129,13 +1270,33 @@ def test_api_pair_candles(botclient, ohlcv_history):
 
     assert (rc.json()['data'] ==
             [['2017-11-26 08:50:00', 8.794e-05, 8.948e-05, 8.794e-05, 8.88e-05, 0.0877869,
-              None, 0, 0, 1511686200000, None, None],
+              None, 0, 0, 0, 0, 1511686200000, None, None, None, None],
              ['2017-11-26 08:55:00', 8.88e-05, 8.942e-05, 8.88e-05,
-                 8.893e-05, 0.05874751, 8.886500000000001e-05, 1, 0, 1511686500000, 8.88e-05, None],
+                 8.893e-05, 0.05874751, 8.886500000000001e-05, 1, 0, 0, 0, 1511686500000, 8.893e-05,
+                 None, None, None],
              ['2017-11-26 09:00:00', 8.891e-05, 8.893e-05, 8.875e-05, 8.877e-05,
-                 0.7039405, 8.885e-05, 0, 0, 1511686800000, None, None]
+                 0.7039405, 8.885e-05, 0, 0, 0, 0, 1511686800000, None, None, None, None]
 
              ])
+    ohlcv_history['exit_long'] = ohlcv_history['exit_long'].astype('float64')
+    ohlcv_history.at[0, 'exit_long'] = float('inf')
+    ohlcv_history['date1'] = ohlcv_history['date']
+    ohlcv_history.at[0, 'date1'] = pd.NaT
+
+    ftbot.dataprovider._set_cached_df("XRP/BTC", timeframe, ohlcv_history, CandleType.SPOT)
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_candles?limit={amount}&pair=XRP%2FBTC&timeframe={timeframe}")
+    assert_response(rc)
+    assert (rc.json()['data'] ==
+            [['2017-11-26 08:50:00', 8.794e-05, 8.948e-05, 8.794e-05, 8.88e-05, 0.0877869,
+              None, 0, None, 0, 0, None, 1511686200000, None, None, None, None],
+             ['2017-11-26 08:55:00', 8.88e-05, 8.942e-05, 8.88e-05,
+                 8.893e-05, 0.05874751, 8.886500000000001e-05, 1, 0.0, 0, 0, '2017-11-26 08:55:00',
+                 1511686500000, 8.893e-05, None, None, None],
+             ['2017-11-26 09:00:00', 8.891e-05, 8.893e-05, 8.875e-05, 8.877e-05,
+                 0.7039405, 8.885e-05, 0, 0.0, 0, 0, '2017-11-26 09:00:00', 1511686800000,
+                 None, None, None, None]
+             ])
 
 
 def test_api_pair_history(botclient, ohlcv_history):
@@ -1145,19 +1306,19 @@ def test_api_pair_history(botclient, ohlcv_history):
     # No pair
     rc = client_get(client,
                     f"{BASE_URI}/pair_history?timeframe={timeframe}"
-                    "&timerange=20180111-20180112&strategy=StrategyTestV2")
+                    f"&timerange=20180111-20180112&strategy={CURRENT_TEST_STRATEGY}")
     assert_response(rc, 422)
 
     # No Timeframe
     rc = client_get(client,
                     f"{BASE_URI}/pair_history?pair=UNITTEST%2FBTC"
-                    "&timerange=20180111-20180112&strategy=StrategyTestV2")
+                    f"&timerange=20180111-20180112&strategy={CURRENT_TEST_STRATEGY}")
     assert_response(rc, 422)
 
     # No timerange
     rc = client_get(client,
                     f"{BASE_URI}/pair_history?pair=UNITTEST%2FBTC&timeframe={timeframe}"
-                    "&strategy=StrategyTestV2")
+                    f"&strategy={CURRENT_TEST_STRATEGY}")
     assert_response(rc, 422)
 
     # No strategy
@@ -1169,14 +1330,14 @@ def test_api_pair_history(botclient, ohlcv_history):
     # Working
     rc = client_get(client,
                     f"{BASE_URI}/pair_history?pair=UNITTEST%2FBTC&timeframe={timeframe}"
-                    "&timerange=20180111-20180112&strategy=StrategyTestV2")
+                    f"&timerange=20180111-20180112&strategy={CURRENT_TEST_STRATEGY}")
     assert_response(rc, 200)
     assert rc.json()['length'] == 289
     assert len(rc.json()['data']) == rc.json()['length']
     assert 'columns' in rc.json()
     assert 'data' in rc.json()
     assert rc.json()['pair'] == 'UNITTEST/BTC'
-    assert rc.json()['strategy'] == 'StrategyTestV2'
+    assert rc.json()['strategy'] == CURRENT_TEST_STRATEGY
     assert rc.json()['data_start'] == '2018-01-11 00:00:00+00:00'
     assert rc.json()['data_start_ts'] == 1515628800000
     assert rc.json()['data_stop'] == '2018-01-12 00:00:00+00:00'
@@ -1185,7 +1346,7 @@ def test_api_pair_history(botclient, ohlcv_history):
     # No data found
     rc = client_get(client,
                     f"{BASE_URI}/pair_history?pair=UNITTEST%2FBTC&timeframe={timeframe}"
-                    "&timerange=20200111-20200112&strategy=StrategyTestV2")
+                    f"&timerange=20200111-20200112&strategy={CURRENT_TEST_STRATEGY}")
     assert_response(rc, 502)
     assert rc.json()['error'] == ("Error querying /api/v1/pair_history: "
                                   "No data for UNITTEST/BTC, 5m in 20200111-20200112 found.")
@@ -1226,19 +1387,21 @@ def test_api_strategies(botclient):
         'HyperoptableStrategy',
         'InformativeDecoratorTest',
         'StrategyTestV2',
-        'TestStrategyLegacyV1'
+        'StrategyTestV3',
+        'StrategyTestV3Futures',
+        'TestStrategyLegacyV1',
     ]}
 
 
 def test_api_strategy(botclient):
     ftbot, client = botclient
 
-    rc = client_get(client, f"{BASE_URI}/strategy/StrategyTestV2")
+    rc = client_get(client, f"{BASE_URI}/strategy/{CURRENT_TEST_STRATEGY}")
 
     assert_response(rc)
-    assert rc.json()['strategy'] == 'StrategyTestV2'
+    assert rc.json()['strategy'] == CURRENT_TEST_STRATEGY
 
-    data = (Path(__file__).parents[1] / "strategy/strats/strategy_test_v2.py").read_text()
+    data = (Path(__file__).parents[1] / "strategy/strats/strategy_test_v3.py").read_text()
     assert rc.json()['code'] == data
 
     rc = client_get(client, f"{BASE_URI}/strategy/NoStrat")
@@ -1270,11 +1433,40 @@ def test_list_available_pairs(botclient):
     assert rc.json()['pairs'] == ['XRP/ETH']
     assert len(rc.json()['pair_interval']) == 1
 
+    ftbot.config['trading_mode'] = 'futures'
+    rc = client_get(
+        client, f"{BASE_URI}/available_pairs?timeframe=1h")
+    assert_response(rc)
+    assert rc.json()['length'] == 1
+    assert rc.json()['pairs'] == ['XRP/USDT']
 
-def test_api_backtesting(botclient, mocker, fee, caplog):
+    rc = client_get(
+        client, f"{BASE_URI}/available_pairs?timeframe=1h&candletype=mark")
+    assert_response(rc)
+    assert rc.json()['length'] == 2
+    assert rc.json()['pairs'] == ['UNITTEST/USDT', 'XRP/USDT']
+    assert len(rc.json()['pair_interval']) == 2
+
+
+def test_sysinfo(botclient):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/sysinfo")
+    assert_response(rc)
+    result = rc.json()
+    assert 'cpu_pct' in result
+    assert 'ram_pct' in result
+
+
+def test_api_backtesting(botclient, mocker, fee, caplog, tmpdir):
     ftbot, client = botclient
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
 
+    rc = client_get(client, f"{BASE_URI}/backtest")
+    # Backtest prevented in default mode
+    assert_response(rc, 502)
+
+    ftbot.config['runmode'] = RunMode.WEBSERVER
     # Backtesting not started yet
     rc = client_get(client, f"{BASE_URI}/backtest")
     assert_response(rc)
@@ -1292,10 +1484,15 @@ def test_api_backtesting(botclient, mocker, fee, caplog):
     assert result['status'] == 'reset'
     assert not result['running']
     assert result['status_msg'] == 'Backtest reset'
+    ftbot.config['export'] = 'trades'
+    ftbot.config['backtest_cache'] = 'none'
+    ftbot.config['user_data_dir'] = Path(tmpdir)
+    ftbot.config['exportfilename'] = Path(tmpdir) / "backtest_results"
+    ftbot.config['exportfilename'].mkdir()
 
     # start backtesting
     data = {
-        "strategy": "StrategyTestV2",
+        "strategy": CURRENT_TEST_STRATEGY,
         "timeframe": "5m",
         "timerange": "20180110-20180111",
         "max_open_trades": 3,
@@ -1366,6 +1563,14 @@ def test_api_backtesting(botclient, mocker, fee, caplog):
     rc = client_post(client, f"{BASE_URI}/backtest", data=json.dumps(data))
     assert log_has("Backtesting caused an error: ", caplog)
 
+    ftbot.config['backtest_cache'] = 'day'
+
+    # Rerun backtest (should get previous result)
+    rc = client_post(client, f"{BASE_URI}/backtest", data=json.dumps(data))
+    assert_response(rc)
+    result = rc.json()
+    assert log_has_re('Reusing result of previous backtest.*', caplog)
+
     # Delete backtesting to avoid leakage since the backtest-object may stick around.
     rc = client_delete(client, f"{BASE_URI}/backtest")
     assert_response(rc)
@@ -1374,3 +1579,46 @@ def test_api_backtesting(botclient, mocker, fee, caplog):
     assert result['status'] == 'reset'
     assert not result['running']
     assert result['status_msg'] == 'Backtest reset'
+
+
+def test_api_backtest_history(botclient, mocker, testdatadir):
+    ftbot, client = botclient
+    mocker.patch('freqtrade.data.btanalysis._get_backtest_files',
+                 return_value=[
+                     testdatadir / 'backtest_results/backtest-result_multistrat.json',
+                     testdatadir / 'backtest_results/backtest-result_new.json'
+                     ])
+
+    rc = client_get(client, f"{BASE_URI}/backtest/history")
+    assert_response(rc, 502)
+    ftbot.config['user_data_dir'] = testdatadir
+    ftbot.config['runmode'] = RunMode.WEBSERVER
+
+    rc = client_get(client, f"{BASE_URI}/backtest/history")
+    assert_response(rc)
+    result = rc.json()
+    assert len(result) == 3
+    fn = result[0]['filename']
+    assert fn == "backtest-result_multistrat.json"
+    strategy = result[0]['strategy']
+    rc = client_get(client, f"{BASE_URI}/backtest/history/result?filename={fn}&strategy={strategy}")
+    assert_response(rc)
+    result2 = rc.json()
+    assert result2
+    assert result2['status'] == 'ended'
+    assert not result2['running']
+    assert result2['progress'] == 1
+    # Only one strategy loaded - even though we use multiresult
+    assert len(result2['backtest_result']['strategy']) == 1
+    assert result2['backtest_result']['strategy'][strategy]
+
+
+def test_health(botclient):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/health")
+
+    assert_response(rc)
+    ret = rc.json()
+    assert ret['last_process_ts'] == 0
+    assert ret['last_process'] == '1970-01-01T00:00:00+00:00'
diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py
index 7dde7b803..2bc4fc5c3 100644
--- a/tests/rpc/test_rpc_telegram.py
+++ b/tests/rpc/test_rpc_telegram.py
@@ -4,7 +4,7 @@
 
 import logging
 import re
-from datetime import datetime
+from datetime import datetime, timedelta, timezone
 from functools import reduce
 from random import choice, randint
 from string import ascii_uppercase
@@ -18,21 +18,24 @@ from telegram.error import BadRequest, NetworkError, TelegramError
 from freqtrade import __version__
 from freqtrade.constants import CANCEL_REASON
 from freqtrade.edge import PairInfo
-from freqtrade.enums import RPCMessageType, RunMode, SellType, State
+from freqtrade.enums import ExitType, RPCMessageType, RunMode, SignalDirection, State
 from freqtrade.exceptions import OperationalException
 from freqtrade.freqtradebot import FreqtradeBot
 from freqtrade.loggers import setup_logging
 from freqtrade.persistence import PairLocks, Trade
+from freqtrade.persistence.models import Order
 from freqtrade.rpc import RPC
+from freqtrade.rpc.rpc import RPCException
 from freqtrade.rpc.telegram import Telegram, authorized_only
-from tests.conftest import (create_mock_trades, get_patched_freqtradebot, log_has, log_has_re,
-                            patch_exchange, patch_get_signal, patch_whitelist)
+from tests.conftest import (CURRENT_TEST_STRATEGY, create_mock_trades, get_patched_freqtradebot,
+                            log_has, log_has_re, patch_exchange, patch_get_signal, patch_whitelist)
 
 
 class DummyCls(Telegram):
     """
     Dummy class for testing the Telegram @authorized_only decorator
     """
+
     def __init__(self, rpc: RPC, config) -> None:
         super().__init__(rpc, config)
         self.state = {'called': False}
@@ -91,11 +94,15 @@ def test_telegram_init(default_conf, mocker, caplog) -> None:
     assert start_polling.start_polling.call_count == 1
 
     message_str = ("rpc.telegram is listening for following commands: [['status'], ['profit'], "
-                   "['balance'], ['start'], ['stop'], ['forcesell'], ['forcebuy'], ['trades'], "
-                   "['delete'], ['performance'], ['stats'], ['daily'], ['count'], ['locks'], "
-                   "['unlock', 'delete_locks'], ['reload_config', 'reload_conf'], "
-                   "['show_config', 'show_conf'], ['stopbuy'], "
-                   "['whitelist'], ['blacklist'], ['logs'], ['edge'], ['help'], ['version']"
+                   "['balance'], ['start'], ['stop'], "
+                   "['forcesell', 'forceexit', 'fx'], ['forcebuy', 'forcelong'], ['forceshort'], "
+                   "['trades'], ['delete'], ['performance'], "
+                   "['buys', 'entries'], ['sells', 'exits'], ['mix_tags'], "
+                   "['stats'], ['daily'], ['weekly'], ['monthly'], "
+                   "['count'], ['locks'], ['unlock', 'delete_locks'], "
+                   "['reload_config', 'reload_conf'], ['show_config', 'show_conf'], "
+                   "['stopbuy'], ['whitelist'], ['blacklist'], ['blacklist_delete', 'bl_delete'], "
+                   "['logs'], ['edge'], ['health'], ['help'], ['version']"
                    "]")
 
     assert log_has(message_str, caplog)
@@ -177,7 +184,8 @@ def test_telegram_status(default_conf, update, mocker) -> None:
         _rpc_trade_status=MagicMock(return_value=[{
             'trade_id': 1,
             'pair': 'ETH/BTC',
-            'base_currency': 'BTC',
+            'base_currency': 'ETH',
+            'quote_currency': 'BTC',
             'open_date': arrow.utcnow(),
             'close_date': None,
             'open_rate': 1.099e-05,
@@ -186,18 +194,22 @@ def test_telegram_status(default_conf, update, mocker) -> None:
             'amount': 90.99181074,
             'stake_amount': 90.99181074,
             'buy_tag': None,
-            'close_profit_pct': None,
+            'enter_tag': None,
+            'close_profit_ratio': None,
             'profit': -0.0059,
-            'profit_pct': -0.59,
+            'profit_ratio': -0.0059,
             'initial_stop_loss_abs': 1.098e-05,
             'stop_loss_abs': 1.099e-05,
-            'sell_order_status': None,
-            'initial_stop_loss_pct': -0.05,
+            'exit_order_status': None,
+            'initial_stop_loss_ratio': -0.0005,
             'stoploss_current_dist': 1e-08,
-            'stoploss_current_dist_pct': -0.02,
-            'stop_loss_pct': -0.01,
+            'stoploss_current_dist_ratio': -0.0002,
+            'stop_loss_ratio': -0.0001,
             'open_order': '(limit buy rem=0.00000000)',
-            'is_open': True
+            'is_open': True,
+            'is_short': False,
+            'filled_entry_orders': [],
+            'orders': []
         }]),
     )
 
@@ -213,6 +225,82 @@ def test_telegram_status(default_conf, update, mocker) -> None:
     assert status_table.call_count == 1
 
 
+@pytest.mark.usefixtures("init_persistence")
+def test_telegram_status_multi_entry(default_conf, update, mocker, fee) -> None:
+    update.message.chat.id = "123"
+    default_conf['telegram']['enabled'] = False
+    default_conf['telegram']['chat_id'] = "123"
+    default_conf['position_adjustment_enable'] = True
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_order=MagicMock(return_value=None),
+        get_rate=MagicMock(return_value=0.22),
+    )
+
+    telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
+
+    create_mock_trades(fee)
+    trades = Trade.get_open_trades()
+    trade = trades[0]
+    # Average may be empty on some exchanges
+    trade.orders[0].average = 0
+    trade.orders.append(Order(
+        order_id='5412vbb',
+        ft_order_side='buy',
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side="buy",
+        price=trade.open_rate * 0.95,
+        average=0,
+        filled=trade.amount,
+        remaining=0,
+        cost=trade.amount,
+        order_date=trade.open_date,
+        order_filled_date=trade.open_date,
+    )
+    )
+    trade.recalc_trade_from_orders()
+    Trade.commit()
+
+    telegram._status(update=update, context=MagicMock())
+    assert msg_mock.call_count == 4
+    msg = msg_mock.call_args_list[0][0][0]
+    assert re.search(r'Number of Entries.*2', msg)
+    assert re.search(r'Average Entry Price', msg)
+    assert re.search(r'Order filled at', msg)
+    assert re.search(r'Close Date:', msg) is None
+    assert re.search(r'Close Profit:', msg) is None
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_telegram_status_closed_trade(default_conf, update, mocker, fee) -> None:
+    update.message.chat.id = "123"
+    default_conf['telegram']['enabled'] = False
+    default_conf['telegram']['chat_id'] = "123"
+    default_conf['position_adjustment_enable'] = True
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_order=MagicMock(return_value=None),
+        get_rate=MagicMock(return_value=0.22),
+    )
+
+    telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
+
+    create_mock_trades(fee)
+    trades = Trade.get_trades([Trade.is_open.is_(False)])
+    trade = trades[0]
+    context = MagicMock()
+    context.args = [str(trade.id)]
+    telegram._status(update=update, context=context)
+    assert msg_mock.call_count == 1
+    msg = msg_mock.call_args_list[0][0][0]
+    assert re.search(r'Close Date:', msg)
+    assert re.search(r'Close Profit:', msg)
+
+
 def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
     default_conf['max_open_trades'] = 3
     mocker.patch.multiple(
@@ -311,6 +399,7 @@ def test_status_table_handle(default_conf, update, ticker, fee, mocker) -> None:
     fields = re.sub('[ ]+', ' ', line[2].strip()).split(' ')
 
     assert int(fields[0]) == 1
+    # assert 'L' in fields[1]
     assert 'ETH/BTC' in fields[1]
     assert msg_mock.call_count == 1
 
@@ -338,10 +427,12 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
     assert trade
 
     # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
 
     # Simulate fulfilled LIMIT_SELL order for trade
-    trade.update(limit_sell_order)
+    oobjs = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobjs)
 
     trade.close_date = datetime.utcnow()
     trade.is_open = False
@@ -352,7 +443,8 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
     context.args = ["2"]
     telegram._daily(update=update, context=context)
     assert msg_mock.call_count == 1
-    assert 'Daily' in msg_mock.call_args_list[0][0][0]
+    assert "Daily Profit over the last 2 days</b>:" in msg_mock.call_args_list[0][0][0]
+    assert 'Day ' in msg_mock.call_args_list[0][0][0]
     assert str(datetime.utcnow().date()) in msg_mock.call_args_list[0][0][0]
     assert str('  0.00006217 BTC') in msg_mock.call_args_list[0][0][0]
     assert str('  0.933 USD') in msg_mock.call_args_list[0][0][0]
@@ -364,7 +456,7 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
     context.args = []
     telegram._daily(update=update, context=context)
     assert msg_mock.call_count == 1
-    assert 'Daily' in msg_mock.call_args_list[0][0][0]
+    assert "Daily Profit over the last 7 days</b>:" in msg_mock.call_args_list[0][0][0]
     assert str(datetime.utcnow().date()) in msg_mock.call_args_list[0][0][0]
     assert str('  0.00006217 BTC') in msg_mock.call_args_list[0][0][0]
     assert str('  0.933 USD') in msg_mock.call_args_list[0][0][0]
@@ -380,8 +472,8 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
 
     trades = Trade.query.all()
     for trade in trades:
-        trade.update(limit_buy_order)
-        trade.update(limit_sell_order)
+        trade.update_trade(oobj)
+        trade.update_trade(oobjs)
         trade.close_date = datetime.utcnow()
         trade.is_open = False
 
@@ -420,7 +512,246 @@ def test_daily_wrong_input(default_conf, update, ticker, mocker) -> None:
     context = MagicMock()
     context.args = ["today"]
     telegram._daily(update=update, context=context)
-    assert str('Daily Profit over the last 7 days') in msg_mock.call_args_list[0][0][0]
+    assert str('Daily Profit over the last 7 days</b>:') in msg_mock.call_args_list[0][0][0]
+
+
+def test_weekly_handle(default_conf, update, ticker, limit_buy_order, fee,
+                       limit_sell_order, mocker) -> None:
+    default_conf['max_open_trades'] = 1
+    mocker.patch(
+        'freqtrade.rpc.rpc.CryptoToFiatConverter._find_price',
+        return_value=15000.0
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+
+    telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
+
+    patch_get_signal(freqtradebot)
+
+    # Create some test data
+    freqtradebot.enter_positions()
+    trade = Trade.query.first()
+    assert trade
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+
+    # Simulate fulfilled LIMIT_SELL order for trade
+    oobjs = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobjs)
+
+    trade.close_date = datetime.utcnow()
+    trade.is_open = False
+
+    # Try valid data
+    # /weekly 2
+    context = MagicMock()
+    context.args = ["2"]
+    telegram._weekly(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert "Weekly Profit over the last 2 weeks (starting from Monday)</b>:" \
+           in msg_mock.call_args_list[0][0][0]
+    assert 'Monday ' in msg_mock.call_args_list[0][0][0]
+    today = datetime.utcnow().date()
+    first_iso_day_of_current_week = today - timedelta(days=today.weekday())
+    assert str(first_iso_day_of_current_week) in msg_mock.call_args_list[0][0][0]
+    assert str('  0.00006217 BTC') in msg_mock.call_args_list[0][0][0]
+    assert str('  0.933 USD') in msg_mock.call_args_list[0][0][0]
+    assert str('  1 trade') in msg_mock.call_args_list[0][0][0]
+    assert str('  0 trade') in msg_mock.call_args_list[0][0][0]
+
+    # Reset msg_mock
+    msg_mock.reset_mock()
+    context.args = []
+    telegram._weekly(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert "Weekly Profit over the last 8 weeks (starting from Monday)</b>:" \
+           in msg_mock.call_args_list[0][0][0]
+    assert 'Weekly' in msg_mock.call_args_list[0][0][0]
+    assert str('  0.00006217 BTC') in msg_mock.call_args_list[0][0][0]
+    assert str('  0.933 USD') in msg_mock.call_args_list[0][0][0]
+    assert str('  1 trade') in msg_mock.call_args_list[0][0][0]
+    assert str('  0 trade') in msg_mock.call_args_list[0][0][0]
+
+    # Reset msg_mock
+    msg_mock.reset_mock()
+    freqtradebot.config['max_open_trades'] = 2
+    # Add two other trades
+    n = freqtradebot.enter_positions()
+    assert n == 2
+
+    trades = Trade.query.all()
+    for trade in trades:
+        trade.update_trade(oobj)
+        trade.update_trade(oobjs)
+        trade.close_date = datetime.utcnow()
+        trade.is_open = False
+
+    # /weekly 1
+    # By default, the 8 previous weeks are shown
+    # So the previous modified trade should be excluded from the stats
+    context = MagicMock()
+    context.args = ["1"]
+    telegram._weekly(update=update, context=context)
+    assert str('  0.00018651 BTC') in msg_mock.call_args_list[0][0][0]
+    assert str('  2.798 USD') in msg_mock.call_args_list[0][0][0]
+    assert str('  3 trades') in msg_mock.call_args_list[0][0][0]
+
+
+def test_weekly_wrong_input(default_conf, update, ticker, mocker) -> None:
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker
+    )
+
+    telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
+    patch_get_signal(freqtradebot)
+
+    # Try invalid data
+    msg_mock.reset_mock()
+    freqtradebot.state = State.RUNNING
+    # /weekly -3
+    context = MagicMock()
+    context.args = ["-3"]
+    telegram._weekly(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert 'must be an integer greater than 0' in msg_mock.call_args_list[0][0][0]
+
+    # Try invalid data
+    msg_mock.reset_mock()
+    freqtradebot.state = State.RUNNING
+    # /weekly this week
+    context = MagicMock()
+    context.args = ["this week"]
+    telegram._weekly(update=update, context=context)
+    assert str('Weekly Profit over the last 8 weeks (starting from Monday)</b>:') \
+        in msg_mock.call_args_list[0][0][0]
+
+
+def test_monthly_handle(default_conf, update, ticker, limit_buy_order, fee,
+                        limit_sell_order, mocker) -> None:
+    default_conf['max_open_trades'] = 1
+    mocker.patch(
+        'freqtrade.rpc.rpc.CryptoToFiatConverter._find_price',
+        return_value=15000.0
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+
+    telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
+
+    patch_get_signal(freqtradebot)
+
+    # Create some test data
+    freqtradebot.enter_positions()
+    trade = Trade.query.first()
+    assert trade
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+
+    # Simulate fulfilled LIMIT_SELL order for trade
+    oobjs = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobjs)
+
+    trade.close_date = datetime.utcnow()
+    trade.is_open = False
+
+    # Try valid data
+    # /monthly 2
+    context = MagicMock()
+    context.args = ["2"]
+    telegram._monthly(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert 'Monthly Profit over the last 2 months</b>:' in msg_mock.call_args_list[0][0][0]
+    assert 'Month ' in msg_mock.call_args_list[0][0][0]
+    today = datetime.utcnow().date()
+    current_month = f"{today.year}-{today.month:02} "
+    assert current_month in msg_mock.call_args_list[0][0][0]
+    assert str('  0.00006217 BTC') in msg_mock.call_args_list[0][0][0]
+    assert str('  0.933 USD') in msg_mock.call_args_list[0][0][0]
+    assert str('  1 trade') in msg_mock.call_args_list[0][0][0]
+    assert str('  0 trade') in msg_mock.call_args_list[0][0][0]
+
+    # Reset msg_mock
+    msg_mock.reset_mock()
+    context.args = []
+    telegram._monthly(update=update, context=context)
+    assert msg_mock.call_count == 1
+    # Default to 6 months
+    assert 'Monthly Profit over the last 6 months</b>:' in msg_mock.call_args_list[0][0][0]
+    assert 'Month ' in msg_mock.call_args_list[0][0][0]
+    assert current_month in msg_mock.call_args_list[0][0][0]
+    assert str('  0.00006217 BTC') in msg_mock.call_args_list[0][0][0]
+    assert str('  0.933 USD') in msg_mock.call_args_list[0][0][0]
+    assert str('  1 trade') in msg_mock.call_args_list[0][0][0]
+    assert str('  0 trade') in msg_mock.call_args_list[0][0][0]
+
+    # Reset msg_mock
+    msg_mock.reset_mock()
+    freqtradebot.config['max_open_trades'] = 2
+    # Add two other trades
+    n = freqtradebot.enter_positions()
+    assert n == 2
+
+    trades = Trade.query.all()
+    for trade in trades:
+        trade.update_trade(oobj)
+        trade.update_trade(oobjs)
+        trade.close_date = datetime.utcnow()
+        trade.is_open = False
+
+    # /monthly 12
+    context = MagicMock()
+    context.args = ["12"]
+    telegram._monthly(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert 'Monthly Profit over the last 12 months</b>:' in msg_mock.call_args_list[0][0][0]
+    assert str('  0.00018651 BTC') in msg_mock.call_args_list[0][0][0]
+    assert str('  2.798 USD') in msg_mock.call_args_list[0][0][0]
+    assert str('  3 trades') in msg_mock.call_args_list[0][0][0]
+
+    # The one-digit months should contain a zero, Eg: September 2021 = "2021-09"
+    # Since we loaded the last 12 months, any month should appear
+    assert str('-09') in msg_mock.call_args_list[0][0][0]
+
+
+def test_monthly_wrong_input(default_conf, update, ticker, mocker) -> None:
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker
+    )
+
+    telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
+    patch_get_signal(freqtradebot)
+
+    # Try invalid data
+    msg_mock.reset_mock()
+    freqtradebot.state = State.RUNNING
+    # /monthly -3
+    context = MagicMock()
+    context.args = ["-3"]
+    telegram._monthly(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert 'must be an integer greater than 0' in msg_mock.call_args_list[0][0][0]
+
+    # Try invalid data
+    msg_mock.reset_mock()
+    freqtradebot.state = State.RUNNING
+    # /monthly february
+    context = MagicMock()
+    context.args = ["february"]
+    telegram._monthly(update=update, context=context)
+    assert str('Monthly Profit over the last 6 months</b>:') in msg_mock.call_args_list[0][0][0]
 
 
 def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
@@ -445,7 +776,9 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
     trade = Trade.query.first()
 
     # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+
     context = MagicMock()
     # Test with invalid 2nd argument (should silently pass)
     context.args = ["aaa"]
@@ -454,18 +787,22 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
     assert 'No closed trade' in msg_mock.call_args_list[-1][0][0]
     assert '*ROI:* All trades' in msg_mock.call_args_list[-1][0][0]
     mocker.patch('freqtrade.wallets.Wallets.get_starting_balance', return_value=0.01)
-    assert ('∙ `-0.00000500 BTC (-0.50%) (-0.0 \N{GREEK CAPITAL LETTER SIGMA}%)`'
+    assert ('∙ `-0.000005 BTC (-0.50%) (-0.0 \N{GREEK CAPITAL LETTER SIGMA}%)`'
             in msg_mock.call_args_list[-1][0][0])
     msg_mock.reset_mock()
 
     # Update the ticker with a market going up
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', ticker_sell_up)
-    trade.update(limit_sell_order)
+    # Simulate fulfilled LIMIT_SELL order for trade
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
 
-    trade.close_date = datetime.utcnow()
+    trade.close_date = datetime.now(timezone.utc)
     trade.is_open = False
+    Trade.commit()
 
-    telegram._profit(update=update, context=MagicMock())
+    context.args = [3]
+    telegram._profit(update=update, context=context)
     assert msg_mock.call_count == 1
     assert '*ROI:* Closed trades' in msg_mock.call_args_list[-1][0][0]
     assert ('∙ `0.00006217 BTC (6.20%) (0.62 \N{GREEK CAPITAL LETTER SIGMA}%)`'
@@ -479,8 +816,9 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
     assert '*Best Performing:* `ETH/BTC: 6.20%`' in msg_mock.call_args_list[-1][0][0]
 
 
+@pytest.mark.parametrize('is_short', [True, False])
 def test_telegram_stats(default_conf, update, ticker, ticker_sell_up, fee,
-                        limit_buy_order, limit_sell_order, mocker) -> None:
+                        limit_buy_order, limit_sell_order, mocker, is_short) -> None:
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
@@ -492,15 +830,15 @@ def test_telegram_stats(default_conf, update, ticker, ticker_sell_up, fee,
 
     telegram._stats(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
-    # assert 'No trades yet.' in msg_mock.call_args_list[0][0][0]
+    assert 'No trades yet.' in msg_mock.call_args_list[0][0][0]
     msg_mock.reset_mock()
 
     # Create some test data
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
 
     telegram._stats(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
-    assert 'Sell Reason' in msg_mock.call_args_list[-1][0][0]
+    assert 'Exit Reason' in msg_mock.call_args_list[-1][0][0]
     assert 'ROI' in msg_mock.call_args_list[-1][0][0]
     assert 'Avg. Duration' in msg_mock.call_args_list[-1][0][0]
     msg_mock.reset_mock()
@@ -527,7 +865,7 @@ def test_telegram_balance_handle(default_conf, update, mocker, rpc_balance, tick
     assert '*XRP:*' not in result
     assert 'Balance:' in result
     assert 'Est. BTC:' in result
-    assert 'BTC: 12.00000000' in result
+    assert 'BTC: 12' in result
     assert "*3 Other Currencies (< 0.0001 BTC):*" in result
     assert 'BTC: 0.00000309' in result
 
@@ -543,7 +881,7 @@ def test_balance_handle_empty_response(default_conf, update, mocker) -> None:
     telegram._balance(update=update, context=MagicMock())
     result = msg_mock.call_args_list[0][0][0]
     assert msg_mock.call_count == 1
-    assert 'All balances are zero.' in result
+    assert 'Starting capital: `0 BTC' in result
 
 
 def test_balance_handle_empty_response_dry(default_conf, update, mocker) -> None:
@@ -556,7 +894,7 @@ def test_balance_handle_empty_response_dry(default_conf, update, mocker) -> None
     result = msg_mock.call_args_list[0][0][0]
     assert msg_mock.call_count == 1
     assert "*Warning:* Simulated balances in Dry Mode." in result
-    assert "Starting capital: `1000` BTC" in result
+    assert "Starting capital: `1000 BTC`" in result
 
 
 def test_balance_handle_too_large_response(default_conf, update, mocker) -> None:
@@ -570,6 +908,10 @@ def test_balance_handle_too_large_response(default_conf, update, mocker) -> None
             'balance': i,
             'est_stake': 1,
             'stake': 'BTC',
+            'is_position': False,
+            'leverage': 1.0,
+            'position': 0.0,
+            'side': 'long',
         })
     mocker.patch('freqtrade.rpc.rpc.RPC._rpc_balance', return_value={
         'currencies': balances,
@@ -663,7 +1005,7 @@ def test_reload_config_handle(default_conf, update, mocker) -> None:
     assert 'Reloading config' in msg_mock.call_args_list[0][0][0]
 
 
-def test_telegram_forcesell_handle(default_conf, update, ticker, fee,
+def test_telegram_forceexit_handle(default_conf, update, ticker, fee,
                                    ticker_sell_up, mocker) -> None:
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     msg_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
@@ -691,37 +1033,43 @@ def test_telegram_forcesell_handle(default_conf, update, ticker, fee,
     # Increase the price and sell it
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', ticker_sell_up)
 
-    # /forcesell 1
+    # /forceexit 1
     context = MagicMock()
     context.args = ["1"]
-    telegram._forcesell(update=update, context=context)
+    telegram._force_exit(update=update, context=context)
 
     assert msg_mock.call_count == 4
-    last_msg = msg_mock.call_args_list[-1][0][0]
+    last_msg = msg_mock.call_args_list[-2][0][0]
     assert {
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': 'profit',
+        'leverage': 1.0,
         'limit': 1.173e-05,
         'amount': 91.07468123,
         'order_type': 'limit',
         'open_rate': 1.098e-05,
         'current_rate': 1.173e-05,
+        'direction': 'Long',
         'profit_amount': 6.314e-05,
         'profit_ratio': 0.0629778,
         'stake_currency': 'BTC',
+        'base_currency': 'ETH',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.FORCE_SELL.value,
+        'buy_tag': ANY,
+        'enter_tag': ANY,
+        'sell_reason': ExitType.FORCE_EXIT.value,
+        'exit_reason': ExitType.FORCE_EXIT.value,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
     } == last_msg
 
 
-def test_telegram_forcesell_down_handle(default_conf, update, ticker, fee,
-                                        ticker_sell_down, mocker) -> None:
+def test_telegram_force_exit_down_handle(default_conf, update, ticker, fee,
+                                         ticker_sell_down, mocker) -> None:
     mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
                  return_value=15000.0)
     msg_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
@@ -753,37 +1101,43 @@ def test_telegram_forcesell_down_handle(default_conf, update, ticker, fee,
     trade = Trade.query.first()
     assert trade
 
-    # /forcesell 1
+    # /forceexit 1
     context = MagicMock()
     context.args = ["1"]
-    telegram._forcesell(update=update, context=context)
+    telegram._force_exit(update=update, context=context)
 
     assert msg_mock.call_count == 4
 
-    last_msg = msg_mock.call_args_list[-1][0][0]
+    last_msg = msg_mock.call_args_list[-2][0][0]
     assert {
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': 'loss',
+        'leverage': 1.0,
         'limit': 1.043e-05,
         'amount': 91.07468123,
         'order_type': 'limit',
         'open_rate': 1.098e-05,
         'current_rate': 1.043e-05,
+        'direction': 'Long',
         'profit_amount': -5.497e-05,
         'profit_ratio': -0.05482878,
         'stake_currency': 'BTC',
+        'base_currency': 'ETH',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.FORCE_SELL.value,
+        'buy_tag': ANY,
+        'enter_tag': ANY,
+        'sell_reason': ExitType.FORCE_EXIT.value,
+        'exit_reason': ExitType.FORCE_EXIT.value,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
     } == last_msg
 
 
-def test_forcesell_all_handle(default_conf, update, ticker, fee, mocker) -> None:
+def test_forceexit_all_handle(default_conf, update, ticker, fee, mocker) -> None:
     patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
                  return_value=15000.0)
@@ -806,37 +1160,43 @@ def test_forcesell_all_handle(default_conf, update, ticker, fee, mocker) -> None
     freqtradebot.enter_positions()
     msg_mock.reset_mock()
 
-    # /forcesell all
+    # /forceexit all
     context = MagicMock()
     context.args = ["all"]
-    telegram._forcesell(update=update, context=context)
+    telegram._force_exit(update=update, context=context)
 
     # Called for each trade 2 times
     assert msg_mock.call_count == 8
-    msg = msg_mock.call_args_list[1][0][0]
+    msg = msg_mock.call_args_list[0][0][0]
     assert {
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': 'loss',
+        'leverage': 1.0,
         'limit': 1.099e-05,
         'amount': 91.07468123,
         'order_type': 'limit',
         'open_rate': 1.098e-05,
         'current_rate': 1.099e-05,
+        'direction': 'Long',
         'profit_amount': -4.09e-06,
         'profit_ratio': -0.00408133,
         'stake_currency': 'BTC',
+        'base_currency': 'ETH',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.FORCE_SELL.value,
+        'buy_tag': ANY,
+        'enter_tag': ANY,
+        'sell_reason': ExitType.FORCE_EXIT.value,
+        'exit_reason': ExitType.FORCE_EXIT.value,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
     } == msg
 
 
-def test_forcesell_handle_invalid(default_conf, update, mocker) -> None:
+def test_forceexit_handle_invalid(default_conf, update, mocker) -> None:
     mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
                  return_value=15000.0)
 
@@ -845,58 +1205,103 @@ def test_forcesell_handle_invalid(default_conf, update, mocker) -> None:
 
     # Trader is not running
     freqtradebot.state = State.STOPPED
-    # /forcesell 1
+    # /forceexit 1
     context = MagicMock()
     context.args = ["1"]
-    telegram._forcesell(update=update, context=context)
+    telegram._force_exit(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'not running' in msg_mock.call_args_list[0][0][0]
 
-    # No argument
-    msg_mock.reset_mock()
-    freqtradebot.state = State.RUNNING
-    context = MagicMock()
-    context.args = []
-    telegram._forcesell(update=update, context=context)
-    assert msg_mock.call_count == 1
-    assert "You must specify a trade-id or 'all'." in msg_mock.call_args_list[0][0][0]
-
     # Invalid argument
     msg_mock.reset_mock()
     freqtradebot.state = State.RUNNING
-    # /forcesell 123456
+    # /forceexit 123456
     context = MagicMock()
     context.args = ["123456"]
-    telegram._forcesell(update=update, context=context)
+    telegram._force_exit(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'invalid argument' in msg_mock.call_args_list[0][0][0]
 
 
-def test_forcebuy_handle(default_conf, update, mocker) -> None:
+def test_force_exit_no_pair(default_conf, update, ticker, fee, mocker) -> None:
+    default_conf['max_open_trades'] = 4
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+        _is_dry_limit_order_filled=MagicMock(return_value=True),
+    )
+    femock = mocker.patch('freqtrade.rpc.rpc.RPC._rpc_force_exit')
+    telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
+
+    patch_get_signal(freqtradebot)
+
+    # /forceexit
+    context = MagicMock()
+    context.args = []
+    telegram._force_exit(update=update, context=context)
+    # No pair
+    assert msg_mock.call_args_list[0][1]['msg'] == 'No open trade found.'
+
+    # Create some test data
+    freqtradebot.enter_positions()
+    msg_mock.reset_mock()
+
+    # /forceexit
+    telegram._force_exit(update=update, context=context)
+    keyboard = msg_mock.call_args_list[0][1]['keyboard']
+    # 4 pairs + cancel
+    assert reduce(lambda acc, x: acc + len(x), keyboard, 0) == 5
+    assert keyboard[-1][0].text == "Cancel"
+
+    assert keyboard[1][0].callback_data == 'force_exit__2 '
+    update = MagicMock()
+    update.callback_query = MagicMock()
+    update.callback_query.data = keyboard[1][0].callback_data
+    telegram._force_exit_inline(update, None)
+    assert update.callback_query.answer.call_count == 1
+    assert update.callback_query.edit_message_text.call_count == 1
+    assert femock.call_count == 1
+    assert femock.call_args_list[0][0][0] == '2'
+
+    # Retry exiting - but cancel instead
+    update.callback_query.reset_mock()
+    telegram._force_exit(update=update, context=context)
+    # Use cancel button
+    update.callback_query.data = keyboard[-1][0].callback_data
+    telegram._force_exit_inline(update, None)
+    query = update.callback_query
+    assert query.answer.call_count == 1
+    assert query.edit_message_text.call_count == 1
+    assert query.edit_message_text.call_args_list[-1][1]['text'] == "Force exit canceled."
+
+
+def test_force_enter_handle(default_conf, update, mocker) -> None:
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
 
     fbuy_mock = MagicMock(return_value=None)
-    mocker.patch('freqtrade.rpc.RPC._rpc_forcebuy', fbuy_mock)
+    mocker.patch('freqtrade.rpc.RPC._rpc_force_entry', fbuy_mock)
 
     telegram, freqtradebot, _ = get_telegram_testobject(mocker, default_conf)
     patch_get_signal(freqtradebot)
 
-    # /forcebuy ETH/BTC
+    # /forcelong ETH/BTC
     context = MagicMock()
     context.args = ["ETH/BTC"]
-    telegram._forcebuy(update=update, context=context)
+    telegram._force_enter(update=update, context=context, order_side=SignalDirection.LONG)
 
     assert fbuy_mock.call_count == 1
     assert fbuy_mock.call_args_list[0][0][0] == 'ETH/BTC'
     assert fbuy_mock.call_args_list[0][0][1] is None
+    assert fbuy_mock.call_args_list[0][1]['order_side'] == SignalDirection.LONG
 
     # Reset and retry with specified price
     fbuy_mock = MagicMock(return_value=None)
-    mocker.patch('freqtrade.rpc.RPC._rpc_forcebuy', fbuy_mock)
-    # /forcebuy ETH/BTC 0.055
+    mocker.patch('freqtrade.rpc.RPC._rpc_force_entry', fbuy_mock)
+    # /forcelong ETH/BTC 0.055
     context = MagicMock()
     context.args = ["ETH/BTC", "0.055"]
-    telegram._forcebuy(update=update, context=context)
+    telegram._force_enter(update=update, context=context, order_side=SignalDirection.LONG)
 
     assert fbuy_mock.call_count == 1
     assert fbuy_mock.call_args_list[0][0][0] == 'ETH/BTC'
@@ -904,24 +1309,24 @@ def test_forcebuy_handle(default_conf, update, mocker) -> None:
     assert fbuy_mock.call_args_list[0][0][1] == 0.055
 
 
-def test_forcebuy_handle_exception(default_conf, update, mocker) -> None:
+def test_force_enter_handle_exception(default_conf, update, mocker) -> None:
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
 
     telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
     patch_get_signal(freqtradebot)
 
     update.message.text = '/forcebuy ETH/Nonepair'
-    telegram._forcebuy(update=update, context=MagicMock())
+    telegram._force_enter(update=update, context=MagicMock(), order_side=SignalDirection.LONG)
 
     assert msg_mock.call_count == 1
-    assert msg_mock.call_args_list[0][0][0] == 'Forcebuy not enabled.'
+    assert msg_mock.call_args_list[0][0][0] == 'Force_entry not enabled.'
 
 
-def test_forcebuy_no_pair(default_conf, update, mocker) -> None:
+def test_force_enter_no_pair(default_conf, update, mocker) -> None:
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
 
     fbuy_mock = MagicMock(return_value=None)
-    mocker.patch('freqtrade.rpc.RPC._rpc_forcebuy', fbuy_mock)
+    mocker.patch('freqtrade.rpc.RPC._rpc_force_entry', fbuy_mock)
 
     telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
 
@@ -929,23 +1334,24 @@ def test_forcebuy_no_pair(default_conf, update, mocker) -> None:
 
     context = MagicMock()
     context.args = []
-    telegram._forcebuy(update=update, context=context)
+    telegram._force_enter(update=update, context=context, order_side=SignalDirection.LONG)
 
     assert fbuy_mock.call_count == 0
     assert msg_mock.call_count == 1
     assert msg_mock.call_args_list[0][1]['msg'] == 'Which pair?'
     # assert msg_mock.call_args_list[0][1]['callback_query_handler'] == 'forcebuy'
     keyboard = msg_mock.call_args_list[0][1]['keyboard']
-    assert reduce(lambda acc, x: acc + len(x), keyboard, 0) == 4
+    # One additional button - cancel
+    assert reduce(lambda acc, x: acc + len(x), keyboard, 0) == 5
     update = MagicMock()
     update.callback_query = MagicMock()
-    update.callback_query.data = 'XRP/USDT'
-    telegram._forcebuy_inline(update, None)
+    update.callback_query.data = 'XRP/USDT_||_long'
+    telegram._force_enter_inline(update, None)
     assert fbuy_mock.call_count == 1
 
 
-def test_performance_handle(default_conf, update, ticker, fee,
-                            limit_buy_order, limit_sell_order, mocker) -> None:
+def test_telegram_performance_handle(default_conf, update, ticker, fee,
+                                     limit_buy_order, limit_sell_order, mocker) -> None:
 
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
@@ -961,10 +1367,12 @@ def test_performance_handle(default_conf, update, ticker, fee,
     assert trade
 
     # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
 
     # Simulate fulfilled LIMIT_SELL order for trade
-    trade.update(limit_sell_order)
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
 
     trade.close_date = datetime.utcnow()
     trade.is_open = False
@@ -974,6 +1382,144 @@ def test_performance_handle(default_conf, update, ticker, fee,
     assert '<code>ETH/BTC\t0.00006217 BTC (6.20%) (1)</code>' in msg_mock.call_args_list[0][0][0]
 
 
+def test_telegram_entry_tag_performance_handle(
+        default_conf, update, ticker, fee, limit_buy_order, limit_sell_order, mocker) -> None:
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
+    patch_get_signal(freqtradebot)
+
+    # Create some test data
+    freqtradebot.enter_positions()
+    trade = Trade.query.first()
+    assert trade
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+
+    trade.enter_tag = "TESTBUY"
+    # Simulate fulfilled LIMIT_SELL order for trade
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
+
+    trade.close_date = datetime.utcnow()
+    trade.is_open = False
+    context = MagicMock()
+    telegram._enter_tag_performance(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert 'Entry Tag Performance' in msg_mock.call_args_list[0][0][0]
+    assert '<code>TESTBUY\t0.00006217 BTC (6.20%) (1)</code>' in msg_mock.call_args_list[0][0][0]
+
+    context.args = [trade.pair]
+    telegram._enter_tag_performance(update=update, context=context)
+    assert msg_mock.call_count == 2
+
+    msg_mock.reset_mock()
+    mocker.patch('freqtrade.rpc.rpc.RPC._rpc_enter_tag_performance',
+                 side_effect=RPCException('Error'))
+    telegram._enter_tag_performance(update=update, context=MagicMock())
+
+    assert msg_mock.call_count == 1
+    assert "Error" in msg_mock.call_args_list[0][0][0]
+
+
+def test_telegram_exit_reason_performance_handle(default_conf, update, ticker, fee,
+                                                 limit_buy_order, limit_sell_order, mocker) -> None:
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
+    patch_get_signal(freqtradebot)
+
+    # Create some test data
+    freqtradebot.enter_positions()
+    trade = Trade.query.first()
+    assert trade
+    trade.exit_reason = 'TESTSELL'
+    # Simulate fulfilled LIMIT_BUY order for trade
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+
+    # Simulate fulfilled LIMIT_SELL order for trade
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
+
+    trade.close_date = datetime.utcnow()
+    trade.is_open = False
+    context = MagicMock()
+    telegram._exit_reason_performance(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert 'Exit Reason Performance' in msg_mock.call_args_list[0][0][0]
+    assert '<code>TESTSELL\t0.00006217 BTC (6.20%) (1)</code>' in msg_mock.call_args_list[0][0][0]
+    context.args = [trade.pair]
+
+    telegram._exit_reason_performance(update=update, context=context)
+    assert msg_mock.call_count == 2
+
+    msg_mock.reset_mock()
+    mocker.patch('freqtrade.rpc.rpc.RPC._rpc_exit_reason_performance',
+                 side_effect=RPCException('Error'))
+    telegram._exit_reason_performance(update=update, context=MagicMock())
+
+    assert msg_mock.call_count == 1
+    assert "Error" in msg_mock.call_args_list[0][0][0]
+
+
+def test_telegram_mix_tag_performance_handle(default_conf, update, ticker, fee,
+                                             limit_buy_order, limit_sell_order, mocker) -> None:
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
+    patch_get_signal(freqtradebot)
+
+    # Create some test data
+    freqtradebot.enter_positions()
+    trade = Trade.query.first()
+    assert trade
+
+    trade.enter_tag = "TESTBUY"
+    trade.exit_reason = "TESTSELL"
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    oobj = Order.parse_from_ccxt_object(limit_buy_order, limit_buy_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+
+    # Simulate fulfilled LIMIT_SELL order for trade
+    oobj = Order.parse_from_ccxt_object(limit_sell_order, limit_sell_order['symbol'], 'sell')
+    trade.update_trade(oobj)
+
+    trade.close_date = datetime.utcnow()
+    trade.is_open = False
+
+    context = MagicMock()
+    telegram._mix_tag_performance(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert 'Mix Tag Performance' in msg_mock.call_args_list[0][0][0]
+    assert ('<code>TESTBUY TESTSELL\t0.00006217 BTC (6.20%) (1)</code>'
+            in msg_mock.call_args_list[0][0][0])
+
+    context.args = [trade.pair]
+    telegram._mix_tag_performance(update=update, context=context)
+    assert msg_mock.call_count == 2
+
+    msg_mock.reset_mock()
+    mocker.patch('freqtrade.rpc.rpc.RPC._rpc_mix_tag_performance',
+                 side_effect=RPCException('Error'))
+    telegram._mix_tag_performance(update=update, context=MagicMock())
+
+    assert msg_mock.call_count == 1
+    assert "Error" in msg_mock.call_args_list[0][0][0]
+
+
 def test_count_handle(default_conf, update, ticker, fee, mocker) -> None:
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
@@ -997,9 +1543,9 @@ def test_count_handle(default_conf, update, ticker, fee, mocker) -> None:
 
     msg = ('<pre>  current    max    total stake\n---------  -----  -------------\n'
            '        1      {}          {}</pre>').format(
-            default_conf['max_open_trades'],
-            default_conf['stake_amount']
-        )
+        default_conf['max_open_trades'],
+        default_conf['stake_amount']
+    )
     assert msg in msg_mock.call_args_list[0][0][0]
 
 
@@ -1094,6 +1640,13 @@ def test_blacklist_static(default_conf, update, mocker) -> None:
             in msg_mock.call_args_list[0][0][0])
     assert freqtradebot.pairlists.blacklist == ["DOGE/BTC", "HOT/BTC", "ETH/BTC", "XRP/.*"]
 
+    msg_mock.reset_mock()
+    context.args = ["DOGE/BTC"]
+    telegram._blacklist_delete(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert ("Blacklist contains 3 pairs\n`HOT/BTC, ETH/BTC, XRP/.*`"
+            in msg_mock.call_args_list[0][0][0])
+
 
 def test_telegram_logs(default_conf, update, mocker) -> None:
     mocker.patch.multiple(
@@ -1159,7 +1712,10 @@ def test_edge_enabled(edge_conf, update, mocker) -> None:
     assert 'Winrate' not in msg_mock.call_args_list[0][0][0]
 
 
-def test_telegram_trades(mocker, update, default_conf, fee):
+@pytest.mark.parametrize('is_short,regex_pattern',
+                         [(True, r"just now[ ]*XRP\/BTC \(#3\)  -1.00% \("),
+                          (False, r"just now[ ]*XRP\/BTC \(#3\)  1.00% \(")])
+def test_telegram_trades(mocker, update, default_conf, fee, is_short, regex_pattern):
 
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
@@ -1177,7 +1733,7 @@ def test_telegram_trades(mocker, update, default_conf, fee):
     assert "<pre>" not in msg_mock.call_args_list[0][0][0]
     msg_mock.reset_mock()
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
 
     context = MagicMock()
     context.args = [5]
@@ -1187,11 +1743,11 @@ def test_telegram_trades(mocker, update, default_conf, fee):
     assert "Profit (" in msg_mock.call_args_list[0][0][0]
     assert "Close Date" in msg_mock.call_args_list[0][0][0]
     assert "<pre>" in msg_mock.call_args_list[0][0][0]
-    assert bool(re.search(r"just now[ ]*XRP\/BTC \(#3\)  1.00% \(",
-                msg_mock.call_args_list[0][0][0]))
+    assert bool(re.search(regex_pattern, msg_mock.call_args_list[0][0][0]))
 
 
-def test_telegram_delete_trade(mocker, update, default_conf, fee):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_telegram_delete_trade(mocker, update, default_conf, fee, is_short):
 
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
     context = MagicMock()
@@ -1201,7 +1757,7 @@ def test_telegram_delete_trade(mocker, update, default_conf, fee):
     assert "Trade-id not set." in msg_mock.call_args_list[0][0][0]
 
     msg_mock.reset_mock()
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
 
     context = MagicMock()
     context.args = [1]
@@ -1221,12 +1777,20 @@ def test_help_handle(default_conf, update, mocker) -> None:
 
 def test_version_handle(default_conf, update, mocker) -> None:
 
-    telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
+    telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram._version(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert '*Version:* `{}`'.format(__version__) in msg_mock.call_args_list[0][0][0]
 
+    msg_mock.reset_mock()
+    freqtradebot.strategy.version = lambda: '1.1.1'
+
+    telegram._version(update=update, context=MagicMock())
+    assert msg_mock.call_count == 1
+    assert '*Version:* `{}`'.format(__version__) in msg_mock.call_args_list[0][0][0]
+    assert '*Strategy version: * `1.1.1`' in msg_mock.call_args_list[0][0][0]
+
 
 def test_show_config_handle(default_conf, update, mocker) -> None:
 
@@ -1238,7 +1802,7 @@ def test_show_config_handle(default_conf, update, mocker) -> None:
     assert msg_mock.call_count == 1
     assert '*Mode:* `{}`'.format('Dry-run') in msg_mock.call_args_list[0][0][0]
     assert '*Exchange:* `binance`' in msg_mock.call_args_list[0][0][0]
-    assert '*Strategy:* `StrategyTestV2`' in msg_mock.call_args_list[0][0][0]
+    assert f'*Strategy:* `{CURRENT_TEST_STRATEGY}`' in msg_mock.call_args_list[0][0][0]
     assert '*Stoploss:* `-0.1`' in msg_mock.call_args_list[0][0][0]
 
     msg_mock.reset_mock()
@@ -1247,21 +1811,29 @@ def test_show_config_handle(default_conf, update, mocker) -> None:
     assert msg_mock.call_count == 1
     assert '*Mode:* `{}`'.format('Dry-run') in msg_mock.call_args_list[0][0][0]
     assert '*Exchange:* `binance`' in msg_mock.call_args_list[0][0][0]
-    assert '*Strategy:* `StrategyTestV2`' in msg_mock.call_args_list[0][0][0]
+    assert f'*Strategy:* `{CURRENT_TEST_STRATEGY}`' in msg_mock.call_args_list[0][0][0]
     assert '*Initial Stoploss:* `-0.1`' in msg_mock.call_args_list[0][0][0]
 
 
-def test_send_msg_buy_notification(default_conf, mocker, caplog) -> None:
+@pytest.mark.parametrize('message_type,enter,enter_signal,leverage', [
+    (RPCMessageType.ENTRY, 'Long', 'long_signal_01', None),
+    (RPCMessageType.ENTRY, 'Long', 'long_signal_01', 1.0),
+    (RPCMessageType.ENTRY, 'Long', 'long_signal_01', 5.0),
+    (RPCMessageType.ENTRY, 'Short', 'short_signal_01', 2.0)])
+def test_send_msg_buy_notification(default_conf, mocker, caplog, message_type,
+                                   enter, enter_signal, leverage) -> None:
 
     msg = {
-        'type': RPCMessageType.BUY,
+        'type': message_type,
         'trade_id': 1,
-        'buy_tag': 'buy_signal_01',
+        'enter_tag': enter_signal,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
+        'leverage': leverage,
         'limit': 1.099e-05,
         'order_type': 'limit',
-        'stake_amount': 0.001,
+        'direction': enter,
+        'stake_amount': 0.01465333,
         'stake_amount_fiat': 0.0,
         'stake_currency': 'BTC',
         'fiat_currency': 'USD',
@@ -1272,13 +1844,17 @@ def test_send_msg_buy_notification(default_conf, mocker, caplog) -> None:
     telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram.send_msg(msg)
-    assert msg_mock.call_args[0][0] \
-        == '\N{LARGE BLUE CIRCLE} *Binance:* Buying ETH/BTC (#1)\n' \
-           '*Buy Tag:* `buy_signal_01`\n' \
-           '*Amount:* `1333.33333333`\n' \
-           '*Open Rate:* `0.00001099`\n' \
-           '*Current Rate:* `0.00001099`\n' \
-           '*Total:* `(0.00100000 BTC, 12.345 USD)`'
+    leverage_text = f'*Leverage:* `{leverage}`\n' if leverage and leverage != 1.0 else ''
+
+    assert msg_mock.call_args[0][0] == (
+        f'\N{LARGE BLUE CIRCLE} *Binance:* {enter} ETH/BTC (#1)\n'
+        f'*Enter Tag:* `{enter_signal}`\n'
+        '*Amount:* `1333.33333333`\n'
+        f'{leverage_text}'
+        '*Open Rate:* `0.00001099`\n'
+        '*Current Rate:* `0.00001099`\n'
+        '*Total:* `(0.01465333 BTC, 180.895 USD)`'
+    )
 
     freqtradebot.config['telegram']['notification_settings'] = {'buy': 'off'}
     caplog.clear()
@@ -1296,20 +1872,23 @@ def test_send_msg_buy_notification(default_conf, mocker, caplog) -> None:
     msg_mock.call_args_list[0][1]['disable_notification'] is True
 
 
-def test_send_msg_buy_cancel_notification(default_conf, mocker) -> None:
+@pytest.mark.parametrize('message_type,enter_signal', [
+    (RPCMessageType.ENTRY_CANCEL, 'long_signal_01'),
+    (RPCMessageType.ENTRY_CANCEL, 'short_signal_01')])
+def test_send_msg_buy_cancel_notification(default_conf, mocker, message_type, enter_signal) -> None:
 
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram.send_msg({
-        'type': RPCMessageType.BUY_CANCEL,
-        'buy_tag': 'buy_signal_01',
+        'type': message_type,
+        'enter_tag': enter_signal,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'reason': CANCEL_REASON['TIMEOUT']
     })
     assert (msg_mock.call_args[0][0] == '\N{WARNING SIGN} *Binance:* '
-            'Cancelling open buy Order for ETH/BTC (#1). '
+            'Cancelling enter Order for ETH/BTC (#1). '
             'Reason: cancelled due to timeout.')
 
 
@@ -1341,24 +1920,42 @@ def test_send_msg_protection_notification(default_conf, mocker, time_machine) ->
             "*All pairs* will be locked until `2021-09-01 06:45:00`.")
 
 
-def test_send_msg_buy_fill_notification(default_conf, mocker) -> None:
+@pytest.mark.parametrize('message_type,entered,enter_signal,leverage', [
+    (RPCMessageType.ENTRY_FILL, 'Long', 'long_signal_01', 1.0),
+    (RPCMessageType.ENTRY_FILL, 'Long', 'long_signal_02', 2.0),
+    (RPCMessageType.ENTRY_FILL, 'Short', 'short_signal_01', 2.0),
+])
+def test_send_msg_entry_fill_notification(default_conf, mocker, message_type, entered,
+                                          enter_signal, leverage) -> None:
 
-    default_conf['telegram']['notification_settings']['buy_fill'] = 'on'
+    default_conf['telegram']['notification_settings']['entry_fill'] = 'on'
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram.send_msg({
-        'type': RPCMessageType.BUY_FILL,
-        'buy_tag': 'buy_signal_01',
+        'type': message_type,
         'trade_id': 1,
+        'enter_tag': enter_signal,
         'exchange': 'Binance',
-        'pair': 'ETH/USDT',
-        'open_rate': 200,
-        'stake_amount': 100,
-        'amount': 0.5,
-        'open_date': arrow.utcnow().datetime
+        'pair': 'ETH/BTC',
+        'leverage': leverage,
+        'stake_amount': 0.01465333,
+        'direction': entered,
+        # 'stake_amount_fiat': 0.0,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'USD',
+        'open_rate': 1.099e-05,
+        'amount': 1333.3333333333335,
+        'open_date': arrow.utcnow().shift(hours=-1)
     })
-    assert (msg_mock.call_args[0][0] == '\N{LARGE CIRCLE} *Binance:* '
-            'Buy order for ETH/USDT (#1) filled for 200.')
+    leverage_text = f'*Leverage:* `{leverage}`\n' if leverage != 1.0 else ''
+    assert msg_mock.call_args[0][0] == (
+        f'\N{CHECK MARK} *Binance:* {entered}ed ETH/BTC (#1)\n'
+        f'*Enter Tag:* `{enter_signal}`\n'
+        '*Amount:* `1333.33333333`\n'
+        f"{leverage_text}"
+        '*Open Rate:* `0.00001099`\n'
+        '*Total:* `(0.01465333 BTC, 180.895 USD)`'
+    )
 
 
 def test_send_msg_sell_notification(default_conf, mocker) -> None:
@@ -1368,10 +1965,12 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
     old_convamount = telegram._rpc._fiat_converter.convert_amount
     telegram._rpc._fiat_converter.convert_amount = lambda a, b, c: -24.812
     telegram.send_msg({
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
+        'leverage': 1.0,
+        'direction': 'Long',
         'gain': 'loss',
         'limit': 3.201e-05,
         'amount': 1333.3333333333335,
@@ -1382,27 +1981,31 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
         'profit_ratio': -0.57405275,
         'stake_currency': 'ETH',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.STOP_LOSS.value,
+        'enter_tag': 'buy_signal1',
+        'exit_reason': ExitType.STOP_LOSS.value,
         'open_date': arrow.utcnow().shift(hours=-1),
         'close_date': arrow.utcnow(),
     })
-    assert msg_mock.call_args[0][0] \
-        == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH (#1)\n'
-            '*Profit:* `-57.41% (loss: -0.05746268 ETH / -24.812 USD)`\n'
-            '*Sell Reason:* `stop_loss`\n'
-            '*Duration:* `1:00:00 (60.0 min)`\n'
-            '*Amount:* `1333.33333333`\n'
-            '*Open Rate:* `0.00007500`\n'
-            '*Current Rate:* `0.00003201`\n'
-            '*Close Rate:* `0.00003201`'
-            )
+    assert msg_mock.call_args[0][0] == (
+        '\N{WARNING SIGN} *Binance:* Exiting KEY/ETH (#1)\n'
+        '*Unrealized Profit:* `-57.41% (loss: -0.05746268 ETH / -24.812 USD)`\n'
+        '*Enter Tag:* `buy_signal1`\n'
+        '*Exit Reason:* `stop_loss`\n'
+        '*Duration:* `1:00:00 (60.0 min)`\n'
+        '*Direction:* `Long`\n'
+        '*Amount:* `1333.33333333`\n'
+        '*Open Rate:* `0.00007500`\n'
+        '*Current Rate:* `0.00003201`\n'
+        '*Close Rate:* `0.00003201`'
+    )
 
     msg_mock.reset_mock()
     telegram.send_msg({
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
+        'direction': 'Long',
         'gain': 'loss',
         'limit': 3.201e-05,
         'amount': 1333.3333333333335,
@@ -1412,20 +2015,23 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
         'profit_amount': -0.05746268,
         'profit_ratio': -0.57405275,
         'stake_currency': 'ETH',
-        'sell_reason': SellType.STOP_LOSS.value,
+        'enter_tag': 'buy_signal1',
+        'exit_reason': ExitType.STOP_LOSS.value,
         'open_date': arrow.utcnow().shift(days=-1, hours=-2, minutes=-30),
         'close_date': arrow.utcnow(),
     })
-    assert msg_mock.call_args[0][0] \
-        == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH (#1)\n'
-            '*Profit:* `-57.41%`\n'
-            '*Sell Reason:* `stop_loss`\n'
-            '*Duration:* `1 day, 2:30:00 (1590.0 min)`\n'
-            '*Amount:* `1333.33333333`\n'
-            '*Open Rate:* `0.00007500`\n'
-            '*Current Rate:* `0.00003201`\n'
-            '*Close Rate:* `0.00003201`'
-            )
+    assert msg_mock.call_args[0][0] == (
+        '\N{WARNING SIGN} *Binance:* Exiting KEY/ETH (#1)\n'
+        '*Unrealized Profit:* `-57.41%`\n'
+        '*Enter Tag:* `buy_signal1`\n'
+        '*Exit Reason:* `stop_loss`\n'
+        '*Duration:* `1 day, 2:30:00 (1590.0 min)`\n'
+        '*Direction:* `Long`\n'
+        '*Amount:* `1333.33333333`\n'
+        '*Open Rate:* `0.00007500`\n'
+        '*Current Rate:* `0.00003201`\n'
+        '*Close Rate:* `0.00003201`'
+    )
     # Reset singleton function to avoid random breaks
     telegram._rpc._fiat_converter.convert_amount = old_convamount
 
@@ -1437,58 +2043,76 @@ def test_send_msg_sell_cancel_notification(default_conf, mocker) -> None:
     old_convamount = telegram._rpc._fiat_converter.convert_amount
     telegram._rpc._fiat_converter.convert_amount = lambda a, b, c: -24.812
     telegram.send_msg({
-        'type': RPCMessageType.SELL_CANCEL,
+        'type': RPCMessageType.EXIT_CANCEL,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
         'reason': 'Cancelled on exchange'
     })
-    assert msg_mock.call_args[0][0] \
-        == ('\N{WARNING SIGN} *Binance:* Cancelling open sell Order for KEY/ETH (#1).'
-            ' Reason: Cancelled on exchange.')
+    assert msg_mock.call_args[0][0] == (
+        '\N{WARNING SIGN} *Binance:* Cancelling exit Order for KEY/ETH (#1).'
+        ' Reason: Cancelled on exchange.')
 
     msg_mock.reset_mock()
     telegram.send_msg({
-        'type': RPCMessageType.SELL_CANCEL,
+        'type': RPCMessageType.EXIT_CANCEL,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
         'reason': 'timeout'
     })
-    assert msg_mock.call_args[0][0] \
-        == ('\N{WARNING SIGN} *Binance:* Cancelling open sell Order for KEY/ETH (#1).'
-            ' Reason: timeout.')
+    assert msg_mock.call_args[0][0] == (
+        '\N{WARNING SIGN} *Binance:* Cancelling exit Order for KEY/ETH (#1). Reason: timeout.')
     # Reset singleton function to avoid random breaks
     telegram._rpc._fiat_converter.convert_amount = old_convamount
 
 
-def test_send_msg_sell_fill_notification(default_conf, mocker) -> None:
+@pytest.mark.parametrize('direction,enter_signal,leverage', [
+    ('Long', 'long_signal_01', None),
+    ('Long', 'long_signal_01', 1.0),
+    ('Long', 'long_signal_01', 5.0),
+    ('Short', 'short_signal_01', 2.0)])
+def test_send_msg_sell_fill_notification(default_conf, mocker, direction,
+                                         enter_signal, leverage) -> None:
 
-    default_conf['telegram']['notification_settings']['sell_fill'] = 'on'
+    default_conf['telegram']['notification_settings']['exit_fill'] = 'on'
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram.send_msg({
-        'type': RPCMessageType.SELL_FILL,
+        'type': RPCMessageType.EXIT_FILL,
         'trade_id': 1,
         'exchange': 'Binance',
-        'pair': 'ETH/USDT',
+        'pair': 'KEY/ETH',
+        'leverage': leverage,
+        'direction': direction,
         'gain': 'loss',
         'limit': 3.201e-05,
-        'amount': 0.1,
+        'amount': 1333.3333333333335,
         'order_type': 'market',
-        'open_rate': 500,
-        'close_rate': 550,
-        'current_rate': 3.201e-05,
+        'open_rate': 7.5e-05,
+        'close_rate': 3.201e-05,
         'profit_amount': -0.05746268,
         'profit_ratio': -0.57405275,
         'stake_currency': 'ETH',
-        'fiat_currency': 'USD',
-        'sell_reason': SellType.STOP_LOSS.value,
-        'open_date': arrow.utcnow().shift(hours=-1),
+        'enter_tag': enter_signal,
+        'exit_reason': ExitType.STOP_LOSS.value,
+        'open_date': arrow.utcnow().shift(days=-1, hours=-2, minutes=-30),
         'close_date': arrow.utcnow(),
     })
-    assert msg_mock.call_args[0][0] \
-        == ('\N{LARGE CIRCLE} *Binance:* Sell order for ETH/USDT (#1) filled for 550.')
+
+    leverage_text = f'*Leverage:* `{leverage}`\n' if leverage and leverage != 1.0 else ''
+    assert msg_mock.call_args[0][0] == (
+        '\N{WARNING SIGN} *Binance:* Exited KEY/ETH (#1)\n'
+        '*Profit:* `-57.41%`\n'
+        f'*Enter Tag:* `{enter_signal}`\n'
+        '*Exit Reason:* `stop_loss`\n'
+        '*Duration:* `1 day, 2:30:00 (1590.0 min)`\n'
+        f"*Direction:* `{direction}`\n"
+        f"{leverage_text}"
+        '*Amount:* `1333.33333333`\n'
+        '*Open Rate:* `0.00007500`\n'
+        '*Close Rate:* `0.00003201`'
+    )
 
 
 def test_send_msg_status_notification(default_conf, mocker) -> None:
@@ -1527,19 +2151,26 @@ def test_send_msg_unknown_type(default_conf, mocker) -> None:
         })
 
 
-def test_send_msg_buy_notification_no_fiat(default_conf, mocker) -> None:
+@pytest.mark.parametrize('message_type,enter,enter_signal,leverage', [
+    (RPCMessageType.ENTRY, 'Long', 'long_signal_01', None),
+    (RPCMessageType.ENTRY, 'Long', 'long_signal_01', 2.0),
+    (RPCMessageType.ENTRY, 'Short', 'short_signal_01', 2.0)])
+def test_send_msg_buy_notification_no_fiat(
+        default_conf, mocker, message_type, enter, enter_signal, leverage) -> None:
     del default_conf['fiat_display_currency']
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram.send_msg({
-        'type': RPCMessageType.BUY,
-        'buy_tag': 'buy_signal_01',
+        'type': message_type,
+        'enter_tag': enter_signal,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
+        'leverage': leverage,
         'limit': 1.099e-05,
         'order_type': 'limit',
-        'stake_amount': 0.001,
+        'direction': enter,
+        'stake_amount': 0.01465333,
         'stake_amount_fiat': 0.0,
         'stake_currency': 'BTC',
         'fiat_currency': None,
@@ -1547,24 +2178,38 @@ def test_send_msg_buy_notification_no_fiat(default_conf, mocker) -> None:
         'amount': 1333.3333333333335,
         'open_date': arrow.utcnow().shift(hours=-1)
     })
-    assert msg_mock.call_args[0][0] == ('\N{LARGE BLUE CIRCLE} *Binance:* Buying ETH/BTC (#1)\n'
-                                        '*Buy Tag:* `buy_signal_01`\n'
-                                        '*Amount:* `1333.33333333`\n'
-                                        '*Open Rate:* `0.00001099`\n'
-                                        '*Current Rate:* `0.00001099`\n'
-                                        '*Total:* `(0.00100000 BTC)`')
+
+    leverage_text = f'*Leverage:* `{leverage}`\n' if leverage and leverage != 1.0 else ''
+    assert msg_mock.call_args[0][0] == (
+        f'\N{LARGE BLUE CIRCLE} *Binance:* {enter} ETH/BTC (#1)\n'
+        f'*Enter Tag:* `{enter_signal}`\n'
+        '*Amount:* `1333.33333333`\n'
+        f'{leverage_text}'
+        '*Open Rate:* `0.00001099`\n'
+        '*Current Rate:* `0.00001099`\n'
+        '*Total:* `(0.01465333 BTC)`'
+    )
 
 
-def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
+@pytest.mark.parametrize('direction,enter_signal,leverage', [
+    ('Long', 'long_signal_01', None),
+    ('Long', 'long_signal_01', 1.0),
+    ('Long', 'long_signal_01', 5.0),
+    ('Short', 'short_signal_01', 2.0),
+])
+def test_send_msg_sell_notification_no_fiat(
+        default_conf, mocker, direction, enter_signal, leverage) -> None:
     del default_conf['fiat_display_currency']
     telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
 
     telegram.send_msg({
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'trade_id': 1,
         'exchange': 'Binance',
         'pair': 'KEY/ETH',
         'gain': 'loss',
+        'leverage': leverage,
+        'direction': direction,
         'limit': 3.201e-05,
         'amount': 1333.3333333333335,
         'order_type': 'limit',
@@ -1574,29 +2219,36 @@ def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
         'profit_ratio': -0.57405275,
         'stake_currency': 'ETH',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.STOP_LOSS.value,
+        'enter_tag': enter_signal,
+        'exit_reason': ExitType.STOP_LOSS.value,
         'open_date': arrow.utcnow().shift(hours=-2, minutes=-35, seconds=-3),
         'close_date': arrow.utcnow(),
     })
-    assert msg_mock.call_args[0][0] == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH (#1)\n'
-                                        '*Profit:* `-57.41%`\n'
-                                        '*Sell Reason:* `stop_loss`\n'
-                                        '*Duration:* `2:35:03 (155.1 min)`\n'
-                                        '*Amount:* `1333.33333333`\n'
-                                        '*Open Rate:* `0.00007500`\n'
-                                        '*Current Rate:* `0.00003201`\n'
-                                        '*Close Rate:* `0.00003201`'
-                                        )
+
+    leverage_text = f'*Leverage:* `{leverage}`\n' if leverage and leverage != 1.0 else ''
+    assert msg_mock.call_args[0][0] == (
+        '\N{WARNING SIGN} *Binance:* Exiting KEY/ETH (#1)\n'
+        '*Unrealized Profit:* `-57.41%`\n'
+        f'*Enter Tag:* `{enter_signal}`\n'
+        '*Exit Reason:* `stop_loss`\n'
+        '*Duration:* `2:35:03 (155.1 min)`\n'
+        f'*Direction:* `{direction}`\n'
+        f'{leverage_text}'
+        '*Amount:* `1333.33333333`\n'
+        '*Open Rate:* `0.00007500`\n'
+        '*Current Rate:* `0.00003201`\n'
+        '*Close Rate:* `0.00003201`'
+    )
 
 
 @pytest.mark.parametrize('msg,expected', [
-    ({'profit_percent': 20.1, 'sell_reason': 'roi'}, "\N{ROCKET}"),
-    ({'profit_percent': 5.1, 'sell_reason': 'roi'}, "\N{ROCKET}"),
-    ({'profit_percent': 2.56, 'sell_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
-    ({'profit_percent': 1.0, 'sell_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
-    ({'profit_percent': 0.0, 'sell_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
-    ({'profit_percent': -5.0, 'sell_reason': 'stop_loss'}, "\N{WARNING SIGN}"),
-    ({'profit_percent': -2.0, 'sell_reason': 'sell_signal'}, "\N{CROSS MARK}"),
+    ({'profit_percent': 20.1, 'exit_reason': 'roi'}, "\N{ROCKET}"),
+    ({'profit_percent': 5.1, 'exit_reason': 'roi'}, "\N{ROCKET}"),
+    ({'profit_percent': 2.56, 'exit_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
+    ({'profit_percent': 1.0, 'exit_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
+    ({'profit_percent': 0.0, 'exit_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
+    ({'profit_percent': -5.0, 'exit_reason': 'stop_loss'}, "\N{WARNING SIGN}"),
+    ({'profit_percent': -2.0, 'exit_reason': 'sell_signal'}, "\N{CROSS MARK}"),
 ])
 def test__sell_emoji(default_conf, mocker, msg, expected):
     del default_conf['fiat_display_currency']
diff --git a/tests/rpc/test_rpc_webhook.py b/tests/rpc/test_rpc_webhook.py
index 04e63a3be..db357f80f 100644
--- a/tests/rpc/test_rpc_webhook.py
+++ b/tests/rpc/test_rpc_webhook.py
@@ -5,7 +5,7 @@ from unittest.mock import MagicMock
 import pytest
 from requests import RequestException
 
-from freqtrade.enums import RPCMessageType, SellType
+from freqtrade.enums import ExitType, RPCMessageType
 from freqtrade.rpc import RPC
 from freqtrade.rpc.webhook import Webhook
 from tests.conftest import get_patched_freqtradebot, log_has
@@ -15,32 +15,38 @@ def get_webhook_dict() -> dict:
     return {
         "enabled": True,
         "url": "https://maker.ifttt.com/trigger/freqtrade_test/with/key/c764udvJ5jfSlswVRukZZ2/",
-        "webhookbuy": {
+        "webhookentry": {
             "value1": "Buying {pair}",
             "value2": "limit {limit:8f}",
-            "value3": "{stake_amount:8f} {stake_currency}"
+            "value3": "{stake_amount:8f} {stake_currency}",
+            "value4": "leverage {leverage:.1f}",
+            "value5": "direction {direction}"
         },
-        "webhookbuycancel": {
+        "webhookentrycancel": {
             "value1": "Cancelling Open Buy Order for {pair}",
             "value2": "limit {limit:8f}",
-            "value3": "{stake_amount:8f} {stake_currency}"
+            "value3": "{stake_amount:8f} {stake_currency}",
+            "value4": "leverage {leverage:.1f}",
+            "value5": "direction {direction}"
         },
-        "webhookbuyfill": {
+        "webhookentryfill": {
             "value1": "Buy Order for {pair} filled",
             "value2": "at {open_rate:8f}",
-            "value3": "{stake_amount:8f} {stake_currency}"
+            "value3": "{stake_amount:8f} {stake_currency}",
+            "value4": "leverage {leverage:.1f}",
+            "value5": "direction {direction}"
         },
-        "webhooksell": {
+        "webhookexit": {
             "value1": "Selling {pair}",
             "value2": "limit {limit:8f}",
             "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
         },
-        "webhooksellcancel": {
+        "webhookexitcancel": {
             "value1": "Cancelling Open Sell Order for {pair}",
             "value2": "limit {limit:8f}",
             "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
         },
-        "webhooksellfill": {
+        "webhookexitfill": {
             "value1": "Sell Order for {pair} filled",
             "value2": "at {close_rate:8f}",
             "value3": ""
@@ -68,9 +74,11 @@ def test_send_msg_webhook(default_conf, mocker):
     msg_mock = MagicMock()
     mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
     msg = {
-        'type': RPCMessageType.BUY,
+        'type': RPCMessageType.ENTRY,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
+        'leverage': 1.0,
+        'direction': 'Long',
         'limit': 0.005,
         'stake_amount': 0.8,
         'stake_amount_fiat': 500,
@@ -80,18 +88,51 @@ def test_send_msg_webhook(default_conf, mocker):
     webhook.send_msg(msg=msg)
     assert msg_mock.call_count == 1
     assert (msg_mock.call_args[0][0]["value1"] ==
-            default_conf["webhook"]["webhookbuy"]["value1"].format(**msg))
+            default_conf["webhook"]["webhookentry"]["value1"].format(**msg))
     assert (msg_mock.call_args[0][0]["value2"] ==
-            default_conf["webhook"]["webhookbuy"]["value2"].format(**msg))
+            default_conf["webhook"]["webhookentry"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
-            default_conf["webhook"]["webhookbuy"]["value3"].format(**msg))
+            default_conf["webhook"]["webhookentry"]["value3"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value4"] ==
+            default_conf["webhook"]["webhookentry"]["value4"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value5"] ==
+            default_conf["webhook"]["webhookentry"]["value5"].format(**msg))
+    # Test short
+    msg_mock.reset_mock()
+
+    msg = {
+        'type': RPCMessageType.ENTRY,
+        'exchange': 'Binance',
+        'pair': 'ETH/BTC',
+        'leverage': 2.0,
+        'direction': 'Short',
+        'limit': 0.005,
+        'stake_amount': 0.8,
+        'stake_amount_fiat': 500,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'EUR'
+    }
+    webhook.send_msg(msg=msg)
+    assert msg_mock.call_count == 1
+    assert (msg_mock.call_args[0][0]["value1"] ==
+            default_conf["webhook"]["webhookentry"]["value1"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value2"] ==
+            default_conf["webhook"]["webhookentry"]["value2"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value3"] ==
+            default_conf["webhook"]["webhookentry"]["value3"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value4"] ==
+            default_conf["webhook"]["webhookentry"]["value4"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value5"] ==
+            default_conf["webhook"]["webhookentry"]["value5"].format(**msg))
     # Test buy cancel
     msg_mock.reset_mock()
 
     msg = {
-        'type': RPCMessageType.BUY_CANCEL,
+        'type': RPCMessageType.ENTRY_CANCEL,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
+        'leverage': 1.0,
+        'direction': 'Long',
         'limit': 0.005,
         'stake_amount': 0.8,
         'stake_amount_fiat': 500,
@@ -101,18 +142,47 @@ def test_send_msg_webhook(default_conf, mocker):
     webhook.send_msg(msg=msg)
     assert msg_mock.call_count == 1
     assert (msg_mock.call_args[0][0]["value1"] ==
-            default_conf["webhook"]["webhookbuycancel"]["value1"].format(**msg))
+            default_conf["webhook"]["webhookentrycancel"]["value1"].format(**msg))
     assert (msg_mock.call_args[0][0]["value2"] ==
-            default_conf["webhook"]["webhookbuycancel"]["value2"].format(**msg))
+            default_conf["webhook"]["webhookentrycancel"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
-            default_conf["webhook"]["webhookbuycancel"]["value3"].format(**msg))
+            default_conf["webhook"]["webhookentrycancel"]["value3"].format(**msg))
+    # Test short cancel
+    msg_mock.reset_mock()
+
+    msg = {
+        'type': RPCMessageType.ENTRY_CANCEL,
+        'exchange': 'Binance',
+        'pair': 'ETH/BTC',
+        'leverage': 2.0,
+        'direction': 'Short',
+        'limit': 0.005,
+        'stake_amount': 0.8,
+        'stake_amount_fiat': 500,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'EUR'
+    }
+    webhook.send_msg(msg=msg)
+    assert msg_mock.call_count == 1
+    assert (msg_mock.call_args[0][0]["value1"] ==
+            default_conf["webhook"]["webhookentrycancel"]["value1"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value2"] ==
+            default_conf["webhook"]["webhookentrycancel"]["value2"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value3"] ==
+            default_conf["webhook"]["webhookentrycancel"]["value3"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value4"] ==
+            default_conf["webhook"]["webhookentrycancel"]["value4"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value5"] ==
+            default_conf["webhook"]["webhookentrycancel"]["value5"].format(**msg))
     # Test buy fill
     msg_mock.reset_mock()
 
     msg = {
-        'type': RPCMessageType.BUY_FILL,
+        'type': RPCMessageType.ENTRY_FILL,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
+        'leverage': 1.0,
+        'direction': 'Long',
         'open_rate': 0.005,
         'stake_amount': 0.8,
         'stake_amount_fiat': 500,
@@ -122,15 +192,47 @@ def test_send_msg_webhook(default_conf, mocker):
     webhook.send_msg(msg=msg)
     assert msg_mock.call_count == 1
     assert (msg_mock.call_args[0][0]["value1"] ==
-            default_conf["webhook"]["webhookbuyfill"]["value1"].format(**msg))
+            default_conf["webhook"]["webhookentryfill"]["value1"].format(**msg))
     assert (msg_mock.call_args[0][0]["value2"] ==
-            default_conf["webhook"]["webhookbuyfill"]["value2"].format(**msg))
+            default_conf["webhook"]["webhookentryfill"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
-            default_conf["webhook"]["webhookbuyfill"]["value3"].format(**msg))
+            default_conf["webhook"]["webhookentryfill"]["value3"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value4"] ==
+            default_conf["webhook"]["webhookentrycancel"]["value4"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value5"] ==
+            default_conf["webhook"]["webhookentrycancel"]["value5"].format(**msg))
+    # Test short fill
+    msg_mock.reset_mock()
+
+    msg = {
+        'type': RPCMessageType.ENTRY_FILL,
+        'exchange': 'Binance',
+        'pair': 'ETH/BTC',
+        'leverage': 2.0,
+        'direction': 'Short',
+        'open_rate': 0.005,
+        'stake_amount': 0.8,
+        'stake_amount_fiat': 500,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'EUR'
+    }
+    webhook.send_msg(msg=msg)
+    assert msg_mock.call_count == 1
+    assert (msg_mock.call_args[0][0]["value1"] ==
+            default_conf["webhook"]["webhookentryfill"]["value1"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value2"] ==
+            default_conf["webhook"]["webhookentryfill"]["value2"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value3"] ==
+            default_conf["webhook"]["webhookentryfill"]["value3"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value4"] ==
+            default_conf["webhook"]["webhookentrycancel"]["value4"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value5"] ==
+            default_conf["webhook"]["webhookentrycancel"]["value5"].format(**msg))
     # Test sell
     msg_mock.reset_mock()
+
     msg = {
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': "profit",
@@ -142,20 +244,20 @@ def test_send_msg_webhook(default_conf, mocker):
         'profit_amount': 0.001,
         'profit_ratio': 0.20,
         'stake_currency': 'BTC',
-        'sell_reason': SellType.STOP_LOSS.value
+        'sell_reason': ExitType.STOP_LOSS.value
     }
     webhook.send_msg(msg=msg)
     assert msg_mock.call_count == 1
     assert (msg_mock.call_args[0][0]["value1"] ==
-            default_conf["webhook"]["webhooksell"]["value1"].format(**msg))
+            default_conf["webhook"]["webhookexit"]["value1"].format(**msg))
     assert (msg_mock.call_args[0][0]["value2"] ==
-            default_conf["webhook"]["webhooksell"]["value2"].format(**msg))
+            default_conf["webhook"]["webhookexit"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
-            default_conf["webhook"]["webhooksell"]["value3"].format(**msg))
+            default_conf["webhook"]["webhookexit"]["value3"].format(**msg))
     # Test sell cancel
     msg_mock.reset_mock()
     msg = {
-        'type': RPCMessageType.SELL_CANCEL,
+        'type': RPCMessageType.EXIT_CANCEL,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': "profit",
@@ -167,20 +269,20 @@ def test_send_msg_webhook(default_conf, mocker):
         'profit_amount': 0.001,
         'profit_ratio': 0.20,
         'stake_currency': 'BTC',
-        'sell_reason': SellType.STOP_LOSS.value
+        'sell_reason': ExitType.STOP_LOSS.value
     }
     webhook.send_msg(msg=msg)
     assert msg_mock.call_count == 1
     assert (msg_mock.call_args[0][0]["value1"] ==
-            default_conf["webhook"]["webhooksellcancel"]["value1"].format(**msg))
+            default_conf["webhook"]["webhookexitcancel"]["value1"].format(**msg))
     assert (msg_mock.call_args[0][0]["value2"] ==
-            default_conf["webhook"]["webhooksellcancel"]["value2"].format(**msg))
+            default_conf["webhook"]["webhookexitcancel"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
-            default_conf["webhook"]["webhooksellcancel"]["value3"].format(**msg))
+            default_conf["webhook"]["webhookexitcancel"]["value3"].format(**msg))
     # Test Sell fill
     msg_mock.reset_mock()
     msg = {
-        'type': RPCMessageType.SELL_FILL,
+        'type': RPCMessageType.EXIT_FILL,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'gain': "profit",
@@ -192,16 +294,16 @@ def test_send_msg_webhook(default_conf, mocker):
         'profit_amount': 0.001,
         'profit_ratio': 0.20,
         'stake_currency': 'BTC',
-        'sell_reason': SellType.STOP_LOSS.value
+        'sell_reason': ExitType.STOP_LOSS.value
     }
     webhook.send_msg(msg=msg)
     assert msg_mock.call_count == 1
     assert (msg_mock.call_args[0][0]["value1"] ==
-            default_conf["webhook"]["webhooksellfill"]["value1"].format(**msg))
+            default_conf["webhook"]["webhookexitfill"]["value1"].format(**msg))
     assert (msg_mock.call_args[0][0]["value2"] ==
-            default_conf["webhook"]["webhooksellfill"]["value2"].format(**msg))
+            default_conf["webhook"]["webhookexitfill"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
-            default_conf["webhook"]["webhooksellfill"]["value3"].format(**msg))
+            default_conf["webhook"]["webhookexitfill"]["value3"].format(**msg))
 
     for msgtype in [RPCMessageType.STATUS,
                     RPCMessageType.WARNING,
@@ -225,20 +327,20 @@ def test_send_msg_webhook(default_conf, mocker):
 
 def test_exception_send_msg(default_conf, mocker, caplog):
     default_conf["webhook"] = get_webhook_dict()
-    del default_conf["webhook"]["webhookbuy"]
+    del default_conf["webhook"]["webhookentry"]
 
     webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf)
-    webhook.send_msg({'type': RPCMessageType.BUY})
-    assert log_has(f"Message type '{RPCMessageType.BUY}' not configured for webhooks",
+    webhook.send_msg({'type': RPCMessageType.ENTRY})
+    assert log_has(f"Message type '{RPCMessageType.ENTRY}' not configured for webhooks",
                    caplog)
 
     default_conf["webhook"] = get_webhook_dict()
-    default_conf["webhook"]["webhookbuy"]["value1"] = "{DEADBEEF:8f}"
+    default_conf["webhook"]["webhookentry"]["value1"] = "{DEADBEEF:8f}"
     msg_mock = MagicMock()
     mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
     webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf)
     msg = {
-        'type': RPCMessageType.BUY,
+        'type': RPCMessageType.ENTRY,
         'exchange': 'Binance',
         'pair': 'ETH/BTC',
         'limit': 0.005,
@@ -292,3 +394,15 @@ def test__send_msg_with_json_format(default_conf, mocker, caplog):
     webhook._send_msg(msg)
 
     assert post.call_args[1] == {'json': msg}
+
+
+def test__send_msg_with_raw_format(default_conf, mocker, caplog):
+    default_conf["webhook"] = get_webhook_dict()
+    default_conf["webhook"]["format"] = "raw"
+    webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf)
+    msg = {'data': 'Hello'}
+    post = MagicMock()
+    mocker.patch("freqtrade.rpc.webhook.post", post)
+    webhook._send_msg(msg)
+
+    assert post.call_args[1] == {'data': msg['data'], 'headers': {'Content-Type': 'text/plain'}}
diff --git a/tests/strategy/strats/broken_strats/broken_futures_strategies.py b/tests/strategy/strats/broken_strats/broken_futures_strategies.py
new file mode 100644
index 000000000..7e6955d37
--- /dev/null
+++ b/tests/strategy/strats/broken_strats/broken_futures_strategies.py
@@ -0,0 +1,49 @@
+"""
+The strategies here are minimal strategies designed to fail loading in certain conditions.
+They are not operational, and don't aim to be.
+"""
+
+from datetime import datetime
+
+from pandas import DataFrame
+
+from freqtrade.strategy.interface import IStrategy
+
+
+class TestStrategyNoImplements(IStrategy):
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        return super().populate_indicators(dataframe, metadata)
+
+
+class TestStrategyNoImplementSell(TestStrategyNoImplements):
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        return super().populate_entry_trend(dataframe, metadata)
+
+
+class TestStrategyImplementCustomSell(TestStrategyNoImplementSell):
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        return super().populate_exit_trend(dataframe, metadata)
+
+    def custom_sell(self, pair: str, trade, current_time: datetime,
+                    current_rate: float, current_profit: float,
+                    **kwargs):
+        return False
+
+
+class TestStrategyImplementBuyTimeout(TestStrategyNoImplementSell):
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        return super().populate_exit_trend(dataframe, metadata)
+
+    def check_buy_timeout(self, pair: str, trade, order: dict,
+                          current_time: datetime, **kwargs) -> bool:
+        return False
+
+
+class TestStrategyImplementSellTimeout(TestStrategyNoImplementSell):
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        return super().populate_exit_trend(dataframe, metadata)
+
+    def check_sell_timeout(self, pair: str, trade, order: dict,
+                           current_time: datetime, **kwargs) -> bool:
+        return False
diff --git a/tests/strategy/strats/hyperoptable_strategy.py b/tests/strategy/strats/hyperoptable_strategy.py
index 88bdd078e..f4dcf1a05 100644
--- a/tests/strategy/strats/hyperoptable_strategy.py
+++ b/tests/strategy/strats/hyperoptable_strategy.py
@@ -1,14 +1,13 @@
 # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
 
-import talib.abstract as ta
 from pandas import DataFrame
+from strategy_test_v2 import StrategyTestV2
 
 import freqtrade.vendor.qtpylib.indicators as qtpylib
-from freqtrade.strategy import (BooleanParameter, DecimalParameter, IntParameter, IStrategy,
-                                RealParameter)
+from freqtrade.strategy import BooleanParameter, DecimalParameter, IntParameter, RealParameter
 
 
-class HyperoptableStrategy(IStrategy):
+class HyperoptableStrategy(StrategyTestV2):
     """
     Default Strategy provided by freqtrade bot.
     Please do not modify this strategy, it's  intended for internal use only.
@@ -16,38 +15,6 @@ class HyperoptableStrategy(IStrategy):
     or strategy repository https://github.com/freqtrade/freqtrade-strategies
     for samples and inspiration.
     """
-    INTERFACE_VERSION = 2
-
-    # Minimal ROI designed for the strategy
-    minimal_roi = {
-        "40": 0.0,
-        "30": 0.01,
-        "20": 0.02,
-        "0": 0.04
-    }
-
-    # Optimal stoploss designed for the strategy
-    stoploss = -0.10
-
-    # Optimal ticker interval for the strategy
-    timeframe = '5m'
-
-    # Optional order type mapping
-    order_types = {
-        'buy': 'limit',
-        'sell': 'limit',
-        'stoploss': 'limit',
-        'stoploss_on_exchange': False
-    }
-
-    # Number of candles the strategy requires before producing valid signals
-    startup_candle_count: int = 20
-
-    # Optional time in force for orders
-    order_time_in_force = {
-        'buy': 'gtc',
-        'sell': 'gtc',
-    }
 
     buy_params = {
         'buy_rsi': 35,
@@ -91,55 +58,6 @@ class HyperoptableStrategy(IStrategy):
         """
         return []
 
-    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        """
-        Adds several different TA indicators to the given DataFrame
-
-        Performance Note: For the best performance be frugal on the number of indicators
-        you are using. Let uncomment only the indicator you are using in your strategies
-        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
-        :param dataframe: Dataframe with data from the exchange
-        :param metadata: Additional information, like the currently traded pair
-        :return: a Dataframe with all mandatory indicators for the strategies
-        """
-
-        # Momentum Indicator
-        # ------------------------------------
-
-        # ADX
-        dataframe['adx'] = ta.ADX(dataframe)
-
-        # MACD
-        macd = ta.MACD(dataframe)
-        dataframe['macd'] = macd['macd']
-        dataframe['macdsignal'] = macd['macdsignal']
-        dataframe['macdhist'] = macd['macdhist']
-
-        # Minus Directional Indicator / Movement
-        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
-
-        # Plus Directional Indicator / Movement
-        dataframe['plus_di'] = ta.PLUS_DI(dataframe)
-
-        # RSI
-        dataframe['rsi'] = ta.RSI(dataframe)
-
-        # Stoch fast
-        stoch_fast = ta.STOCHF(dataframe)
-        dataframe['fastd'] = stoch_fast['fastd']
-        dataframe['fastk'] = stoch_fast['fastk']
-
-        # Bollinger bands
-        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
-        dataframe['bb_lowerband'] = bollinger['lower']
-        dataframe['bb_middleband'] = bollinger['mid']
-        dataframe['bb_upperband'] = bollinger['upper']
-
-        # EMA - Exponential Moving Average
-        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
-
-        return dataframe
-
     def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
@@ -167,7 +85,7 @@ class HyperoptableStrategy(IStrategy):
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
         :param metadata: Additional information, like the currently traded pair
-        :return: DataFrame with buy column
+        :return: DataFrame with sell column
         """
         dataframe.loc[
             (
diff --git a/tests/strategy/strats/informative_decorator_strategy.py b/tests/strategy/strats/informative_decorator_strategy.py
index a32ad79e8..8c1466de9 100644
--- a/tests/strategy/strats/informative_decorator_strategy.py
+++ b/tests/strategy/strats/informative_decorator_strategy.py
@@ -2,8 +2,7 @@
 
 from pandas import DataFrame
 
-from freqtrade.strategy import informative, merge_informative_pair
-from freqtrade.strategy.interface import IStrategy
+from freqtrade.strategy import IStrategy, informative, merge_informative_pair
 
 
 class InformativeDecoratorTest(IStrategy):
@@ -20,7 +19,12 @@ class InformativeDecoratorTest(IStrategy):
     startup_candle_count: int = 20
 
     def informative_pairs(self):
-        return [('BTC/USDT', '5m')]
+        # Intentionally return 2 tuples, must be converted to 3 in compatibility code
+        return [
+            ('NEO/USDT', '5m'),
+            ('NEO/USDT', '15m', ''),
+            ('NEO/USDT', '2h', 'futures'),
+            ]
 
     def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['buy'] = 0
@@ -38,19 +42,19 @@ class InformativeDecoratorTest(IStrategy):
         return dataframe
 
     # Simple informative test.
-    @informative('1h', 'BTC/{stake}')
-    def populate_indicators_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    @informative('1h', 'NEO/{stake}')
+    def populate_indicators_neo_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['rsi'] = 14
         return dataframe
 
     # Quote currency different from stake currency test.
-    @informative('1h', 'ETH/BTC')
+    @informative('1h', 'ETH/BTC', candle_type='spot')
     def populate_indicators_eth_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['rsi'] = 14
         return dataframe
 
     # Formatting test.
-    @informative('30m', 'BTC/{stake}', '{column}_{BASE}_{QUOTE}_{base}_{quote}_{asset}_{timeframe}')
+    @informative('30m', 'NEO/{stake}', '{column}_{BASE}_{QUOTE}_{base}_{quote}_{asset}_{timeframe}')
     def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         dataframe['rsi'] = 14
         return dataframe
@@ -68,7 +72,7 @@ class InformativeDecoratorTest(IStrategy):
         dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h']
 
         # Mixing manual informative pairs with decorators.
-        informative = self.dp.get_pair_dataframe('BTC/USDT', '5m')
+        informative = self.dp.get_pair_dataframe('NEO/USDT', '5m', '')
         informative['rsi'] = 14
         dataframe = merge_informative_pair(dataframe, informative, self.timeframe, '5m', ffill=True)
 
diff --git a/tests/strategy/strats/legacy_strategy_v1.py b/tests/strategy/strats/legacy_strategy_v1.py
index ebfce632b..bad2aa40d 100644
--- a/tests/strategy/strats/legacy_strategy_v1.py
+++ b/tests/strategy/strats/legacy_strategy_v1.py
@@ -4,7 +4,7 @@
 import talib.abstract as ta
 from pandas import DataFrame
 
-from freqtrade.strategy.interface import IStrategy
+from freqtrade.strategy import IStrategy
 
 
 # --------------------------------
@@ -31,9 +31,7 @@ class TestStrategyLegacyV1(IStrategy):
     # This attribute will be overridden if the config file contains "stoploss"
     stoploss = -0.10
 
-    # Optimal timeframe for the strategy
-    # Keep the legacy value here to test compatibility
-    ticker_interval = '5m'
+    timeframe = '5m'
 
     def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
         """
diff --git a/tests/strategy/strats/strategy_test_v2.py b/tests/strategy/strats/strategy_test_v2.py
index 53e39526f..8996b227a 100644
--- a/tests/strategy/strats/strategy_test_v2.py
+++ b/tests/strategy/strats/strategy_test_v2.py
@@ -1,10 +1,13 @@
 # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
 
+from datetime import datetime
+
 import talib.abstract as ta
 from pandas import DataFrame
 
 import freqtrade.vendor.qtpylib.indicators as qtpylib
-from freqtrade.strategy.interface import IStrategy
+from freqtrade.persistence import Trade
+from freqtrade.strategy import IStrategy
 
 
 class StrategyTestV2(IStrategy):
@@ -33,8 +36,8 @@ class StrategyTestV2(IStrategy):
 
     # Optional order type mapping
     order_types = {
-        'buy': 'limit',
-        'sell': 'limit',
+        'entry': 'limit',
+        'exit': 'limit',
         'stoploss': 'limit',
         'stoploss_on_exchange': False
     }
@@ -44,9 +47,14 @@ class StrategyTestV2(IStrategy):
 
     # Optional time in force for orders
     order_time_in_force = {
-        'buy': 'gtc',
-        'sell': 'gtc',
+        'entry': 'gtc',
+        'exit': 'gtc',
     }
+    # Test legacy use_sell_signal definition
+    use_sell_signal = False
+
+    # By default this strategy does not use Position Adjustments
+    position_adjustment_enable = False
 
     def informative_pairs(self):
         """
@@ -154,3 +162,12 @@ class StrategyTestV2(IStrategy):
             ),
             'sell'] = 1
         return dataframe
+
+    def adjust_trade_position(self, trade: Trade, current_time: datetime, current_rate: float,
+                              current_profit: float, min_stake: float, max_stake: float, **kwargs):
+
+        if current_profit < -0.0075:
+            orders = trade.select_filled_orders('buy')
+            return round(orders[0].cost, 0)
+
+        return None
diff --git a/tests/strategy/strats/strategy_test_v3.py b/tests/strategy/strats/strategy_test_v3.py
new file mode 100644
index 000000000..372e29412
--- /dev/null
+++ b/tests/strategy/strats/strategy_test_v3.py
@@ -0,0 +1,193 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+from datetime import datetime
+
+import talib.abstract as ta
+from pandas import DataFrame
+
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+from freqtrade.persistence import Trade
+from freqtrade.strategy import (BooleanParameter, DecimalParameter, IntParameter, IStrategy,
+                                RealParameter)
+
+
+class StrategyTestV3(IStrategy):
+    """
+    Strategy used by tests freqtrade bot.
+    Please do not modify this strategy, it's  intended for internal use only.
+    Please look at the SampleStrategy in the user_data/strategy directory
+    or strategy repository https://github.com/freqtrade/freqtrade-strategies
+    for samples and inspiration.
+    """
+    INTERFACE_VERSION = 3
+
+    # Minimal ROI designed for the strategy
+    minimal_roi = {
+        "40": 0.0,
+        "30": 0.01,
+        "20": 0.02,
+        "0": 0.04
+    }
+
+    # Optimal stoploss designed for the strategy
+    stoploss = -0.10
+
+    # Optimal timeframe for the strategy
+    timeframe = '5m'
+
+    # Optional order type mapping
+    order_types = {
+        'entry': 'limit',
+        'exit': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': False
+    }
+
+    # Number of candles the strategy requires before producing valid signals
+    startup_candle_count: int = 20
+
+    # Optional time in force for orders
+    order_time_in_force = {
+        'entry': 'gtc',
+        'exit': 'gtc',
+    }
+
+    buy_params = {
+        'buy_rsi': 35,
+        # Intentionally not specified, so "default" is tested
+        # 'buy_plusdi': 0.4
+    }
+
+    sell_params = {
+        'sell_rsi': 74,
+        'sell_minusdi': 0.4
+    }
+
+    buy_rsi = IntParameter([0, 50], default=30, space='buy')
+    buy_plusdi = RealParameter(low=0, high=1, default=0.5, space='buy')
+    sell_rsi = IntParameter(low=50, high=100, default=70, space='sell')
+    sell_minusdi = DecimalParameter(low=0, high=1, default=0.5001, decimals=3, space='sell',
+                                    load=False)
+    protection_enabled = BooleanParameter(default=True)
+    protection_cooldown_lookback = IntParameter([0, 50], default=30)
+
+    # TODO: Can this work with protection tests? (replace HyperoptableStrategy implicitly ... )
+    # @property
+    # def protections(self):
+    #     prot = []
+    #     if self.protection_enabled.value:
+    #         prot.append({
+    #             "method": "CooldownPeriod",
+    #             "stop_duration_candles": self.protection_cooldown_lookback.value
+    #         })
+    #     return prot
+
+    def informative_pairs(self):
+
+        return []
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        # Momentum Indicator
+        # ------------------------------------
+
+        # ADX
+        dataframe['adx'] = ta.ADX(dataframe)
+
+        # MACD
+        macd = ta.MACD(dataframe)
+        dataframe['macd'] = macd['macd']
+        dataframe['macdsignal'] = macd['macdsignal']
+        dataframe['macdhist'] = macd['macdhist']
+
+        # Minus Directional Indicator / Movement
+        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
+
+        # Plus Directional Indicator / Movement
+        dataframe['plus_di'] = ta.PLUS_DI(dataframe)
+
+        # RSI
+        dataframe['rsi'] = ta.RSI(dataframe)
+
+        # Stoch fast
+        stoch_fast = ta.STOCHF(dataframe)
+        dataframe['fastd'] = stoch_fast['fastd']
+        dataframe['fastk'] = stoch_fast['fastk']
+
+        # Bollinger bands
+        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
+        dataframe['bb_lowerband'] = bollinger['lower']
+        dataframe['bb_middleband'] = bollinger['mid']
+        dataframe['bb_upperband'] = bollinger['upper']
+
+        # EMA - Exponential Moving Average
+        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
+
+        return dataframe
+
+    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        dataframe.loc[
+            (
+                (dataframe['rsi'] < self.buy_rsi.value) &
+                (dataframe['fastd'] < 35) &
+                (dataframe['adx'] > 30) &
+                (dataframe['plus_di'] > self.buy_plusdi.value)
+            ) |
+            (
+                (dataframe['adx'] > 65) &
+                (dataframe['plus_di'] > self.buy_plusdi.value)
+            ),
+            'enter_long'] = 1
+        dataframe.loc[
+            (
+                qtpylib.crossed_below(dataframe['rsi'], self.sell_rsi.value)
+            ),
+            'enter_short'] = 1
+
+        return dataframe
+
+    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe.loc[
+            (
+                (
+                    (qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) |
+                    (qtpylib.crossed_above(dataframe['fastd'], 70))
+                ) &
+                (dataframe['adx'] > 10) &
+                (dataframe['minus_di'] > 0)
+            ) |
+            (
+                (dataframe['adx'] > 70) &
+                (dataframe['minus_di'] > self.sell_minusdi.value)
+            ),
+            'exit_long'] = 1
+
+        dataframe.loc[
+            (
+                qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)
+            ),
+            'exit_short'] = 1
+
+        return dataframe
+
+    def leverage(self, pair: str, current_time: datetime, current_rate: float,
+                 proposed_leverage: float, max_leverage: float, side: str,
+                 **kwargs) -> float:
+        # Return 3.0 in all cases.
+        # Bot-logic must make sure it's an allowed leverage and eventually adjust accordingly.
+
+        return 3.0
+
+    def adjust_trade_position(self, trade: Trade, current_time: datetime, current_rate: float,
+                              current_profit: float, min_stake: float, max_stake: float, **kwargs):
+
+        if current_profit < -0.0075:
+            orders = trade.select_filled_orders(trade.entry_side)
+            return round(orders[0].cost, 0)
+
+        return None
+
+
+class StrategyTestV3Futures(StrategyTestV3):
+    can_short = True
diff --git a/tests/strategy/test_default_strategy.py b/tests/strategy/test_default_strategy.py
index 6426ebe5f..5cb8fce16 100644
--- a/tests/strategy/test_default_strategy.py
+++ b/tests/strategy/test_default_strategy.py
@@ -1,23 +1,28 @@
 from datetime import datetime
 
+import pytest
 from pandas import DataFrame
 
 from freqtrade.persistence.models import Trade
 
-from .strats.strategy_test_v2 import StrategyTestV2
+from .strats.strategy_test_v3 import StrategyTestV3
 
 
-def test_strategy_test_v2_structure():
-    assert hasattr(StrategyTestV2, 'minimal_roi')
-    assert hasattr(StrategyTestV2, 'stoploss')
-    assert hasattr(StrategyTestV2, 'timeframe')
-    assert hasattr(StrategyTestV2, 'populate_indicators')
-    assert hasattr(StrategyTestV2, 'populate_buy_trend')
-    assert hasattr(StrategyTestV2, 'populate_sell_trend')
+def test_strategy_test_v3_structure():
+    assert hasattr(StrategyTestV3, 'minimal_roi')
+    assert hasattr(StrategyTestV3, 'stoploss')
+    assert hasattr(StrategyTestV3, 'timeframe')
+    assert hasattr(StrategyTestV3, 'populate_indicators')
+    assert hasattr(StrategyTestV3, 'populate_entry_trend')
+    assert hasattr(StrategyTestV3, 'populate_exit_trend')
 
 
-def test_strategy_test_v2(result, fee):
-    strategy = StrategyTestV2({})
+@pytest.mark.parametrize('is_short,side', [
+    (True, 'short'),
+    (False, 'long'),
+])
+def test_strategy_test_v3(result, fee, is_short, side):
+    strategy = StrategyTestV3({})
 
     metadata = {'pair': 'ETH/BTC'}
     assert type(strategy.minimal_roi) is dict
@@ -32,15 +37,19 @@ def test_strategy_test_v2(result, fee):
         open_rate=19_000,
         amount=0.1,
         pair='ETH/BTC',
-        fee_open=fee.return_value
+        fee_open=fee.return_value,
+        is_short=is_short
     )
 
     assert strategy.confirm_trade_entry(pair='ETH/BTC', order_type='limit', amount=0.1,
                                         rate=20000, time_in_force='gtc',
-                                        current_time=datetime.utcnow()) is True
+                                        current_time=datetime.utcnow(),
+                                        side=side, entry_tag=None) is True
     assert strategy.confirm_trade_exit(pair='ETH/BTC', trade=trade, order_type='limit', amount=0.1,
-                                       rate=20000, time_in_force='gtc', sell_reason='roi',
-                                       current_time=datetime.utcnow()) is True
+                                       rate=20000, time_in_force='gtc', exit_reason='roi',
+                                       sell_reason='roi',
+                                       current_time=datetime.utcnow(),
+                                       side=side) is True
 
     assert strategy.custom_stoploss(pair='ETH/BTC', trade=trade, current_time=datetime.now(),
                                     current_rate=20_000, current_profit=0.05) == strategy.stoploss
diff --git a/tests/strategy/test_interface.py b/tests/strategy/test_interface.py
index dcb9e3e64..a86d69135 100644
--- a/tests/strategy/test_interface.py
+++ b/tests/strategy/test_interface.py
@@ -11,47 +11,94 @@ from pandas import DataFrame
 from freqtrade.configuration import TimeRange
 from freqtrade.data.dataprovider import DataProvider
 from freqtrade.data.history import load_data
-from freqtrade.enums import SellType
+from freqtrade.enums import ExitCheckTuple, ExitType, SignalDirection
 from freqtrade.exceptions import OperationalException, StrategyError
 from freqtrade.optimize.space import SKDecimal
 from freqtrade.persistence import PairLocks, Trade
 from freqtrade.resolvers import StrategyResolver
 from freqtrade.strategy.hyper import (BaseParameter, BooleanParameter, CategoricalParameter,
                                       DecimalParameter, IntParameter, RealParameter)
-from freqtrade.strategy.interface import SellCheckTuple
 from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
-from tests.conftest import log_has, log_has_re
+from tests.conftest import CURRENT_TEST_STRATEGY, TRADE_SIDES, log_has, log_has_re
 
-from .strats.strategy_test_v2 import StrategyTestV2
+from .strats.strategy_test_v3 import StrategyTestV3
 
 
 # Avoid to reinit the same object again and again
-_STRATEGY = StrategyTestV2(config={})
+_STRATEGY = StrategyTestV3(config={})
 _STRATEGY.dp = DataProvider({}, None, None)
 
 
-def test_returns_latest_signal(mocker, default_conf, ohlcv_history):
+def test_returns_latest_signal(ohlcv_history):
     ohlcv_history.loc[1, 'date'] = arrow.utcnow()
     # Take a copy to correctly modify the call
     mocked_history = ohlcv_history.copy()
-    mocked_history['sell'] = 0
-    mocked_history['buy'] = 0
-    mocked_history.loc[1, 'sell'] = 1
+    mocked_history['enter_long'] = 0
+    mocked_history['exit_long'] = 0
+    mocked_history['enter_short'] = 0
+    mocked_history['exit_short'] = 0
+    # Set tags in lines that don't matter to test nan in the sell line
+    mocked_history.loc[0, 'enter_tag'] = 'wrong_line'
+    mocked_history.loc[0, 'exit_tag'] = 'wrong_line'
+    mocked_history.loc[1, 'exit_long'] = 1
 
-    assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (False, True, None)
-    mocked_history.loc[1, 'sell'] = 0
-    mocked_history.loc[1, 'buy'] = 1
+    assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None)
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (False, True, None)
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None)
+    mocked_history.loc[1, 'exit_long'] = 0
+    mocked_history.loc[1, 'enter_long'] = 1
 
-    assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (True, False, None)
-    mocked_history.loc[1, 'sell'] = 0
-    mocked_history.loc[1, 'buy'] = 0
+    assert _STRATEGY.get_entry_signal(
+        'ETH/BTC', '5m', mocked_history) == (SignalDirection.LONG, None)
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (True, False, None)
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None)
+    mocked_history.loc[1, 'exit_long'] = 0
+    mocked_history.loc[1, 'enter_long'] = 0
 
-    assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (False, False, None)
-    mocked_history.loc[1, 'sell'] = 0
-    mocked_history.loc[1, 'buy'] = 1
-    mocked_history.loc[1, 'buy_tag'] = 'buy_signal_01'
+    assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None)
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (False, False, None)
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None)
+    mocked_history.loc[1, 'exit_long'] = 0
+    mocked_history.loc[1, 'enter_long'] = 1
+    mocked_history.loc[1, 'enter_tag'] = 'buy_signal_01'
 
-    assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (True, False, 'buy_signal_01')
+    assert _STRATEGY.get_entry_signal(
+        'ETH/BTC', '5m', mocked_history) == (SignalDirection.LONG, 'buy_signal_01')
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (True, False, None)
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None)
+
+    mocked_history.loc[1, 'exit_long'] = 0
+    mocked_history.loc[1, 'enter_long'] = 0
+    mocked_history.loc[1, 'enter_short'] = 1
+    mocked_history.loc[1, 'exit_short'] = 0
+    mocked_history.loc[1, 'enter_tag'] = 'sell_signal_01'
+
+    # Don't provide short signal while in spot mode
+    assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None)
+
+    _STRATEGY.config['trading_mode'] = 'futures'
+    # Short signal get's ignored as can_short is not set.
+    assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None)
+
+    _STRATEGY.can_short = True
+
+    assert _STRATEGY.get_entry_signal(
+        'ETH/BTC', '5m', mocked_history) == (SignalDirection.SHORT, 'sell_signal_01')
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (False, False, None)
+    assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (True, False, None)
+
+    mocked_history.loc[1, 'enter_short'] = 0
+    mocked_history.loc[1, 'exit_short'] = 1
+    mocked_history.loc[1, 'exit_tag'] = 'sell_signal_02'
+    assert _STRATEGY.get_entry_signal(
+        'ETH/BTC', '5m', mocked_history) == (None, None)
+    assert _STRATEGY.get_exit_signal(
+        'ETH/BTC', '5m', mocked_history) == (False, False, 'sell_signal_02')
+    assert _STRATEGY.get_exit_signal(
+        'ETH/BTC', '5m', mocked_history, True) == (False, True, 'sell_signal_02')
+
+    _STRATEGY.can_short = False
+    _STRATEGY.config['trading_mode'] = 'spot'
 
 
 def test_analyze_pair_empty(default_conf, mocker, caplog, ohlcv_history):
@@ -67,18 +114,18 @@ def test_analyze_pair_empty(default_conf, mocker, caplog, ohlcv_history):
     assert log_has('Empty dataframe for pair ETH/BTC', caplog)
 
 
-def test_get_signal_empty(default_conf, mocker, caplog):
-    assert (False, False, None) == _STRATEGY.get_signal(
+def test_get_signal_empty(default_conf, caplog):
+    assert (None, None) == _STRATEGY.get_latest_candle(
         'foo', default_conf['timeframe'], DataFrame()
     )
     assert log_has('Empty candle (OHLCV) data for pair foo', caplog)
     caplog.clear()
 
-    assert (False, False, None) == _STRATEGY.get_signal('bar', default_conf['timeframe'], None)
+    assert (None, None) == _STRATEGY.get_latest_candle('bar', default_conf['timeframe'], None)
     assert log_has('Empty candle (OHLCV) data for pair bar', caplog)
     caplog.clear()
 
-    assert (False, False, None) == _STRATEGY.get_signal(
+    assert (None, None) == _STRATEGY.get_latest_candle(
         'baz',
         default_conf['timeframe'],
         DataFrame([])
@@ -86,7 +133,7 @@ def test_get_signal_empty(default_conf, mocker, caplog):
     assert log_has('Empty candle (OHLCV) data for pair baz', caplog)
 
 
-def test_get_signal_exception_valueerror(default_conf, mocker, caplog, ohlcv_history):
+def test_get_signal_exception_valueerror(mocker, caplog, ohlcv_history):
     caplog.set_level(logging.INFO)
     mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
     mocker.patch.object(
@@ -111,14 +158,14 @@ def test_get_signal_old_dataframe(default_conf, mocker, caplog, ohlcv_history):
     ohlcv_history.loc[1, 'date'] = arrow.utcnow().shift(minutes=-16)
     # Take a copy to correctly modify the call
     mocked_history = ohlcv_history.copy()
-    mocked_history['sell'] = 0
-    mocked_history['buy'] = 0
-    mocked_history.loc[1, 'buy'] = 1
+    mocked_history['exit_long'] = 0
+    mocked_history['enter_long'] = 0
+    mocked_history.loc[1, 'enter_long'] = 1
 
     caplog.set_level(logging.INFO)
     mocker.patch.object(_STRATEGY, 'assert_df')
 
-    assert (False, False, None) == _STRATEGY.get_signal(
+    assert (None, None) == _STRATEGY.get_latest_candle(
         'xyz',
         default_conf['timeframe'],
         mocked_history
@@ -134,13 +181,13 @@ def test_get_signal_no_sell_column(default_conf, mocker, caplog, ohlcv_history):
     mocked_history = ohlcv_history.copy()
     # Intentionally don't set sell column
     # mocked_history['sell'] = 0
-    mocked_history['buy'] = 0
-    mocked_history.loc[1, 'buy'] = 1
+    mocked_history['enter_long'] = 0
+    mocked_history.loc[1, 'enter_long'] = 1
 
     caplog.set_level(logging.INFO)
     mocker.patch.object(_STRATEGY, 'assert_df')
 
-    assert (True, False, None) == _STRATEGY.get_signal(
+    assert (SignalDirection.LONG, None) == _STRATEGY.get_entry_signal(
         'xyz',
         default_conf['timeframe'],
         mocked_history
@@ -148,7 +195,6 @@ def test_get_signal_no_sell_column(default_conf, mocker, caplog, ohlcv_history):
 
 
 def test_ignore_expired_candle(default_conf):
-    default_conf.update({'strategy': 'StrategyTestV2'})
     strategy = StrategyResolver.load_strategy(default_conf)
     strategy.ignore_buying_expired_candle_after = 60
 
@@ -156,17 +202,21 @@ def test_ignore_expired_candle(default_conf):
     # Add 1 candle length as the "latest date" defines candle open.
     current_time = latest_date + timedelta(seconds=80 + 300)
 
-    assert strategy.ignore_expired_candle(latest_date=latest_date,
-                                          current_time=current_time,
-                                          timeframe_seconds=300,
-                                          buy=True) is True
+    assert strategy.ignore_expired_candle(
+        latest_date=latest_date,
+        current_time=current_time,
+        timeframe_seconds=300,
+        enter=True
+    ) is True
 
     current_time = latest_date + timedelta(seconds=30 + 300)
 
-    assert not strategy.ignore_expired_candle(latest_date=latest_date,
-                                              current_time=current_time,
-                                              timeframe_seconds=300,
-                                              buy=True) is True
+    assert not strategy.ignore_expired_candle(
+        latest_date=latest_date,
+        current_time=current_time,
+        timeframe_seconds=300,
+        enter=True
+    ) is True
 
 
 def test_assert_df_raise(mocker, caplog, ohlcv_history):
@@ -191,8 +241,8 @@ def test_assert_df_raise(mocker, caplog, ohlcv_history):
 
 def test_assert_df(ohlcv_history, caplog):
     df_len = len(ohlcv_history) - 1
-    ohlcv_history.loc[:, 'buy'] = 0
-    ohlcv_history.loc[:, 'sell'] = 0
+    ohlcv_history.loc[:, 'enter_long'] = 0
+    ohlcv_history.loc[:, 'exit_long'] = 0
     # Ensure it's running when passed correctly
     _STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
                         ohlcv_history.loc[df_len, 'close'], ohlcv_history.loc[df_len, 'date'])
@@ -215,8 +265,8 @@ def test_assert_df(ohlcv_history, caplog):
         _STRATEGY.assert_df(None, len(ohlcv_history),
                             ohlcv_history.loc[df_len, 'close'], ohlcv_history.loc[0, 'date'])
     with pytest.raises(StrategyError,
-                       match="Buy column not set"):
-        _STRATEGY.assert_df(ohlcv_history.drop('buy', axis=1), len(ohlcv_history),
+                       match="enter_long/buy column not set."):
+        _STRATEGY.assert_df(ohlcv_history.drop('enter_long', axis=1), len(ohlcv_history),
                             ohlcv_history.loc[df_len, 'close'], ohlcv_history.loc[0, 'date'])
 
     _STRATEGY.disable_dataframe_checks = True
@@ -229,7 +279,6 @@ def test_assert_df(ohlcv_history, caplog):
 
 
 def test_advise_all_indicators(default_conf, testdatadir) -> None:
-    default_conf.update({'strategy': 'StrategyTestV2'})
     strategy = StrategyResolver.load_strategy(default_conf)
 
     timerange = TimeRange.parse_timerange('1510694220-1510700340')
@@ -240,7 +289,6 @@ def test_advise_all_indicators(default_conf, testdatadir) -> None:
 
 
 def test_advise_all_indicators_copy(mocker, default_conf, testdatadir) -> None:
-    default_conf.update({'strategy': 'StrategyTestV2'})
     strategy = StrategyResolver.load_strategy(default_conf)
     aimock = mocker.patch('freqtrade.strategy.interface.IStrategy.advise_indicators')
     timerange = TimeRange.parse_timerange('1510694220-1510700340')
@@ -258,7 +306,6 @@ def test_min_roi_reached(default_conf, fee) -> None:
     min_roi_list = [{20: 0.05, 55: 0.01, 0: 0.1},
                     {0: 0.1, 20: 0.05, 55: 0.01}]
     for roi in min_roi_list:
-        default_conf.update({'strategy': 'StrategyTestV2'})
         strategy = StrategyResolver.load_strategy(default_conf)
         strategy.minimal_roi = roi
         trade = Trade(
@@ -297,7 +344,6 @@ def test_min_roi_reached2(default_conf, fee) -> None:
                      },
                     ]
     for roi in min_roi_list:
-        default_conf.update({'strategy': 'StrategyTestV2'})
         strategy = StrategyResolver.load_strategy(default_conf)
         strategy.minimal_roi = roi
         trade = Trade(
@@ -332,7 +378,6 @@ def test_min_roi_reached3(default_conf, fee) -> None:
                30: 0.05,
                55: 0.30,
                }
-    default_conf.update({'strategy': 'StrategyTestV2'})
     strategy = StrategyResolver.load_strategy(default_conf)
     strategy.minimal_roi = min_roi
     trade = Trade(
@@ -364,29 +409,27 @@ def test_min_roi_reached3(default_conf, fee) -> None:
     'profit,adjusted,expected,trailing,custom,profit2,adjusted2,expected2,custom_stop', [
         # Profit, adjusted stoploss(absolute), profit for 2nd call, enable trailing,
         #   enable custom stoploss, expected after 1st call, expected after 2nd call
-        (0.2, 0.9, SellType.NONE, False, False, 0.3, 0.9, SellType.NONE, None),
-        (0.2, 0.9, SellType.NONE, False, False, -0.2, 0.9, SellType.STOP_LOSS, None),
-        (0.2, 1.14, SellType.NONE, True, False, 0.05, 1.14, SellType.TRAILING_STOP_LOSS, None),
-        (0.01, 0.96, SellType.NONE, True, False, 0.05, 1, SellType.NONE, None),
-        (0.05, 1, SellType.NONE, True, False, -0.01, 1, SellType.TRAILING_STOP_LOSS, None),
+        (0.2, 0.9, ExitType.NONE, False, False, 0.3, 0.9, ExitType.NONE, None),
+        (0.2, 0.9, ExitType.NONE, False, False, -0.2, 0.9, ExitType.STOP_LOSS, None),
+        (0.2, 1.14, ExitType.NONE, True, False, 0.05, 1.14, ExitType.TRAILING_STOP_LOSS, None),
+        (0.01, 0.96, ExitType.NONE, True, False, 0.05, 1, ExitType.NONE, None),
+        (0.05, 1, ExitType.NONE, True, False, -0.01, 1, ExitType.TRAILING_STOP_LOSS, None),
         # Default custom case - trails with 10%
-        (0.05, 0.95, SellType.NONE, False, True, -0.02, 0.95, SellType.NONE, None),
-        (0.05, 0.95, SellType.NONE, False, True, -0.06, 0.95, SellType.TRAILING_STOP_LOSS, None),
-        (0.05, 1, SellType.NONE, False, True, -0.06, 1, SellType.TRAILING_STOP_LOSS,
+        (0.05, 0.95, ExitType.NONE, False, True, -0.02, 0.95, ExitType.NONE, None),
+        (0.05, 0.95, ExitType.NONE, False, True, -0.06, 0.95, ExitType.TRAILING_STOP_LOSS, None),
+        (0.05, 1, ExitType.NONE, False, True, -0.06, 1, ExitType.TRAILING_STOP_LOSS,
          lambda **kwargs: -0.05),
-        (0.05, 1, SellType.NONE, False, True, 0.09, 1.04, SellType.NONE,
+        (0.05, 1, ExitType.NONE, False, True, 0.09, 1.04, ExitType.NONE,
          lambda **kwargs: -0.05),
-        (0.05, 0.95, SellType.NONE, False, True, 0.09, 0.98, SellType.NONE,
+        (0.05, 0.95, ExitType.NONE, False, True, 0.09, 0.98, ExitType.NONE,
          lambda current_profit, **kwargs: -0.1 if current_profit < 0.6 else -(current_profit * 2)),
         # Error case - static stoploss in place
-        (0.05, 0.9, SellType.NONE, False, True, 0.09, 0.9, SellType.NONE,
+        (0.05, 0.9, ExitType.NONE, False, True, 0.09, 0.9, ExitType.NONE,
          lambda **kwargs: None),
     ])
 def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, trailing, custom,
                            profit2, adjusted2, expected2, custom_stop) -> None:
 
-    default_conf.update({'strategy': 'StrategyTestV2'})
-
     strategy = StrategyResolver.load_strategy(default_conf)
     trade = Trade(
         pair='ETH/BTC',
@@ -407,33 +450,33 @@ def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, traili
         strategy.custom_stoploss = custom_stop
 
     now = arrow.utcnow().datetime
-    sl_flag = strategy.stop_loss_reached(current_rate=trade.open_rate * (1 + profit), trade=trade,
+    current_rate = trade.open_rate * (1 + profit)
+    sl_flag = strategy.stop_loss_reached(current_rate=current_rate, trade=trade,
                                          current_time=now, current_profit=profit,
                                          force_stoploss=0, high=None)
-    assert isinstance(sl_flag, SellCheckTuple)
-    assert sl_flag.sell_type == expected
-    if expected == SellType.NONE:
-        assert sl_flag.sell_flag is False
+    assert isinstance(sl_flag, ExitCheckTuple)
+    assert sl_flag.exit_type == expected
+    if expected == ExitType.NONE:
+        assert sl_flag.exit_flag is False
     else:
-        assert sl_flag.sell_flag is True
+        assert sl_flag.exit_flag is True
     assert round(trade.stop_loss, 2) == adjusted
+    current_rate2 = trade.open_rate * (1 + profit2)
 
-    sl_flag = strategy.stop_loss_reached(current_rate=trade.open_rate * (1 + profit2), trade=trade,
+    sl_flag = strategy.stop_loss_reached(current_rate=current_rate2, trade=trade,
                                          current_time=now, current_profit=profit2,
                                          force_stoploss=0, high=None)
-    assert sl_flag.sell_type == expected2
-    if expected2 == SellType.NONE:
-        assert sl_flag.sell_flag is False
+    assert sl_flag.exit_type == expected2
+    if expected2 == ExitType.NONE:
+        assert sl_flag.exit_flag is False
     else:
-        assert sl_flag.sell_flag is True
+        assert sl_flag.exit_flag is True
     assert round(trade.stop_loss, 2) == adjusted2
 
     strategy.custom_stoploss = original_stopvalue
 
 
-def test_custom_sell(default_conf, fee, caplog) -> None:
-
-    default_conf.update({'strategy': 'StrategyTestV2'})
+def test_custom_exit(default_conf, fee, caplog) -> None:
 
     strategy = StrategyResolver.load_strategy(default_conf)
     trade = Trade(
@@ -448,50 +491,84 @@ def test_custom_sell(default_conf, fee, caplog) -> None:
     )
 
     now = arrow.utcnow().datetime
-    res = strategy.should_sell(trade, 1, now, False, False, None, None, 0)
+    res = strategy.should_exit(trade, 1, now,
+                               enter=False, exit_=False,
+                               low=None, high=None)
 
-    assert res.sell_flag is False
-    assert res.sell_type == SellType.NONE
+    assert res.exit_flag is False
+    assert res.exit_type == ExitType.NONE
 
-    strategy.custom_sell = MagicMock(return_value=True)
-    res = strategy.should_sell(trade, 1, now, False, False, None, None, 0)
-    assert res.sell_flag is True
-    assert res.sell_type == SellType.CUSTOM_SELL
-    assert res.sell_reason == 'custom_sell'
+    strategy.custom_exit = MagicMock(return_value=True)
+    res = strategy.should_exit(trade, 1, now,
+                               enter=False, exit_=False,
+                               low=None, high=None)
+    assert res.exit_flag is True
+    assert res.exit_type == ExitType.CUSTOM_EXIT
+    assert res.exit_reason == 'custom_exit'
 
-    strategy.custom_sell = MagicMock(return_value='hello world')
+    strategy.custom_exit = MagicMock(return_value='hello world')
 
-    res = strategy.should_sell(trade, 1, now, False, False, None, None, 0)
-    assert res.sell_type == SellType.CUSTOM_SELL
-    assert res.sell_flag is True
-    assert res.sell_reason == 'hello world'
+    res = strategy.should_exit(trade, 1, now,
+                               enter=False, exit_=False,
+                               low=None, high=None)
+    assert res.exit_type == ExitType.CUSTOM_EXIT
+    assert res.exit_flag is True
+    assert res.exit_reason == 'hello world'
 
     caplog.clear()
-    strategy.custom_sell = MagicMock(return_value='h' * 100)
-    res = strategy.should_sell(trade, 1, now, False, False, None, None, 0)
-    assert res.sell_type == SellType.CUSTOM_SELL
-    assert res.sell_flag is True
-    assert res.sell_reason == 'h' * 64
-    assert log_has_re('Custom sell reason returned from custom_sell is too long.*', caplog)
+    strategy.custom_exit = MagicMock(return_value='h' * 100)
+    res = strategy.should_exit(trade, 1, now,
+                               enter=False, exit_=False,
+                               low=None, high=None)
+    assert res.exit_type == ExitType.CUSTOM_EXIT
+    assert res.exit_flag is True
+    assert res.exit_reason == 'h' * 64
+    assert log_has_re('Custom exit reason returned from custom_exit is too long.*', caplog)
+
+
+@pytest.mark.parametrize('side', TRADE_SIDES)
+def test_leverage_callback(default_conf, side) -> None:
+    default_conf['strategy'] = 'StrategyTestV2'
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.leverage(
+        pair='XRP/USDT',
+        current_time=datetime.now(timezone.utc),
+        current_rate=2.2,
+        proposed_leverage=1.0,
+        max_leverage=5.0,
+        side=side,
+        ) == 1
+
+    default_conf['strategy'] = CURRENT_TEST_STRATEGY
+    strategy = StrategyResolver.load_strategy(default_conf)
+    assert strategy.leverage(
+        pair='XRP/USDT',
+        current_time=datetime.now(timezone.utc),
+        current_rate=2.2,
+        proposed_leverage=1.0,
+        max_leverage=5.0,
+        side=side,
+        ) == 3
 
 
 def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
     caplog.set_level(logging.DEBUG)
     ind_mock = MagicMock(side_effect=lambda x, meta: x)
-    buy_mock = MagicMock(side_effect=lambda x, meta: x)
-    sell_mock = MagicMock(side_effect=lambda x, meta: x)
+    entry_mock = MagicMock(side_effect=lambda x, meta: x)
+    exit_mock = MagicMock(side_effect=lambda x, meta: x)
     mocker.patch.multiple(
         'freqtrade.strategy.interface.IStrategy',
         advise_indicators=ind_mock,
-        advise_buy=buy_mock,
-        advise_sell=sell_mock,
+        advise_entry=entry_mock,
+        advise_exit=exit_mock,
 
     )
-    strategy = StrategyTestV2({})
+    strategy = StrategyTestV3({})
     strategy.analyze_ticker(ohlcv_history, {'pair': 'ETH/BTC'})
     assert ind_mock.call_count == 1
-    assert buy_mock.call_count == 1
-    assert buy_mock.call_count == 1
+    assert entry_mock.call_count == 1
+    assert entry_mock.call_count == 1
 
     assert log_has('TA Analysis Launched', caplog)
     assert not log_has('Skipping TA Analysis for already analyzed candle', caplog)
@@ -500,8 +577,8 @@ def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
     strategy.analyze_ticker(ohlcv_history, {'pair': 'ETH/BTC'})
     # No analysis happens as process_only_new_candles is true
     assert ind_mock.call_count == 2
-    assert buy_mock.call_count == 2
-    assert buy_mock.call_count == 2
+    assert entry_mock.call_count == 2
+    assert entry_mock.call_count == 2
     assert log_has('TA Analysis Launched', caplog)
     assert not log_has('Skipping TA Analysis for already analyzed candle', caplog)
 
@@ -509,16 +586,16 @@ def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
 def test__analyze_ticker_internal_skip_analyze(ohlcv_history, mocker, caplog) -> None:
     caplog.set_level(logging.DEBUG)
     ind_mock = MagicMock(side_effect=lambda x, meta: x)
-    buy_mock = MagicMock(side_effect=lambda x, meta: x)
-    sell_mock = MagicMock(side_effect=lambda x, meta: x)
+    entry_mock = MagicMock(side_effect=lambda x, meta: x)
+    exit_mock = MagicMock(side_effect=lambda x, meta: x)
     mocker.patch.multiple(
         'freqtrade.strategy.interface.IStrategy',
         advise_indicators=ind_mock,
-        advise_buy=buy_mock,
-        advise_sell=sell_mock,
+        advise_entry=entry_mock,
+        advise_exit=exit_mock,
 
     )
-    strategy = StrategyTestV2({})
+    strategy = StrategyTestV3({})
     strategy.dp = DataProvider({}, None, None)
     strategy.process_only_new_candles = True
 
@@ -528,8 +605,8 @@ def test__analyze_ticker_internal_skip_analyze(ohlcv_history, mocker, caplog) ->
     assert 'close' in ret.columns
     assert isinstance(ret, DataFrame)
     assert ind_mock.call_count == 1
-    assert buy_mock.call_count == 1
-    assert buy_mock.call_count == 1
+    assert entry_mock.call_count == 1
+    assert entry_mock.call_count == 1
     assert log_has('TA Analysis Launched', caplog)
     assert not log_has('Skipping TA Analysis for already analyzed candle', caplog)
     caplog.clear()
@@ -537,20 +614,19 @@ def test__analyze_ticker_internal_skip_analyze(ohlcv_history, mocker, caplog) ->
     ret = strategy._analyze_ticker_internal(ohlcv_history, {'pair': 'ETH/BTC'})
     # No analysis happens as process_only_new_candles is true
     assert ind_mock.call_count == 1
-    assert buy_mock.call_count == 1
-    assert buy_mock.call_count == 1
+    assert entry_mock.call_count == 1
+    assert entry_mock.call_count == 1
     # only skipped analyze adds buy and sell columns, otherwise it's all mocked
-    assert 'buy' in ret.columns
-    assert 'sell' in ret.columns
-    assert ret['buy'].sum() == 0
-    assert ret['sell'].sum() == 0
+    assert 'enter_long' in ret.columns
+    assert 'exit_long' in ret.columns
+    assert ret['enter_long'].sum() == 0
+    assert ret['exit_long'].sum() == 0
     assert not log_has('TA Analysis Launched', caplog)
     assert log_has('Skipping TA Analysis for already analyzed candle', caplog)
 
 
 @pytest.mark.usefixtures("init_persistence")
 def test_is_pair_locked(default_conf):
-    default_conf.update({'strategy': 'StrategyTestV2'})
     PairLocks.timeframe = default_conf['timeframe']
     PairLocks.use_db = True
     strategy = StrategyResolver.load_strategy(default_conf)
@@ -575,6 +651,13 @@ def test_is_pair_locked(default_conf):
     strategy.unlock_pair(pair)
     assert not strategy.is_pair_locked(pair)
 
+    # Lock with reason
+    reason = "TestLockR"
+    strategy.lock_pair(pair, arrow.now(timezone.utc).shift(minutes=4).datetime, reason)
+    assert strategy.is_pair_locked(pair)
+    strategy.unlock_reason(reason)
+    assert not strategy.is_pair_locked(pair)
+
     pair = 'BTC/USDT'
     # Lock until 14:30
     lock_time = datetime(2020, 5, 1, 14, 30, 0, tzinfo=timezone.utc)
@@ -646,7 +729,7 @@ def test_strategy_safe_wrapper(value):
 
     ret = strategy_safe_wrapper(working_method, message='DeadBeef')(value)
 
-    assert type(ret) == type(value)
+    assert isinstance(ret, type(value))
     assert ret == value
 
 
diff --git a/tests/strategy/test_strategy_helpers.py b/tests/strategy/test_strategy_helpers.py
index a01b55050..65fb9f6dc 100644
--- a/tests/strategy/test_strategy_helpers.py
+++ b/tests/strategy/test_strategy_helpers.py
@@ -5,17 +5,20 @@ import pandas as pd
 import pytest
 
 from freqtrade.data.dataprovider import DataProvider
+from freqtrade.enums import CandleType
+from freqtrade.resolvers.strategy_resolver import StrategyResolver
 from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute, stoploss_from_open,
                                 timeframe_to_minutes)
+from tests.conftest import get_patched_exchange
 
 
-def generate_test_data(timeframe: str, size: int):
+def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
     np.random.seed(42)
     tf_mins = timeframe_to_minutes(timeframe)
 
     base = np.random.normal(20, 2, size=size)
 
-    date = pd.period_range('2020-07-05', periods=size, freq=f'{tf_mins}min').to_timestamp()
+    date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
     df = pd.DataFrame({
         'date': date,
         'open': base,
@@ -107,87 +110,127 @@ def test_stoploss_from_open():
         [1, 100, 30],
         [100, 10000, 30],
     ]
-    current_profit_range = [-0.99, 2, 30]
+    # profit range for long is [-1, inf] while for shorts is [-inf, 1]
+    current_profit_range_dict = {'long': [-0.99, 2, 30], 'short': [-2.0, 0.99, 30]}
     desired_stop_range = [-0.50, 0.50, 30]
 
-    for open_range in open_price_ranges:
-        for open_price in np.linspace(*open_range):
-            for desired_stop in np.linspace(*desired_stop_range):
+    for side, current_profit_range in current_profit_range_dict.items():
+        for open_range in open_price_ranges:
+            for open_price in np.linspace(*open_range):
+                for desired_stop in np.linspace(*desired_stop_range):
 
-                # -1 is not a valid current_profit, should return 1
-                assert stoploss_from_open(desired_stop, -1) == 1
-
-                for current_profit in np.linspace(*current_profit_range):
-                    current_price = open_price * (1 + current_profit)
-                    expected_stop_price = open_price * (1 + desired_stop)
-
-                    stoploss = stoploss_from_open(desired_stop, current_profit)
-
-                    assert stoploss >= 0
-                    assert stoploss <= 1
-
-                    stop_price = current_price * (1 - stoploss)
-
-                    # there is no correct answer if the expected stop price is above
-                    # the current price
-                    if expected_stop_price > current_price:
-                        assert stoploss == 0
+                    if side == 'long':
+                        # -1 is not a valid current_profit, should return 1
+                        assert stoploss_from_open(desired_stop, -1) == 1
                     else:
-                        assert isclose(stop_price, expected_stop_price, rel_tol=0.00001)
+                        # 1 is not a valid current_profit for shorts, should return 1
+                        assert stoploss_from_open(desired_stop, 1, True) == 1
+
+                    for current_profit in np.linspace(*current_profit_range):
+                        if side == 'long':
+                            current_price = open_price * (1 + current_profit)
+                            expected_stop_price = open_price * (1 + desired_stop)
+                            stoploss = stoploss_from_open(desired_stop, current_profit)
+                            stop_price = current_price * (1 - stoploss)
+                        else:
+                            current_price = open_price * (1 - current_profit)
+                            expected_stop_price = open_price * (1 - desired_stop)
+                            stoploss = stoploss_from_open(desired_stop, current_profit, True)
+                            stop_price = current_price * (1 + stoploss)
+
+                        assert stoploss >= 0
+                        # Technically the formula can yield values greater than 1 for shorts
+                        # eventhough it doesn't make sense because the position would be liquidated
+                        if side == 'long':
+                            assert stoploss <= 1
+
+                        # there is no correct answer if the expected stop price is above
+                        # the current price
+                        if ((side == 'long' and expected_stop_price > current_price)
+                                or (side == 'short' and expected_stop_price < current_price)):
+                            assert stoploss == 0
+                        else:
+                            assert isclose(stop_price, expected_stop_price, rel_tol=0.00001)
 
 
 def test_stoploss_from_absolute():
-    assert stoploss_from_absolute(90, 100) == 1 - (90 / 100)
-    assert stoploss_from_absolute(100, 100) == 0
-    assert stoploss_from_absolute(110, 100) == 0
-    assert stoploss_from_absolute(100, 0) == 1
-    assert stoploss_from_absolute(0, 100) == 1
+    assert pytest.approx(stoploss_from_absolute(90, 100)) == 1 - (90 / 100)
+    assert pytest.approx(stoploss_from_absolute(90, 100)) == 0.1
+    assert pytest.approx(stoploss_from_absolute(95, 100)) == 0.05
+    assert pytest.approx(stoploss_from_absolute(100, 100)) == 0
+    assert pytest.approx(stoploss_from_absolute(110, 100)) == 0
+    assert pytest.approx(stoploss_from_absolute(100, 0)) == 1
+    assert pytest.approx(stoploss_from_absolute(0, 100)) == 1
+
+    assert pytest.approx(stoploss_from_absolute(90, 100, True)) == 0
+    assert pytest.approx(stoploss_from_absolute(100, 100, True)) == 0
+    assert pytest.approx(stoploss_from_absolute(110, 100, True)) == -(1 - (110 / 100))
+    assert pytest.approx(stoploss_from_absolute(110, 100, True)) == 0.1
+    assert pytest.approx(stoploss_from_absolute(105, 100, True)) == 0.05
+    assert pytest.approx(stoploss_from_absolute(100, 0, True)) == 1
+    assert pytest.approx(stoploss_from_absolute(0, 100, True)) == 0
+    assert pytest.approx(stoploss_from_absolute(100, 1, True)) == 1
 
 
-def test_informative_decorator(mocker, default_conf):
+@pytest.mark.parametrize('trading_mode', ['futures', 'spot'])
+def test_informative_decorator(mocker, default_conf_usdt, trading_mode):
+    candle_def = CandleType.get_default(trading_mode)
+    default_conf_usdt['candle_type_def'] = candle_def
     test_data_5m = generate_test_data('5m', 40)
     test_data_30m = generate_test_data('30m', 40)
     test_data_1h = generate_test_data('1h', 40)
     data = {
-        ('XRP/USDT', '5m'): test_data_5m,
-        ('XRP/USDT', '30m'): test_data_30m,
-        ('XRP/USDT', '1h'): test_data_1h,
-        ('LTC/USDT', '5m'): test_data_5m,
-        ('LTC/USDT', '30m'): test_data_30m,
-        ('LTC/USDT', '1h'): test_data_1h,
-        ('BTC/USDT', '30m'): test_data_30m,
-        ('BTC/USDT', '5m'): test_data_5m,
-        ('BTC/USDT', '1h'): test_data_1h,
-        ('ETH/USDT', '1h'): test_data_1h,
-        ('ETH/USDT', '30m'): test_data_30m,
-        ('ETH/BTC', '1h'): test_data_1h,
+        ('XRP/USDT', '5m', candle_def): test_data_5m,
+        ('XRP/USDT', '30m', candle_def): test_data_30m,
+        ('XRP/USDT', '1h', candle_def): test_data_1h,
+        ('LTC/USDT', '5m', candle_def): test_data_5m,
+        ('LTC/USDT', '30m', candle_def): test_data_30m,
+        ('LTC/USDT', '1h', candle_def): test_data_1h,
+        ('NEO/USDT', '30m', candle_def): test_data_30m,
+        ('NEO/USDT', '5m', CandleType.SPOT): test_data_5m,  # Explicit request with '' as candletype
+        ('NEO/USDT', '15m', candle_def): test_data_5m,  # Explicit request with '' as candletype
+        ('NEO/USDT', '1h', candle_def): test_data_1h,
+        ('ETH/USDT', '1h', candle_def): test_data_1h,
+        ('ETH/USDT', '30m', candle_def): test_data_30m,
+        ('ETH/BTC', '1h', CandleType.SPOT): test_data_1h,  # Explicitly selected as spot
     }
-    from .strats.informative_decorator_strategy import InformativeDecoratorTest
-    default_conf['stake_currency'] = 'USDT'
-    strategy = InformativeDecoratorTest(config=default_conf)
-    strategy.dp = DataProvider({}, None, None)
+    default_conf_usdt['strategy'] = 'InformativeDecoratorTest'
+    strategy = StrategyResolver.load_strategy(default_conf_usdt)
+    exchange = get_patched_exchange(mocker, default_conf_usdt)
+    strategy.dp = DataProvider({}, exchange, None)
     mocker.patch.object(strategy.dp, 'current_whitelist', return_value=[
-        'XRP/USDT', 'LTC/USDT', 'BTC/USDT'
+        'XRP/USDT', 'LTC/USDT', 'NEO/USDT'
     ])
 
     assert len(strategy._ft_informative) == 6   # Equal to number of decorators used
-    informative_pairs = [('XRP/USDT', '1h'), ('LTC/USDT', '1h'), ('XRP/USDT', '30m'),
-                         ('LTC/USDT', '30m'), ('BTC/USDT', '1h'), ('BTC/USDT', '30m'),
-                         ('BTC/USDT', '5m'), ('ETH/BTC', '1h'), ('ETH/USDT', '30m')]
+    informative_pairs = [
+        ('XRP/USDT', '1h', candle_def),
+        ('LTC/USDT', '1h', candle_def),
+        ('XRP/USDT', '30m', candle_def),
+        ('LTC/USDT', '30m', candle_def),
+        ('NEO/USDT', '1h', candle_def),
+        ('NEO/USDT', '30m', candle_def),
+        ('NEO/USDT', '5m', candle_def),
+        ('NEO/USDT', '15m', candle_def),
+        ('NEO/USDT', '2h', CandleType.FUTURES),
+        ('ETH/BTC', '1h', CandleType.SPOT),  # One candle remains as spot
+        ('ETH/USDT', '30m', candle_def)]
     for inf_pair in informative_pairs:
         assert inf_pair in strategy.gather_informative_pairs()
 
-    def test_historic_ohlcv(pair, timeframe):
-        return data[(pair, timeframe or strategy.timeframe)].copy()
+    def test_historic_ohlcv(pair, timeframe, candle_type):
+        return data[
+            (pair, timeframe or strategy.timeframe, CandleType.from_string(candle_type))].copy()
+
     mocker.patch('freqtrade.data.dataprovider.DataProvider.historic_ohlcv',
                  side_effect=test_historic_ohlcv)
 
     analyzed = strategy.advise_all_indicators(
-        {p: data[(p, strategy.timeframe)] for p in ('XRP/USDT', 'LTC/USDT')})
+        {p: data[(p, strategy.timeframe, candle_def)] for p in ('XRP/USDT', 'LTC/USDT')})
     expected_columns = [
         'rsi_1h', 'rsi_30m',                    # Stacked informative decorators
-        'btc_usdt_rsi_1h',                      # BTC 1h informative
-        'rsi_BTC_USDT_btc_usdt_BTC/USDT_30m',   # Column formatting
+        'neo_usdt_rsi_1h',                      # NEO 1h informative
+        'rsi_NEO_USDT_neo_usdt_NEO/USDT_30m',   # Column formatting
         'rsi_from_callable',                    # Custom column formatter
         'eth_btc_rsi_1h',                       # Quote currency not matching stake currency
         'rsi', 'rsi_less',                      # Non-informative columns
diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py
index 3a30a824a..e74a2a022 100644
--- a/tests/strategy/test_strategy_loading.py
+++ b/tests/strategy/test_strategy_loading.py
@@ -10,7 +10,7 @@ from pandas import DataFrame
 from freqtrade.exceptions import OperationalException
 from freqtrade.resolvers import StrategyResolver
 from freqtrade.strategy.interface import IStrategy
-from tests.conftest import log_has, log_has_re
+from tests.conftest import CURRENT_TEST_STRATEGY, log_has, log_has_re
 
 
 def test_search_strategy():
@@ -18,7 +18,7 @@ def test_search_strategy():
 
     s, _ = StrategyResolver._search_object(
         directory=default_location,
-        object_name='StrategyTestV2',
+        object_name=CURRENT_TEST_STRATEGY,
         add_source=True,
     )
     assert issubclass(s, IStrategy)
@@ -35,7 +35,7 @@ def test_search_all_strategies_no_failed():
     directory = Path(__file__).parent / "strats"
     strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
     assert isinstance(strategies, list)
-    assert len(strategies) == 4
+    assert len(strategies) == 6
     assert isinstance(strategies[0], dict)
 
 
@@ -43,10 +43,10 @@ def test_search_all_strategies_with_failed():
     directory = Path(__file__).parent / "strats"
     strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
     assert isinstance(strategies, list)
-    assert len(strategies) == 5
+    assert len(strategies) == 7
     # with enum_failed=True search_all_objects() shall find 2 good strategies
     # and 1 which fails to load
-    assert len([x for x in strategies if x['class'] is not None]) == 4
+    assert len([x for x in strategies if x['class'] is not None]) == 6
     assert len([x for x in strategies if x['class'] is None]) == 1
 
 
@@ -62,8 +62,8 @@ def test_load_strategy(default_conf, result):
 
 
 def test_load_strategy_base64(result, caplog, default_conf):
-    with (Path(__file__).parents[2] / 'freqtrade/templates/sample_strategy.py').open("rb") as file:
-        encoded_string = urlsafe_b64encode(file.read()).decode("utf-8")
+    filepath = Path(__file__).parents[2] / 'freqtrade/templates/sample_strategy.py'
+    encoded_string = urlsafe_b64encode(filepath.read_bytes()).decode("utf-8")
     default_conf.update({'strategy': 'SampleStrategy:{}'.format(encoded_string)})
 
     strategy = StrategyResolver.load_strategy(default_conf)
@@ -74,10 +74,10 @@ def test_load_strategy_base64(result, caplog, default_conf):
 
 
 def test_load_strategy_invalid_directory(result, caplog, default_conf):
-    default_conf['strategy'] = 'StrategyTestV2'
+    default_conf['strategy'] = 'StrategyTestV3'
     extra_dir = Path.cwd() / 'some/path'
     with pytest.raises(OperationalException):
-        StrategyResolver._load_strategy('StrategyTestV2', config=default_conf,
+        StrategyResolver._load_strategy(CURRENT_TEST_STRATEGY, config=default_conf,
                                         extra_dir=extra_dir)
 
     assert log_has_re(r'Path .*' + r'some.*path.*' + r'.* does not exist', caplog)
@@ -99,8 +99,10 @@ def test_load_strategy_noname(default_conf):
         StrategyResolver.load_strategy(default_conf)
 
 
-def test_strategy(result, default_conf):
-    default_conf.update({'strategy': 'StrategyTestV2'})
+@pytest.mark.filterwarnings("ignore:deprecated")
+@pytest.mark.parametrize('strategy_name', ['StrategyTestV2', 'TestStrategyLegacyV1'])
+def test_strategy_pre_v3(result, default_conf, strategy_name):
+    default_conf.update({'strategy': strategy_name})
 
     strategy = StrategyResolver.load_strategy(default_conf)
     metadata = {'pair': 'ETH/BTC'}
@@ -111,23 +113,40 @@ def test_strategy(result, default_conf):
     assert default_conf['stoploss'] == -0.10
 
     assert strategy.timeframe == '5m'
-    assert strategy.ticker_interval == '5m'
     assert default_conf['timeframe'] == '5m'
 
     df_indicators = strategy.advise_indicators(result, metadata=metadata)
     assert 'adx' in df_indicators
 
-    dataframe = strategy.advise_buy(df_indicators, metadata=metadata)
-    assert 'buy' in dataframe.columns
+    dataframe = strategy.advise_entry(df_indicators, metadata=metadata)
+    assert 'buy' not in dataframe.columns
+    assert 'enter_long' in dataframe.columns
 
-    dataframe = strategy.advise_sell(df_indicators, metadata=metadata)
-    assert 'sell' in dataframe.columns
+    dataframe = strategy.advise_exit(df_indicators, metadata=metadata)
+    assert 'sell' not in dataframe.columns
+    assert 'exit_long' in dataframe.columns
+
+
+def test_strategy_can_short(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+    default_conf.update({
+        'strategy': CURRENT_TEST_STRATEGY,
+    })
+    strat = StrategyResolver.load_strategy(default_conf)
+    assert isinstance(strat, IStrategy)
+    default_conf['strategy'] = 'StrategyTestV3Futures'
+    with pytest.raises(ImportError, match=""):
+        StrategyResolver.load_strategy(default_conf)
+
+    default_conf['trading_mode'] = 'futures'
+    strat = StrategyResolver.load_strategy(default_conf)
+    assert isinstance(strat, IStrategy)
 
 
 def test_strategy_override_minimal_roi(caplog, default_conf):
     caplog.set_level(logging.INFO)
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
         'minimal_roi': {
             "20": 0.1,
             "0": 0.5
@@ -144,7 +163,7 @@ def test_strategy_override_minimal_roi(caplog, default_conf):
 def test_strategy_override_stoploss(caplog, default_conf):
     caplog.set_level(logging.INFO)
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
         'stoploss': -0.5
     })
     strategy = StrategyResolver.load_strategy(default_conf)
@@ -156,7 +175,7 @@ def test_strategy_override_stoploss(caplog, default_conf):
 def test_strategy_override_trailing_stop(caplog, default_conf):
     caplog.set_level(logging.INFO)
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
         'trailing_stop': True
     })
     strategy = StrategyResolver.load_strategy(default_conf)
@@ -169,7 +188,7 @@ def test_strategy_override_trailing_stop(caplog, default_conf):
 def test_strategy_override_trailing_stop_positive(caplog, default_conf):
     caplog.set_level(logging.INFO)
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
         'trailing_stop_positive': -0.1,
         'trailing_stop_positive_offset': -0.2
 
@@ -189,7 +208,7 @@ def test_strategy_override_timeframe(caplog, default_conf):
     caplog.set_level(logging.INFO)
 
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
         'timeframe': 60,
         'stake_currency': 'ETH'
     })
@@ -205,7 +224,7 @@ def test_strategy_override_process_only_new_candles(caplog, default_conf):
     caplog.set_level(logging.INFO)
 
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
         'process_only_new_candles': True
     })
     strategy = StrategyResolver.load_strategy(default_conf)
@@ -219,32 +238,32 @@ def test_strategy_override_order_types(caplog, default_conf):
     caplog.set_level(logging.INFO)
 
     order_types = {
-        'buy': 'market',
-        'sell': 'limit',
+        'entry': 'market',
+        'exit': 'limit',
         'stoploss': 'limit',
         'stoploss_on_exchange': True,
     }
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
         'order_types': order_types
     })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.order_types
-    for method in ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']:
+    for method in ['entry', 'exit', 'stoploss', 'stoploss_on_exchange']:
         assert strategy.order_types[method] == order_types[method]
 
     assert log_has("Override strategy 'order_types' with value in config file:"
-                   " {'buy': 'market', 'sell': 'limit', 'stoploss': 'limit',"
+                   " {'entry': 'market', 'exit': 'limit', 'stoploss': 'limit',"
                    " 'stoploss_on_exchange': True}.", caplog)
 
     default_conf.update({
-        'strategy': 'StrategyTestV2',
-        'order_types': {'buy': 'market'}
+        'strategy': CURRENT_TEST_STRATEGY,
+        'order_types': {'exit': 'market'}
     })
     # Raise error for invalid configuration
     with pytest.raises(ImportError,
-                       match=r"Impossible to load Strategy 'StrategyTestV2'. "
+                       match=r"Impossible to load Strategy '" + CURRENT_TEST_STRATEGY + "'. "
                              r"Order-types mapping is incomplete."):
         StrategyResolver.load_strategy(default_conf)
 
@@ -253,78 +272,78 @@ def test_strategy_override_order_tif(caplog, default_conf):
     caplog.set_level(logging.INFO)
 
     order_time_in_force = {
-        'buy': 'fok',
-        'sell': 'gtc',
+        'entry': 'fok',
+        'exit': 'gtc',
     }
 
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
         'order_time_in_force': order_time_in_force
     })
     strategy = StrategyResolver.load_strategy(default_conf)
 
     assert strategy.order_time_in_force
-    for method in ['buy', 'sell']:
+    for method in ['entry', 'exit']:
         assert strategy.order_time_in_force[method] == order_time_in_force[method]
 
     assert log_has("Override strategy 'order_time_in_force' with value in config file:"
-                   " {'buy': 'fok', 'sell': 'gtc'}.", caplog)
+                   " {'entry': 'fok', 'exit': 'gtc'}.", caplog)
 
     default_conf.update({
-        'strategy': 'StrategyTestV2',
-        'order_time_in_force': {'buy': 'fok'}
+        'strategy': CURRENT_TEST_STRATEGY,
+        'order_time_in_force': {'entry': 'fok'}
     })
     # Raise error for invalid configuration
     with pytest.raises(ImportError,
-                       match=r"Impossible to load Strategy 'StrategyTestV2'. "
-                             r"Order-time-in-force mapping is incomplete."):
+                       match=f"Impossible to load Strategy '{CURRENT_TEST_STRATEGY}'. "
+                             "Order-time-in-force mapping is incomplete."):
         StrategyResolver.load_strategy(default_conf)
 
 
-def test_strategy_override_use_sell_signal(caplog, default_conf):
+def test_strategy_override_use_exit_signal(caplog, default_conf):
     caplog.set_level(logging.INFO)
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
     })
     strategy = StrategyResolver.load_strategy(default_conf)
-    assert strategy.use_sell_signal
-    assert isinstance(strategy.use_sell_signal, bool)
+    assert strategy.use_exit_signal
+    assert isinstance(strategy.use_exit_signal, bool)
     # must be inserted to configuration
-    assert 'use_sell_signal' in default_conf
-    assert default_conf['use_sell_signal']
+    assert 'use_exit_signal' in default_conf
+    assert default_conf['use_exit_signal']
 
     default_conf.update({
-        'strategy': 'StrategyTestV2',
-        'use_sell_signal': False,
+        'strategy': CURRENT_TEST_STRATEGY,
+        'use_exit_signal': False,
     })
     strategy = StrategyResolver.load_strategy(default_conf)
 
-    assert not strategy.use_sell_signal
-    assert isinstance(strategy.use_sell_signal, bool)
-    assert log_has("Override strategy 'use_sell_signal' with value in config file: False.", caplog)
+    assert not strategy.use_exit_signal
+    assert isinstance(strategy.use_exit_signal, bool)
+    assert log_has("Override strategy 'use_exit_signal' with value in config file: False.", caplog)
 
 
-def test_strategy_override_use_sell_profit_only(caplog, default_conf):
+def test_strategy_override_use_exit_profit_only(caplog, default_conf):
     caplog.set_level(logging.INFO)
     default_conf.update({
-        'strategy': 'StrategyTestV2',
+        'strategy': CURRENT_TEST_STRATEGY,
     })
     strategy = StrategyResolver.load_strategy(default_conf)
-    assert not strategy.sell_profit_only
-    assert isinstance(strategy.sell_profit_only, bool)
+    assert not strategy.exit_profit_only
+    assert isinstance(strategy.exit_profit_only, bool)
     # must be inserted to configuration
-    assert 'sell_profit_only' in default_conf
-    assert not default_conf['sell_profit_only']
+    assert 'exit_profit_only' in default_conf
+    assert not default_conf['exit_profit_only']
 
     default_conf.update({
-        'strategy': 'StrategyTestV2',
-        'sell_profit_only': True,
+        'strategy': CURRENT_TEST_STRATEGY,
+        'exit_profit_only': True,
     })
     strategy = StrategyResolver.load_strategy(default_conf)
 
-    assert strategy.sell_profit_only
-    assert isinstance(strategy.sell_profit_only, bool)
-    assert log_has("Override strategy 'sell_profit_only' with value in config file: True.", caplog)
+    assert strategy.exit_profit_only
+    assert isinstance(strategy.exit_profit_only, bool)
+    assert log_has("Override strategy 'exit_profit_only' with value in config file: True.", caplog)
 
 
 @pytest.mark.filterwarnings("ignore:deprecated")
@@ -345,7 +364,7 @@ def test_deprecate_populate_indicators(result, default_conf):
     with warnings.catch_warnings(record=True) as w:
         # Cause all warnings to always be triggered.
         warnings.simplefilter("always")
-        strategy.advise_buy(indicators, {'pair': 'ETH/BTC'})
+        strategy.advise_entry(indicators, {'pair': 'ETH/BTC'})
         assert len(w) == 1
         assert issubclass(w[-1].category, DeprecationWarning)
         assert "deprecated - check out the Sample strategy to see the current function headers!" \
@@ -354,7 +373,7 @@ def test_deprecate_populate_indicators(result, default_conf):
     with warnings.catch_warnings(record=True) as w:
         # Cause all warnings to always be triggered.
         warnings.simplefilter("always")
-        strategy.advise_sell(indicators, {'pair': 'ETH_BTC'})
+        strategy.advise_exit(indicators, {'pair': 'ETH_BTC'})
         assert len(w) == 1
         assert issubclass(w[-1].category, DeprecationWarning)
         assert "deprecated - check out the Sample strategy to see the current function headers!" \
@@ -362,7 +381,65 @@ def test_deprecate_populate_indicators(result, default_conf):
 
 
 @pytest.mark.filterwarnings("ignore:deprecated")
-def test_call_deprecated_function(result, monkeypatch, default_conf, caplog):
+def test_missing_implements(default_conf, caplog):
+
+    default_location = Path(__file__).parent / "strats"
+    default_conf.update({'strategy': 'StrategyTestV2',
+                         'strategy_path': default_location})
+    StrategyResolver.load_strategy(default_conf)
+
+    log_has_re(r"DEPRECATED: .*use_sell_signal.*use_exit_signal.", caplog)
+
+    default_conf['trading_mode'] = 'futures'
+    with pytest.raises(OperationalException,
+                       match=r"DEPRECATED: .*use_sell_signal.*use_exit_signal."):
+        StrategyResolver.load_strategy(default_conf)
+
+    default_conf['trading_mode'] = 'spot'
+
+    default_location = Path(__file__).parent / "strats/broken_strats"
+    default_conf.update({'strategy': 'TestStrategyNoImplements',
+                         'strategy_path': default_location})
+    with pytest.raises(OperationalException,
+                       match=r"`populate_entry_trend` or `populate_buy_trend`.*"):
+        StrategyResolver.load_strategy(default_conf)
+
+    default_conf['strategy'] = 'TestStrategyNoImplementSell'
+
+    with pytest.raises(OperationalException,
+                       match=r"`populate_exit_trend` or `populate_sell_trend`.*"):
+        StrategyResolver.load_strategy(default_conf)
+
+    # Futures mode is more strict ...
+    default_conf['trading_mode'] = 'futures'
+
+    with pytest.raises(OperationalException,
+                       match=r"`populate_exit_trend` must be implemented.*"):
+        StrategyResolver.load_strategy(default_conf)
+
+    default_conf['strategy'] = 'TestStrategyNoImplements'
+    with pytest.raises(OperationalException,
+                       match=r"`populate_entry_trend` must be implemented.*"):
+        StrategyResolver.load_strategy(default_conf)
+
+    default_conf['strategy'] = 'TestStrategyImplementCustomSell'
+    with pytest.raises(OperationalException,
+                       match=r"Please migrate your implementation of `custom_sell`.*"):
+        StrategyResolver.load_strategy(default_conf)
+
+    default_conf['strategy'] = 'TestStrategyImplementBuyTimeout'
+    with pytest.raises(OperationalException,
+                       match=r"Please migrate your implementation of `check_buy_timeout`.*"):
+        StrategyResolver.load_strategy(default_conf)
+
+    default_conf['strategy'] = 'TestStrategyImplementSellTimeout'
+    with pytest.raises(OperationalException,
+                       match=r"Please migrate your implementation of `check_sell_timeout`.*"):
+        StrategyResolver.load_strategy(default_conf)
+
+
+@pytest.mark.filterwarnings("ignore:deprecated")
+def test_call_deprecated_function(result, default_conf, caplog):
     default_location = Path(__file__).parent / "strats"
     del default_conf['timeframe']
     default_conf.update({'strategy': 'TestStrategyLegacyV1',
@@ -376,25 +453,21 @@ def test_call_deprecated_function(result, monkeypatch, default_conf, caplog):
     assert strategy._sell_fun_len == 2
     assert strategy.INTERFACE_VERSION == 1
     assert strategy.timeframe == '5m'
-    assert strategy.ticker_interval == '5m'
 
     indicator_df = strategy.advise_indicators(result, metadata=metadata)
     assert isinstance(indicator_df, DataFrame)
     assert 'adx' in indicator_df.columns
 
-    buydf = strategy.advise_buy(result, metadata=metadata)
-    assert isinstance(buydf, DataFrame)
-    assert 'buy' in buydf.columns
+    enterdf = strategy.advise_entry(result, metadata=metadata)
+    assert isinstance(enterdf, DataFrame)
+    assert 'enter_long' in enterdf.columns
 
-    selldf = strategy.advise_sell(result, metadata=metadata)
-    assert isinstance(selldf, DataFrame)
-    assert 'sell' in selldf
-
-    assert log_has("DEPRECATED: Please migrate to using 'timeframe' instead of 'ticker_interval'.",
-                   caplog)
+    exitdf = strategy.advise_exit(result, metadata=metadata)
+    assert isinstance(exitdf, DataFrame)
+    assert 'exit_long' in exitdf
 
 
-def test_strategy_interface_versioning(result, monkeypatch, default_conf):
+def test_strategy_interface_versioning(result, default_conf):
     default_conf.update({'strategy': 'StrategyTestV2'})
     strategy = StrategyResolver.load_strategy(default_conf)
     metadata = {'pair': 'ETH/BTC'}
@@ -409,10 +482,13 @@ def test_strategy_interface_versioning(result, monkeypatch, default_conf):
     assert isinstance(indicator_df, DataFrame)
     assert 'adx' in indicator_df.columns
 
-    buydf = strategy.advise_buy(result, metadata=metadata)
-    assert isinstance(buydf, DataFrame)
-    assert 'buy' in buydf.columns
+    enterdf = strategy.advise_entry(result, metadata=metadata)
+    assert isinstance(enterdf, DataFrame)
 
-    selldf = strategy.advise_sell(result, metadata=metadata)
-    assert isinstance(selldf, DataFrame)
-    assert 'sell' in selldf
+    assert 'buy' not in enterdf.columns
+    assert 'enter_long' in enterdf.columns
+
+    exitdf = strategy.advise_exit(result, metadata=metadata)
+    assert isinstance(exitdf, DataFrame)
+    assert 'sell' not in exitdf
+    assert 'exit_long' in exitdf
diff --git a/tests/test_arguments.py b/tests/test_arguments.py
index fca5c6ab9..0c63f636d 100644
--- a/tests/test_arguments.py
+++ b/tests/test_arguments.py
@@ -7,6 +7,7 @@ import pytest
 
 from freqtrade.commands import Arguments
 from freqtrade.commands.cli_options import check_int_nonzero, check_int_positive
+from tests.conftest import CURRENT_TEST_STRATEGY
 
 
 # Parse common command-line-arguments. Used for all tools
@@ -111,19 +112,19 @@ def test_parse_args_strategy_path_invalid() -> None:
 
 def test_parse_args_backtesting_invalid() -> None:
     with pytest.raises(SystemExit, match=r'2'):
-        Arguments(['backtesting --ticker-interval']).get_parsed_arg()
+        Arguments(['backtesting --timeframe']).get_parsed_arg()
 
     with pytest.raises(SystemExit, match=r'2'):
-        Arguments(['backtesting --ticker-interval', 'abc']).get_parsed_arg()
+        Arguments(['backtesting --timeframe', 'abc']).get_parsed_arg()
 
 
 def test_parse_args_backtesting_custom() -> None:
     args = [
         'backtesting',
         '-c', 'test_conf.json',
-        '--ticker-interval', '1m',
+        '--timeframe', '1m',
         '--strategy-list',
-        'StrategyTestV2',
+        CURRENT_TEST_STRATEGY,
         'SampleStrategy'
     ]
     call_args = Arguments(args).get_parsed_arg()
diff --git a/tests/test_configuration.py b/tests/test_configuration.py
index 1ce45e4d5..db87c405f 100644
--- a/tests/test_configuration.py
+++ b/tests/test_configuration.py
@@ -18,12 +18,14 @@ from freqtrade.configuration.deprecated_settings import (check_conflicting_setti
                                                          process_removed_setting,
                                                          process_temporary_deprecated_settings)
 from freqtrade.configuration.environment_vars import flat_vars_to_nested_dict
-from freqtrade.configuration.load_config import load_config_file, load_file, log_config_error_range
+from freqtrade.configuration.load_config import (load_config_file, load_file, load_from_files,
+                                                 log_config_error_range)
 from freqtrade.constants import DEFAULT_DB_DRYRUN_URL, DEFAULT_DB_PROD_URL, ENV_VAR_PREFIX
 from freqtrade.enums import RunMode
 from freqtrade.exceptions import OperationalException
-from freqtrade.loggers import _set_loggers, setup_logging, setup_logging_pre
-from tests.conftest import log_has, log_has_re, patched_configuration_load_config_file
+from freqtrade.loggers import FTBufferingHandler, _set_loggers, setup_logging, setup_logging_pre
+from tests.conftest import (CURRENT_TEST_STRATEGY, log_has, log_has_re,
+                            patched_configuration_load_config_file)
 
 
 @pytest.fixture(scope="function")
@@ -159,7 +161,7 @@ def test_load_config_combine_dicts(default_conf, mocker, caplog) -> None:
 
     configsmock = MagicMock(side_effect=config_files)
     mocker.patch(
-        'freqtrade.configuration.configuration.load_config_file',
+        'freqtrade.configuration.load_config.load_config_file',
         configsmock
     )
 
@@ -190,7 +192,7 @@ def test_from_config(default_conf, mocker, caplog) -> None:
     mocker.patch('freqtrade.configuration.configuration.create_datadir', lambda c, x: x)
 
     configsmock = MagicMock(side_effect=config_files)
-    mocker.patch('freqtrade.configuration.configuration.load_config_file', configsmock)
+    mocker.patch('freqtrade.configuration.load_config.load_config_file', configsmock)
 
     validated_conf = Configuration.from_files(['test_conf.json', 'test2_conf.json'])
 
@@ -205,6 +207,33 @@ def test_from_config(default_conf, mocker, caplog) -> None:
     assert isinstance(validated_conf['user_data_dir'], Path)
 
 
+def test_from_recursive_files(testdatadir) -> None:
+    files = testdatadir / "testconfigs/testconfig.json"
+
+    conf = Configuration.from_files([files])
+
+    assert conf
+    # Exchange comes from "the first config"
+    assert conf['exchange']
+    # Pricing comes from the 2nd config
+    assert conf['entry_pricing']
+    assert conf['entry_pricing']['price_side'] == "same"
+    assert conf['exit_pricing']
+    # The other key comes from pricing2, which is imported by pricing.json.
+    # pricing.json is a level higher, therefore wins.
+    assert conf['exit_pricing']['price_side'] == "same"
+
+    assert len(conf['config_files']) == 4
+    assert 'testconfig.json' in conf['config_files'][0]
+    assert 'test_pricing_conf.json' in conf['config_files'][1]
+    assert 'test_base_config.json' in conf['config_files'][2]
+    assert 'test_pricing2_conf.json' in conf['config_files'][3]
+
+    files = testdatadir / "testconfigs/recursive.json"
+    with pytest.raises(OperationalException, match="Config loop detected."):
+        load_from_files([files])
+
+
 def test_print_config(default_conf, mocker, caplog) -> None:
     conf1 = deepcopy(default_conf)
     # Delete non-json elements from default_conf
@@ -213,7 +242,7 @@ def test_print_config(default_conf, mocker, caplog) -> None:
 
     configsmock = MagicMock(side_effect=config_files)
     mocker.patch('freqtrade.configuration.configuration.create_datadir', lambda c, x: x)
-    mocker.patch('freqtrade.configuration.configuration.load_config_file', configsmock)
+    mocker.patch('freqtrade.configuration.configuration.load_from_files', configsmock)
 
     validated_conf = Configuration.from_files(['test_conf.json'])
 
@@ -403,7 +432,7 @@ def test_setup_configuration_without_arguments(mocker, default_conf, caplog) ->
     arglist = [
         'backtesting',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
     ]
 
     args = Arguments(arglist).get_parsed_arg()
@@ -440,10 +469,10 @@ def test_setup_configuration_with_arguments(mocker, default_conf, caplog) -> Non
     arglist = [
         'backtesting',
         '--config', 'config.json',
-        '--strategy', 'StrategyTestV2',
+        '--strategy', CURRENT_TEST_STRATEGY,
         '--datadir', '/foo/bar',
         '--userdir', "/tmp/freqtrade",
-        '--ticker-interval', '1m',
+        '--timeframe', '1m',
         '--enable-position-stacking',
         '--disable-max-market-positions',
         '--timerange', ':100',
@@ -494,10 +523,10 @@ def test_setup_configuration_with_stratlist(mocker, default_conf, caplog) -> Non
     arglist = [
         'backtesting',
         '--config', 'config.json',
-        '--ticker-interval', '1m',
+        '--timeframe', '1m',
         '--export', 'trades',
         '--strategy-list',
-        'StrategyTestV2',
+        CURRENT_TEST_STRATEGY,
         'TestStrategy'
     ]
 
@@ -686,7 +715,7 @@ def test_set_loggers_syslog():
     assert len(logger.handlers) == 3
     assert [x for x in logger.handlers if type(x) == logging.handlers.SysLogHandler]
     assert [x for x in logger.handlers if type(x) == logging.StreamHandler]
-    assert [x for x in logger.handlers if type(x) == logging.handlers.BufferingHandler]
+    assert [x for x in logger.handlers if type(x) == FTBufferingHandler]
     # setting up logging again should NOT cause the loggers to be added a second time.
     setup_logging(config)
     assert len(logger.handlers) == 3
@@ -709,7 +738,7 @@ def test_set_loggers_Filehandler(tmpdir):
     assert len(logger.handlers) == 3
     assert [x for x in logger.handlers if type(x) == logging.handlers.RotatingFileHandler]
     assert [x for x in logger.handlers if type(x) == logging.StreamHandler]
-    assert [x for x in logger.handlers if type(x) == logging.handlers.BufferingHandler]
+    assert [x for x in logger.handlers if type(x) == FTBufferingHandler]
     # setting up logging again should NOT cause the loggers to be added a second time.
     setup_logging(config)
     assert len(logger.handlers) == 3
@@ -771,15 +800,15 @@ def test_set_logfile(default_conf, mocker, tmpdir):
 
 
 def test_load_config_warn_forcebuy(default_conf, mocker, caplog) -> None:
-    default_conf['forcebuy_enable'] = True
+    default_conf['force_entry_enable'] = True
     patched_configuration_load_config_file(mocker, default_conf)
 
     args = Arguments(['trade']).get_parsed_arg()
     configuration = Configuration(args)
     validated_conf = configuration.load_config()
 
-    assert validated_conf.get('forcebuy_enable')
-    assert log_has('`forcebuy` RPC message enabled.', caplog)
+    assert validated_conf.get('force_entry_enable')
+    assert log_has('`force_entry_enable` RPC message enabled.', caplog)
 
 
 def test_validate_default_conf(default_conf) -> None:
@@ -797,8 +826,8 @@ def test_validate_max_open_trades(default_conf):
 
 def test_validate_price_side(default_conf):
     default_conf['order_types'] = {
-        "buy": "limit",
-        "sell": "limit",
+        "entry": "limit",
+        "exit": "limit",
         "stoploss": "limit",
         "stoploss_on_exchange": False,
     }
@@ -806,23 +835,23 @@ def test_validate_price_side(default_conf):
     validate_config_consistency(default_conf)
 
     conf = deepcopy(default_conf)
-    conf['order_types']['buy'] = 'market'
+    conf['order_types']['entry'] = 'market'
     with pytest.raises(OperationalException,
-                       match='Market buy orders require bid_strategy.price_side = "ask".'):
+                       match='Market entry orders require entry_pricing.price_side = "other".'):
         validate_config_consistency(conf)
 
     conf = deepcopy(default_conf)
-    conf['order_types']['sell'] = 'market'
+    conf['order_types']['exit'] = 'market'
     with pytest.raises(OperationalException,
-                       match='Market sell orders require ask_strategy.price_side = "bid".'):
+                       match='Market exit orders require exit_pricing.price_side = "other".'):
         validate_config_consistency(conf)
 
     # Validate inversed case
     conf = deepcopy(default_conf)
-    conf['order_types']['sell'] = 'market'
-    conf['order_types']['buy'] = 'market'
-    conf['ask_strategy']['price_side'] = 'bid'
-    conf['bid_strategy']['price_side'] = 'ask'
+    conf['order_types']['exit'] = 'market'
+    conf['order_types']['entry'] = 'market'
+    conf['exit_pricing']['price_side'] = 'bid'
+    conf['entry_pricing']['price_side'] = 'ask'
 
     validate_config_consistency(conf)
 
@@ -867,15 +896,15 @@ def test_validate_tsl(default_conf):
 
 def test_validate_edge2(edge_conf):
     edge_conf.update({
-        "use_sell_signal": True,
+        "use_exit_signal": True,
     })
     # Passes test
     validate_config_consistency(edge_conf)
 
     edge_conf.update({
-        "use_sell_signal": False,
+        "use_exit_signal": False,
     })
-    with pytest.raises(OperationalException, match="Edge requires `use_sell_signal` to be True, "
+    with pytest.raises(OperationalException, match="Edge requires `use_exit_signal` to be True, "
                        "otherwise no sells will happen."):
         validate_config_consistency(edge_conf)
 
@@ -925,18 +954,138 @@ def test_validate_protections(default_conf, protconf, expected):
 
 def test_validate_ask_orderbook(default_conf, caplog) -> None:
     conf = deepcopy(default_conf)
-    conf['ask_strategy']['use_order_book'] = True
-    conf['ask_strategy']['order_book_min'] = 2
-    conf['ask_strategy']['order_book_max'] = 2
+    conf['exit_pricing']['use_order_book'] = True
+    conf['exit_pricing']['order_book_min'] = 2
+    conf['exit_pricing']['order_book_max'] = 2
 
     validate_config_consistency(conf)
     assert log_has_re(r"DEPRECATED: Please use `order_book_top` instead of.*", caplog)
-    assert conf['ask_strategy']['order_book_top'] == 2
+    assert conf['exit_pricing']['order_book_top'] == 2
 
-    conf['ask_strategy']['order_book_max'] = 5
+    conf['exit_pricing']['order_book_max'] = 5
 
     with pytest.raises(OperationalException,
-                       match=r"Using order_book_max != order_book_min in ask_strategy.*"):
+                       match=r"Using order_book_max != order_book_min in exit_pricing.*"):
+        validate_config_consistency(conf)
+
+
+def test_validate_time_in_force(default_conf, caplog) -> None:
+    conf = deepcopy(default_conf)
+    conf['order_time_in_force'] = {
+        'buy': 'gtc',
+        'sell': 'gtc',
+    }
+    validate_config_consistency(conf)
+    assert log_has_re(r"DEPRECATED: Using 'buy' and 'sell' for time_in_force is.*", caplog)
+    assert conf['order_time_in_force']['entry'] == 'gtc'
+    assert conf['order_time_in_force']['exit'] == 'gtc'
+
+    conf = deepcopy(default_conf)
+    conf['order_time_in_force'] = {
+        'buy': 'gtc',
+        'sell': 'gtc',
+    }
+    conf['trading_mode'] = 'futures'
+    with pytest.raises(OperationalException,
+                       match=r"Please migrate your time_in_force settings .* 'entry' and 'exit'\."):
+        validate_config_consistency(conf)
+
+
+def test__validate_order_types(default_conf, caplog) -> None:
+    conf = deepcopy(default_conf)
+    conf['order_types'] = {
+        'buy': 'limit',
+        'sell': 'market',
+        'forcesell': 'market',
+        'forcebuy': 'limit',
+        'stoploss': 'market',
+        'stoploss_on_exchange': False,
+    }
+    validate_config_consistency(conf)
+    assert log_has_re(r"DEPRECATED: Using 'buy' and 'sell' for order_types is.*", caplog)
+    assert conf['order_types']['entry'] == 'limit'
+    assert conf['order_types']['exit'] == 'market'
+    assert conf['order_types']['force_entry'] == 'limit'
+    assert 'buy' not in conf['order_types']
+    assert 'sell' not in conf['order_types']
+    assert 'forcebuy' not in conf['order_types']
+    assert 'forcesell' not in conf['order_types']
+
+    conf = deepcopy(default_conf)
+    conf['order_types'] = {
+        'buy': 'limit',
+        'sell': 'market',
+        'forcesell': 'market',
+        'forcebuy': 'limit',
+        'stoploss': 'market',
+        'stoploss_on_exchange': False,
+    }
+    conf['trading_mode'] = 'futures'
+    with pytest.raises(OperationalException,
+                       match=r"Please migrate your order_types settings to use the new wording\."):
+        validate_config_consistency(conf)
+
+
+def test__validate_unfilledtimeout(default_conf, caplog) -> None:
+    conf = deepcopy(default_conf)
+    conf['unfilledtimeout'] = {
+        'buy': 30,
+        'sell': 35,
+    }
+    validate_config_consistency(conf)
+    assert log_has_re(r"DEPRECATED: Using 'buy' and 'sell' for unfilledtimeout is.*", caplog)
+    assert conf['unfilledtimeout']['entry'] == 30
+    assert conf['unfilledtimeout']['exit'] == 35
+    assert 'buy' not in conf['unfilledtimeout']
+    assert 'sell' not in conf['unfilledtimeout']
+
+    conf = deepcopy(default_conf)
+    conf['unfilledtimeout'] = {
+        'buy': 30,
+        'sell': 35,
+    }
+    conf['trading_mode'] = 'futures'
+    with pytest.raises(
+            OperationalException,
+            match=r"Please migrate your unfilledtimeout settings to use the new wording\."):
+        validate_config_consistency(conf)
+
+
+def test__validate_pricing_rules(default_conf, caplog) -> None:
+    def_conf = deepcopy(default_conf)
+    del def_conf['entry_pricing']
+    del def_conf['exit_pricing']
+
+    def_conf['ask_strategy'] = {
+        'price_side': 'ask',
+        'use_order_book': True,
+        'bid_last_balance': 0.5
+    }
+    def_conf['bid_strategy'] = {
+        'price_side': 'bid',
+        'use_order_book': False,
+        'ask_last_balance': 0.7
+    }
+    conf = deepcopy(def_conf)
+
+    validate_config_consistency(conf)
+    assert log_has_re(
+        r"DEPRECATED: Using 'ask_strategy' and 'bid_strategy' is.*", caplog)
+    assert conf['exit_pricing']['price_side'] == 'ask'
+    assert conf['exit_pricing']['use_order_book'] is True
+    assert conf['exit_pricing']['price_last_balance'] == 0.5
+    assert conf['entry_pricing']['price_side'] == 'bid'
+    assert conf['entry_pricing']['use_order_book'] is False
+    assert conf['entry_pricing']['price_last_balance'] == 0.7
+    assert 'ask_strategy' not in conf
+    assert 'bid_strategy' not in conf
+
+    conf = deepcopy(def_conf)
+
+    conf['trading_mode'] = 'futures'
+    with pytest.raises(
+            OperationalException,
+            match=r"Please migrate your pricing settings to use the new wording\."):
         validate_config_consistency(conf)
 
 
@@ -1117,14 +1266,8 @@ def test_pairlist_resolving_fallback(mocker):
 
 
 @pytest.mark.parametrize("setting", [
-    ("ask_strategy", "use_sell_signal", True,
-     None, "use_sell_signal", False),
-    ("ask_strategy", "sell_profit_only", True,
-     None, "sell_profit_only", False),
-    ("ask_strategy", "sell_profit_offset", 0.1,
-     None, "sell_profit_offset", 0.01),
-    ("ask_strategy", "ignore_roi_if_buy_signal", True,
-     None, "ignore_roi_if_buy_signal", False),
+    ("webhook", "webhookbuy", 'testWEbhook',
+     "webhook", "webhookentry", 'testWEbhook'),
     ("ask_strategy", "ignore_buying_expired_candle_after", 5,
      None, "ignore_buying_expired_candle_after", 6),
 ])
@@ -1257,11 +1400,14 @@ def test_process_deprecated_setting(mocker, default_conf, caplog):
     # The value of the new setting shall have been set to the
     # value of the deprecated one
     assert default_conf['sectionA']['new_setting'] == 'valB'
+    # Old setting is removed
+    assert 'deprecated_setting' not in default_conf['sectionB']
 
     caplog.clear()
 
     # Delete new setting (deprecated exists)
     del default_conf['sectionA']['new_setting']
+    default_conf['sectionB']['deprecated_setting'] = 'valB'
     process_deprecated_setting(default_conf,
                                'sectionB', 'deprecated_setting',
                                'sectionA', 'new_setting')
@@ -1275,7 +1421,7 @@ def test_process_deprecated_setting(mocker, default_conf, caplog):
     # Assign new setting
     default_conf['sectionA']['new_setting'] = 'valA'
     # Delete deprecated setting
-    del default_conf['sectionB']['deprecated_setting']
+    default_conf['sectionB'].pop('deprecated_setting', None)
     process_deprecated_setting(default_conf,
                                'sectionB', 'deprecated_setting',
                                'sectionA', 'new_setting')
@@ -1320,22 +1466,14 @@ def test_process_removed_setting(mocker, default_conf, caplog):
 def test_process_deprecated_ticker_interval(default_conf, caplog):
     message = "DEPRECATED: Please use 'timeframe' instead of 'ticker_interval."
     config = deepcopy(default_conf)
+
     process_temporary_deprecated_settings(config)
     assert not log_has(message, caplog)
 
     del config['timeframe']
     config['ticker_interval'] = '15m'
-    process_temporary_deprecated_settings(config)
-    assert log_has(message, caplog)
-    assert config['ticker_interval'] == '15m'
-
-    config = deepcopy(default_conf)
-    # Have both timeframe and ticker interval in config
-    # Can also happen when using ticker_interval in configuration, and --timeframe as cli argument
-    config['timeframe'] = '5m'
-    config['ticker_interval'] = '4h'
     with pytest.raises(OperationalException,
-                       match=r"Both 'timeframe' and 'ticker_interval' detected."):
+                       match=r"DEPRECATED: 'ticker_interval' detected. Please use.*"):
         process_temporary_deprecated_settings(config)
 
 
@@ -1356,14 +1494,15 @@ def test_flat_vars_to_nested_dict(caplog):
         'FREQTRADE__EXCHANGE__SOME_SETTING': 'true',
         'FREQTRADE__EXCHANGE__SOME_FALSE_SETTING': 'false',
         'FREQTRADE__EXCHANGE__CONFIG__whatever': 'sometime',
-        'FREQTRADE__ASK_STRATEGY__PRICE_SIDE': 'bid',
-        'FREQTRADE__ASK_STRATEGY__cccc': '500',
+        'FREQTRADE__EXIT_PRICING__PRICE_SIDE': 'bid',
+        'FREQTRADE__EXIT_PRICING__cccc': '500',
         'FREQTRADE__STAKE_AMOUNT': '200.05',
+        'FREQTRADE__TELEGRAM__CHAT_ID': '2151',
         'NOT_RELEVANT': '200.0',  # Will be ignored
     }
     expected = {
         'stake_amount': 200.05,
-        'ask_strategy': {
+        'exit_pricing': {
             'price_side': 'bid',
             'cccc': 500,
         },
@@ -1373,6 +1512,9 @@ def test_flat_vars_to_nested_dict(caplog):
             },
             'some_setting': True,
             'some_false_setting': False,
+        },
+        'telegram': {
+            'chat_id': '2151'
         }
     }
     res = flat_vars_to_nested_dict(test_args, ENV_VAR_PREFIX)
diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py
index 3a9af8c82..3737c7c05 100644
--- a/tests/test_freqtradebot.py
+++ b/tests/test_freqtradebot.py
@@ -5,27 +5,29 @@ import logging
 import time
 from copy import deepcopy
 from math import isclose
-from unittest.mock import ANY, MagicMock, PropertyMock
+from typing import List
+from unittest.mock import ANY, MagicMock, PropertyMock, patch
 
 import arrow
 import pytest
+from pandas import DataFrame
 
 from freqtrade.constants import CANCEL_REASON, MATH_CLOSE_PREC, UNLIMITED_STAKE_AMOUNT
-from freqtrade.enums import RPCMessageType, RunMode, SellType, State
+from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, RPCMessageType, RunMode,
+                             SignalDirection, State)
 from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError,
                                   InvalidOrderException, OperationalException, PricingError,
                                   TemporaryError)
 from freqtrade.freqtradebot import FreqtradeBot
 from freqtrade.persistence import Order, PairLocks, Trade
 from freqtrade.persistence.models import PairLock
-from freqtrade.strategy.interface import SellCheckTuple
 from freqtrade.worker import Worker
 from tests.conftest import (create_mock_trades, get_patched_freqtradebot, get_patched_worker,
                             log_has, log_has_re, patch_edge, patch_exchange, patch_get_signal,
                             patch_wallet, patch_whitelist)
-from tests.conftest_trades import (MOCK_TRADE_COUNT, mock_order_1, mock_order_2, mock_order_2_sell,
-                                   mock_order_3, mock_order_3_sell, mock_order_4,
-                                   mock_order_5_stoploss, mock_order_6_sell)
+from tests.conftest_trades import (MOCK_TRADE_COUNT, entry_side, exit_side, mock_order_1,
+                                   mock_order_2, mock_order_2_sell, mock_order_3, mock_order_3_sell,
+                                   mock_order_4, mock_order_5_stoploss, mock_order_6_sell)
 
 
 def patch_RPCManager(mocker) -> MagicMock:
@@ -41,33 +43,34 @@ def patch_RPCManager(mocker) -> MagicMock:
 
 # Unit tests
 
-def test_freqtradebot_state(mocker, default_conf, markets) -> None:
+
+def test_freqtradebot_state(mocker, default_conf_usdt, markets) -> None:
     mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     assert freqtrade.state is State.RUNNING
 
-    default_conf.pop('initial_state')
-    freqtrade = FreqtradeBot(default_conf)
+    default_conf_usdt.pop('initial_state')
+    freqtrade = FreqtradeBot(default_conf_usdt)
     assert freqtrade.state is State.STOPPED
 
 
-def test_process_stopped(mocker, default_conf) -> None:
+def test_process_stopped(mocker, default_conf_usdt) -> None:
 
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     coo_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cancel_all_open_orders')
     freqtrade.process_stopped()
     assert coo_mock.call_count == 0
 
-    default_conf['cancel_open_orders_on_exit'] = True
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    default_conf_usdt['cancel_open_orders_on_exit'] = True
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     freqtrade.process_stopped()
     assert coo_mock.call_count == 1
 
 
-def test_bot_cleanup(mocker, default_conf, caplog) -> None:
+def test_bot_cleanup(mocker, default_conf_usdt, caplog) -> None:
     mock_cleanup = mocker.patch('freqtrade.freqtradebot.cleanup_db')
     coo_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cancel_all_open_orders')
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     freqtrade.cleanup()
     assert log_has('Cleaning up modules ...', caplog)
     assert mock_cleanup.call_count == 1
@@ -82,18 +85,18 @@ def test_bot_cleanup(mocker, default_conf, caplog) -> None:
     RunMode.DRY_RUN,
     RunMode.LIVE
 ])
-def test_order_dict(default_conf, mocker, runmode, caplog) -> None:
+def test_order_dict(default_conf_usdt, mocker, runmode, caplog) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    conf = default_conf.copy()
+    conf = default_conf_usdt.copy()
     conf['runmode'] = runmode
     conf['order_types'] = {
-        'buy': 'market',
-        'sell': 'limit',
+        'entry': 'market',
+        'exit': 'limit',
         'stoploss': 'limit',
         'stoploss_on_exchange': True,
     }
-    conf['bid_strategy']['price_side'] = 'ask'
+    conf['entry_pricing']['price_side'] = 'ask'
 
     freqtrade = FreqtradeBot(conf)
     if runmode == RunMode.LIVE:
@@ -102,11 +105,11 @@ def test_order_dict(default_conf, mocker, runmode, caplog) -> None:
 
     caplog.clear()
     # is left untouched
-    conf = default_conf.copy()
+    conf = default_conf_usdt.copy()
     conf['runmode'] = runmode
     conf['order_types'] = {
-        'buy': 'market',
-        'sell': 'limit',
+        'entry': 'market',
+        'exit': 'limit',
         'stoploss': 'limit',
         'stoploss_on_exchange': False,
     }
@@ -115,65 +118,63 @@ def test_order_dict(default_conf, mocker, runmode, caplog) -> None:
     assert not log_has_re(".*stoploss_on_exchange .* dry-run", caplog)
 
 
-def test_get_trade_stake_amount(default_conf, ticker, mocker) -> None:
+def test_get_trade_stake_amount(default_conf_usdt, mocker) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
-    result = freqtrade.wallets.get_trade_stake_amount('ETH/BTC')
-    assert result == default_conf['stake_amount']
+    result = freqtrade.wallets.get_trade_stake_amount('ETH/USDT')
+    assert result == default_conf_usdt['stake_amount']
 
 
 @pytest.mark.parametrize("amend_last,wallet,max_open,lsamr,expected", [
-                        (False, 0.002, 2, 0.5, [0.001, None]),
-                        (True, 0.002, 2, 0.5, [0.001, 0.00098]),
-                        (False, 0.003, 3, 0.5, [0.001, 0.001, None]),
-                        (True, 0.003, 3, 0.5, [0.001, 0.001, 0.00097]),
-                        (False, 0.0022, 3, 0.5, [0.001, 0.001, None]),
-                        (True, 0.0022, 3, 0.5, [0.001, 0.001, 0.0]),
-                        (True, 0.0027, 3, 0.5, [0.001, 0.001, 0.000673]),
-                        (True, 0.0022, 3, 1, [0.001, 0.001, 0.0]),
+                        (False, 120, 2, 0.5, [60, None]),
+                        (True, 120, 2, 0.5, [60, 58.8]),
+                        (False, 180, 3, 0.5, [60, 60, None]),
+                        (True, 180, 3, 0.5, [60, 60, 58.2]),
+                        (False, 122, 3, 0.5, [60, 60, None]),
+                        (True, 122, 3, 0.5, [60, 60, 0.0]),
+                        (True, 167, 3, 0.5, [60, 60, 45.33]),
+                        (True, 122, 3, 1, [60, 60, 0.0]),
 ])
-def test_check_available_stake_amount(default_conf, ticker, mocker, fee, limit_buy_order_open,
-                                      amend_last, wallet, max_open, lsamr, expected) -> None:
+def test_check_available_stake_amount(
+    default_conf_usdt, ticker_usdt, mocker, fee, limit_buy_order_usdt_open,
+    amend_last, wallet, max_open, lsamr, expected
+) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value=limit_buy_order_open),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value=limit_buy_order_usdt_open),
         get_fee=fee
     )
-    default_conf['dry_run_wallet'] = wallet
+    default_conf_usdt['dry_run_wallet'] = wallet
 
-    default_conf['amend_last_stake_amount'] = amend_last
-    default_conf['last_stake_amount_min_ratio'] = lsamr
+    default_conf_usdt['amend_last_stake_amount'] = amend_last
+    default_conf_usdt['last_stake_amount_min_ratio'] = lsamr
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
     for i in range(0, max_open):
 
         if expected[i] is not None:
-            limit_buy_order_open['id'] = str(i)
-            result = freqtrade.wallets.get_trade_stake_amount('ETH/BTC')
+            limit_buy_order_usdt_open['id'] = str(i)
+            result = freqtrade.wallets.get_trade_stake_amount('ETH/USDT')
             assert pytest.approx(result) == expected[i]
-            freqtrade.execute_entry('ETH/BTC', result)
+            freqtrade.execute_entry('ETH/USDT', result)
         else:
             with pytest.raises(DependencyException):
-                freqtrade.wallets.get_trade_stake_amount('ETH/BTC')
+                freqtrade.wallets.get_trade_stake_amount('ETH/USDT')
 
 
 def test_edge_called_in_process(mocker, edge_conf) -> None:
     patch_RPCManager(mocker)
     patch_edge(mocker)
 
-    def _refresh_whitelist(list):
-        return ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC']
-
     patch_exchange(mocker)
     freqtrade = FreqtradeBot(edge_conf)
-    freqtrade.pairlists._validate_whitelist = _refresh_whitelist
     patch_get_signal(freqtrade)
     freqtrade.process()
     assert freqtrade.active_pair_whitelist == ['NEO/BTC', 'LTC/BTC']
@@ -193,12 +194,10 @@ def test_edge_overrides_stake_amount(mocker, edge_conf) -> None:
 
 
 @pytest.mark.parametrize('buy_price_mult,ignore_strat_sl', [
-    # Override stoploss
-    (0.79, False),
-    # Override strategy stoploss
-    (0.85, True)
+    (0.79, False),   # Override stoploss
+    (0.85, True),    # Override strategy stoploss
 ])
-def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker,
+def test_edge_overrides_stoploss(limit_order, fee, caplog, mocker,
                                  buy_price_mult, ignore_strat_sl, edge_conf) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
@@ -209,53 +208,56 @@ def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker,
     # Thus, if price falls 21%, stoploss should be triggered
     #
     # mocking the ticker: price is falling ...
-    buy_price = limit_buy_order['price']
+    enter_price = limit_order['buy']['price']
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': buy_price * buy_price_mult,
-            'ask': buy_price * buy_price_mult,
-            'last': buy_price * buy_price_mult,
+            'bid': enter_price * buy_price_mult,
+            'ask': enter_price * buy_price_mult,
+            'last': enter_price * buy_price_mult,
         }),
         get_fee=fee,
     )
     #############################################
 
-    # Create a trade with "limit_buy_order" price
+    # Create a trade with "limit_buy_order_usdt" price
     freqtrade = FreqtradeBot(edge_conf)
     freqtrade.active_pair_whitelist = ['NEO/BTC']
     patch_get_signal(freqtrade)
     freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
     freqtrade.enter_positions()
     trade = Trade.query.first()
-    trade.update(limit_buy_order)
+    caplog.clear()
+    oobj = Order.parse_from_ccxt_object(limit_order['buy'], 'ADA/USDT', 'buy')
+    trade.update_trade(oobj)
     #############################################
 
     # stoploss shoud be hit
     assert freqtrade.handle_trade(trade) is not ignore_strat_sl
     if not ignore_strat_sl:
-        assert log_has('Executing Sell for NEO/BTC. Reason: stop_loss', caplog)
-        assert trade.sell_reason == SellType.STOP_LOSS.value
+        assert log_has_re('Exit for NEO/BTC detected. Reason: stop_loss.*', caplog)
+        assert trade.exit_reason == ExitType.STOP_LOSS.value
+        # Test compatibility ...
+        assert trade.sell_reason == ExitType.STOP_LOSS.value
 
 
-def test_total_open_trades_stakes(mocker, default_conf, ticker, fee) -> None:
+def test_total_open_trades_stakes(mocker, default_conf_usdt, ticker_usdt, fee) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    default_conf['stake_amount'] = 0.00098751
-    default_conf['max_open_trades'] = 2
+    default_conf_usdt['max_open_trades'] = 2
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         _is_dry_limit_order_filled=MagicMock(return_value=False),
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
     freqtrade.enter_positions()
     trade = Trade.query.first()
 
     assert trade is not None
-    assert trade.stake_amount == 0.00098751
+    assert trade.stake_amount == 60.0
     assert trade.is_open
     assert trade.open_date is not None
 
@@ -263,118 +265,126 @@ def test_total_open_trades_stakes(mocker, default_conf, ticker, fee) -> None:
     trade = Trade.query.order_by(Trade.id.desc()).first()
 
     assert trade is not None
-    assert trade.stake_amount == 0.00098751
+    assert trade.stake_amount == 60.0
     assert trade.is_open
     assert trade.open_date is not None
 
-    assert Trade.total_open_trades_stakes() == 1.97502e-03
+    assert Trade.total_open_trades_stakes() == 120.0
 
 
-def test_create_trade(default_conf, ticker, limit_buy_order, fee, mocker) -> None:
+@pytest.mark.parametrize("is_short,open_rate", [
+    (False, 2.0),
+    (True, 2.2)
+])
+def test_create_trade(default_conf_usdt, ticker_usdt, limit_order,
+                      fee, mocker, is_short, open_rate) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         _is_dry_limit_order_filled=MagicMock(return_value=False),
     )
 
     # Save state of current whitelist
-    whitelist = deepcopy(default_conf['exchange']['pair_whitelist'])
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.create_trade('ETH/BTC')
+    whitelist = deepcopy(default_conf_usdt['exchange']['pair_whitelist'])
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
+    freqtrade.create_trade('ETH/USDT')
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade is not None
-    assert trade.stake_amount == 0.001
+    assert pytest.approx(trade.stake_amount) == 60.0
     assert trade.is_open
     assert trade.open_date is not None
     assert trade.exchange == 'binance'
 
     # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(
+        limit_order[entry_side(is_short)], 'ADA/USDT', entry_side(is_short))
+    trade.update_trade(oobj)
 
-    assert trade.open_rate == 0.00001099
-    assert trade.amount == 90.99181073
+    assert trade.open_rate == open_rate
+    assert trade.amount == 30.0
 
-    assert whitelist == default_conf['exchange']['pair_whitelist']
+    assert whitelist == default_conf_usdt['exchange']['pair_whitelist']
 
 
-def test_create_trade_no_stake_amount(default_conf, ticker, limit_buy_order,
-                                      fee, mocker) -> None:
+def test_create_trade_no_stake_amount(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    patch_wallet(mocker, free=default_conf['stake_amount'] * 0.5)
+    patch_wallet(mocker, free=default_conf_usdt['stake_amount'] * 0.5)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
 
     with pytest.raises(DependencyException, match=r'.*stake amount.*'):
-        freqtrade.create_trade('ETH/BTC')
+        freqtrade.create_trade('ETH/USDT')
 
 
+@pytest.mark.parametrize("is_short", [False, True])
 @pytest.mark.parametrize('stake_amount,create,amount_enough,max_open_trades', [
-    (0.0005, True, True, 99),
-    (0.000000005, True, False, 99),
+    (5.0, True, True, 99),
+    (0.049, True, False, 99),  # Amount will be adjusted to min - which is 0.051
     (0, False, True, 99),
     (UNLIMITED_STAKE_AMOUNT, False, True, 0),
 ])
 def test_create_trade_minimal_amount(
-    default_conf, ticker, limit_buy_order_open, fee, mocker,
-    stake_amount, create, amount_enough, max_open_trades, caplog
+    default_conf_usdt, ticker_usdt, limit_order_open, fee, mocker,
+    stake_amount, create, amount_enough, max_open_trades, caplog, is_short
 ) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    buy_mock = MagicMock(return_value=limit_buy_order_open)
+    enter_mock = MagicMock(return_value=limit_order_open[entry_side(is_short)])
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=buy_mock,
+        fetch_ticker=ticker_usdt,
+        create_order=enter_mock,
         get_fee=fee,
     )
-    default_conf['max_open_trades'] = max_open_trades
-    freqtrade = FreqtradeBot(default_conf)
+    default_conf_usdt['max_open_trades'] = max_open_trades
+    freqtrade = FreqtradeBot(default_conf_usdt)
     freqtrade.config['stake_amount'] = stake_amount
-    patch_get_signal(freqtrade)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     if create:
-        assert freqtrade.create_trade('ETH/BTC')
+        assert freqtrade.create_trade('ETH/USDT')
         if amount_enough:
-            rate, amount = buy_mock.call_args[1]['rate'], buy_mock.call_args[1]['amount']
-            assert rate * amount <= default_conf['stake_amount']
+            rate, amount = enter_mock.call_args[1]['rate'], enter_mock.call_args[1]['amount']
+            assert rate * amount <= default_conf_usdt['stake_amount']
         else:
             assert log_has_re(
                 r"Stake amount for pair .* is too small.*",
                 caplog
             )
     else:
-        assert not freqtrade.create_trade('ETH/BTC')
+        assert not freqtrade.create_trade('ETH/USDT')
         if not max_open_trades:
-            assert freqtrade.wallets.get_trade_stake_amount('ETH/BTC', freqtrade.edge) == 0
+            assert freqtrade.wallets.get_trade_stake_amount('ETH/USDT', freqtrade.edge) == 0
 
 
 @pytest.mark.parametrize('whitelist,positions', [
-    (["ETH/BTC"], 1),  # No pairs left
+    (["ETH/USDT"], 1),  # No pairs left
     ([], 0),  # No pairs in whitelist
 ])
-def test_enter_positions_no_pairs_left(default_conf, ticker, limit_buy_order_open, fee,
-                                       whitelist, positions, mocker, caplog) -> None:
+def test_enter_positions_no_pairs_left(default_conf_usdt, ticker_usdt, limit_buy_order_usdt_open,
+                                       fee, whitelist, positions, mocker, caplog) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value=limit_buy_order_open),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value=limit_buy_order_usdt_open),
         get_fee=fee,
     )
-    default_conf['exchange']['pair_whitelist'] = whitelist
-    freqtrade = FreqtradeBot(default_conf)
+    default_conf_usdt['exchange']['pair_whitelist'] = whitelist
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
 
     n = freqtrade.enter_positions()
@@ -390,17 +400,17 @@ def test_enter_positions_no_pairs_left(default_conf, ticker, limit_buy_order_ope
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_enter_positions_global_pairlock(default_conf, ticker, limit_buy_order, fee,
+def test_enter_positions_global_pairlock(default_conf_usdt, ticker_usdt, limit_buy_order_usdt, fee,
                                          mocker, caplog) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value={'id': limit_buy_order['id']}),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value={'id': limit_buy_order_usdt['id']}),
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
     n = freqtrade.enter_positions()
     message = r"Global pairlock active until.* Not creating new trades."
@@ -416,8 +426,9 @@ def test_enter_positions_global_pairlock(default_conf, ticker, limit_buy_order,
     assert log_has_re(message, caplog)
 
 
-def test_handle_protections(mocker, default_conf, fee):
-    default_conf['protections'] = [
+@pytest.mark.parametrize('is_short', [False, True])
+def test_handle_protections(mocker, default_conf_usdt, fee, is_short):
+    default_conf_usdt['protections'] = [
         {"method": "CooldownPeriod", "stop_duration": 60},
         {
             "method": "StoplossGuard",
@@ -428,10 +439,10 @@ def test_handle_protections(mocker, default_conf, fee):
         }
     ]
 
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     freqtrade.protections._protection_handlers[1].global_stop = MagicMock(
         return_value=(True, arrow.utcnow().shift(hours=1).datetime, "asdf"))
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short)
     freqtrade.handle_protections('ETC/BTC')
     send_msg_mock = freqtrade.rpc.send_msg
     assert send_msg_mock.call_count == 2
@@ -439,8 +450,8 @@ def test_handle_protections(mocker, default_conf, fee):
     assert send_msg_mock.call_args_list[1][0][0]['type'] == RPCMessageType.PROTECTION_TRIGGER_GLOBAL
 
 
-def test_create_trade_no_signal(default_conf, fee, mocker) -> None:
-    default_conf['dry_run'] = True
+def test_create_trade_no_signal(default_conf_usdt, fee, mocker) -> None:
+    default_conf_usdt['dry_run'] = True
 
     patch_RPCManager(mocker)
     patch_exchange(mocker)
@@ -448,32 +459,34 @@ def test_create_trade_no_signal(default_conf, fee, mocker) -> None:
         'freqtrade.exchange.Exchange',
         get_fee=fee,
     )
-    default_conf['stake_amount'] = 10
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade, value=(False, False, None))
+    default_conf_usdt['stake_amount'] = 10
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_long=False, exit_long=False)
 
     Trade.query = MagicMock()
     Trade.query.filter = MagicMock()
-    assert not freqtrade.create_trade('ETH/BTC')
+    assert not freqtrade.create_trade('ETH/USDT')
 
 
 @pytest.mark.parametrize("max_open", range(0, 5))
 @pytest.mark.parametrize("tradable_balance_ratio,modifier", [(1.0, 1), (0.99, 0.8), (0.5, 0.5)])
-def test_create_trades_multiple_trades(default_conf, ticker, fee, mocker, limit_buy_order_open,
-                                       max_open, tradable_balance_ratio, modifier) -> None:
+def test_create_trades_multiple_trades(
+    default_conf_usdt, ticker_usdt, fee, mocker, limit_buy_order_usdt_open,
+    max_open, tradable_balance_ratio, modifier
+) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    default_conf['max_open_trades'] = max_open
-    default_conf['tradable_balance_ratio'] = tradable_balance_ratio
-    default_conf['dry_run_wallet'] = 0.001 * max_open
+    default_conf_usdt['max_open_trades'] = max_open
+    default_conf_usdt['tradable_balance_ratio'] = tradable_balance_ratio
+    default_conf_usdt['dry_run_wallet'] = 60.0 * max_open
 
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value=limit_buy_order_open),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value=limit_buy_order_usdt_open),
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
 
     n = freqtrade.enter_positions()
@@ -484,48 +497,52 @@ def test_create_trades_multiple_trades(default_conf, ticker, fee, mocker, limit_
     assert len(trades) == max(int(max_open * modifier), 0)
 
 
-def test_create_trades_preopen(default_conf, ticker, fee, mocker, limit_buy_order_open) -> None:
+def test_create_trades_preopen(default_conf_usdt, ticker_usdt, fee, mocker,
+                               limit_buy_order_usdt_open) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    default_conf['max_open_trades'] = 4
+    default_conf_usdt['max_open_trades'] = 4
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value=limit_buy_order_open),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value=limit_buy_order_usdt_open),
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
 
     # Create 2 existing trades
-    freqtrade.execute_entry('ETH/BTC', default_conf['stake_amount'])
-    freqtrade.execute_entry('NEO/BTC', default_conf['stake_amount'])
+    freqtrade.execute_entry('ETH/USDT', default_conf_usdt['stake_amount'])
+    freqtrade.execute_entry('NEO/BTC', default_conf_usdt['stake_amount'])
 
     assert len(Trade.get_open_trades()) == 2
     # Change order_id for new orders
-    limit_buy_order_open['id'] = '123444'
+    limit_buy_order_usdt_open['id'] = '123444'
 
     # Create 2 new trades using create_trades
-    assert freqtrade.create_trade('ETH/BTC')
+    assert freqtrade.create_trade('ETH/USDT')
     assert freqtrade.create_trade('NEO/BTC')
 
     trades = Trade.get_open_trades()
     assert len(trades) == 4
 
 
-def test_process_trade_creation(default_conf, ticker, limit_buy_order, limit_buy_order_open,
-                                fee, mocker, caplog) -> None:
+@pytest.mark.parametrize('is_short', [False, True])
+def test_process_trade_creation(default_conf_usdt, ticker_usdt, limit_order, limit_order_open,
+                                is_short, fee, mocker, caplog
+                                ) -> None:
+    ticker_side = 'ask' if is_short else 'bid'
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value=limit_buy_order_open),
-        fetch_order=MagicMock(return_value=limit_buy_order),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value=limit_order_open[entry_side(is_short)]),
+        fetch_order=MagicMock(return_value=limit_order[entry_side(is_short)]),
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     trades = Trade.query.filter(Trade.is_open.is_(True)).all()
     assert not trades
@@ -536,45 +553,46 @@ def test_process_trade_creation(default_conf, ticker, limit_buy_order, limit_buy
     assert len(trades) == 1
     trade = trades[0]
     assert trade is not None
-    assert trade.stake_amount == default_conf['stake_amount']
+    assert pytest.approx(trade.stake_amount) == default_conf_usdt['stake_amount']
     assert trade.is_open
     assert trade.open_date is not None
     assert trade.exchange == 'binance'
-    assert trade.open_rate == 0.00001098
-    assert trade.amount == 91.07468123
+    assert trade.open_rate == ticker_usdt.return_value[ticker_side]
+    assert isclose(trade.amount, 60 / ticker_usdt.return_value[ticker_side])
 
     assert log_has(
-        'Buy signal found: about create a new trade for ETH/BTC with stake_amount: 0.001 ...',
+        f'{"Short" if is_short else "Long"} signal found: about create a new trade for ETH/USDT '
+        'with stake_amount: 60.0 ...',
         caplog
     )
 
 
-def test_process_exchange_failures(default_conf, ticker, mocker) -> None:
+def test_process_exchange_failures(default_conf_usdt, ticker_usdt, mocker) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         create_order=MagicMock(side_effect=TemporaryError)
     )
     sleep_mock = mocker.patch('time.sleep', side_effect=lambda _: None)
 
-    worker = Worker(args=None, config=default_conf)
+    worker = Worker(args=None, config=default_conf_usdt)
     patch_get_signal(worker.freqtrade)
 
     worker._process_running()
     assert sleep_mock.has_calls()
 
 
-def test_process_operational_exception(default_conf, ticker, mocker) -> None:
+def test_process_operational_exception(default_conf_usdt, ticker_usdt, mocker) -> None:
     msg_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         create_order=MagicMock(side_effect=OperationalException)
     )
-    worker = Worker(args=None, config=default_conf)
+    worker = Worker(args=None, config=default_conf_usdt)
     patch_get_signal(worker.freqtrade)
 
     assert worker.freqtrade.state == State.RUNNING
@@ -584,17 +602,18 @@ def test_process_operational_exception(default_conf, ticker, mocker) -> None:
     assert 'OperationalException' in msg_mock.call_args_list[-1][0][0]['status']
 
 
-def test_process_trade_handling(default_conf, ticker, limit_buy_order_open, fee, mocker) -> None:
+def test_process_trade_handling(default_conf_usdt, ticker_usdt, limit_buy_order_usdt_open, fee,
+                                mocker) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value=limit_buy_order_open),
-        fetch_order=MagicMock(return_value=limit_buy_order_open),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value=limit_buy_order_usdt_open),
+        fetch_order=MagicMock(return_value=limit_buy_order_usdt_open),
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
 
     trades = Trade.query.filter(Trade.is_open.is_(True)).all()
@@ -609,23 +628,23 @@ def test_process_trade_handling(default_conf, ticker, limit_buy_order_open, fee,
     assert len(trades) == 1
 
 
-def test_process_trade_no_whitelist_pair(default_conf, ticker, limit_buy_order,
+def test_process_trade_no_whitelist_pair(default_conf_usdt, ticker_usdt, limit_buy_order_usdt,
                                          fee, mocker) -> None:
     """ Test process with trade not in pair list """
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value={'id': limit_buy_order['id']}),
-        fetch_order=MagicMock(return_value=limit_buy_order),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value={'id': limit_buy_order_usdt['id']}),
+        fetch_order=MagicMock(return_value=limit_buy_order_usdt),
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
     pair = 'BLK/BTC'
     # Ensure the pair is not in the whitelist!
-    assert pair not in default_conf['exchange']['pair_whitelist']
+    assert pair not in default_conf_usdt['exchange']['pair_whitelist']
 
     # create open trade not in whitelist
     Trade.query.session.add(Trade(
@@ -639,7 +658,7 @@ def test_process_trade_no_whitelist_pair(default_conf, ticker, limit_buy_order,
         exchange='binance',
     ))
     Trade.query.session.add(Trade(
-        pair='ETH/BTC',
+        pair='ETH/USDT',
         stake_amount=0.001,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
@@ -656,181 +675,249 @@ def test_process_trade_no_whitelist_pair(default_conf, ticker, limit_buy_order,
     assert len(freqtrade.active_pair_whitelist) == len(set(freqtrade.active_pair_whitelist))
 
 
-def test_process_informative_pairs_added(default_conf, ticker, mocker) -> None:
+def test_process_informative_pairs_added(default_conf_usdt, ticker_usdt, mocker) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
 
-    def _refresh_whitelist(list):
-        return ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC']
-
     refresh_mock = MagicMock()
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         create_order=MagicMock(side_effect=TemporaryError),
         refresh_latest_ohlcv=refresh_mock,
     )
-    inf_pairs = MagicMock(return_value=[("BTC/ETH", '1m'), ("ETH/USDT", "1h")])
-    mocker.patch(
-        'freqtrade.strategy.interface.IStrategy.get_signal',
-        return_value=(False, False, '')
+    inf_pairs = MagicMock(return_value=[
+        ("BTC/ETH", '1m', CandleType.SPOT),
+        ("ETH/USDT", "1h", CandleType.SPOT)
+    ])
+    mocker.patch.multiple(
+        'freqtrade.strategy.interface.IStrategy',
+        get_exit_signal=MagicMock(return_value=(False, False)),
+        get_entry_signal=MagicMock(return_value=(None, None))
     )
     mocker.patch('time.sleep', return_value=None)
 
-    freqtrade = FreqtradeBot(default_conf)
-    freqtrade.pairlists._validate_whitelist = _refresh_whitelist
+    freqtrade = FreqtradeBot(default_conf_usdt)
     freqtrade.strategy.informative_pairs = inf_pairs
     # patch_get_signal(freqtrade)
 
     freqtrade.process()
     assert inf_pairs.call_count == 1
     assert refresh_mock.call_count == 1
-    assert ("BTC/ETH", "1m") in refresh_mock.call_args[0][0]
-    assert ("ETH/USDT", "1h") in refresh_mock.call_args[0][0]
-    assert ("ETH/BTC", default_conf["timeframe"]) in refresh_mock.call_args[0][0]
+    assert ("BTC/ETH", "1m", CandleType.SPOT) in refresh_mock.call_args[0][0]
+    assert ("ETH/USDT", "1h", CandleType.SPOT) in refresh_mock.call_args[0][0]
+    assert ("ETH/USDT", default_conf_usdt["timeframe"],
+            CandleType.SPOT) in refresh_mock.call_args[0][0]
 
 
-def test_execute_entry(mocker, default_conf, fee, limit_buy_order, limit_buy_order_open) -> None:
+@pytest.mark.parametrize("is_short,trading_mode,exchange_name,margin_mode,liq_buffer,liq_price", [
+    (False, 'spot', 'binance', None, 0.0, None),
+    (True, 'spot', 'binance', None, 0.0, None),
+    (False, 'spot', 'gateio', None, 0.0, None),
+    (True, 'spot', 'gateio', None, 0.0, None),
+    (False, 'spot', 'okx', None, 0.0, None),
+    (True, 'spot', 'okx', None, 0.0, None),
+    (True, 'futures', 'binance', 'isolated', 0.0, 11.89108910891089),
+    (False, 'futures', 'binance', 'isolated', 0.0, 8.070707070707071),
+    (True, 'futures', 'gateio', 'isolated', 0.0, 11.87413417771621),
+    (False, 'futures', 'gateio', 'isolated', 0.0, 8.085708510208207),
+    (True, 'futures', 'binance', 'isolated', 0.05, 11.796534653465345),
+    (False, 'futures', 'binance', 'isolated', 0.05, 8.167171717171717),
+    (True, 'futures', 'gateio', 'isolated', 0.05, 11.7804274688304),
+    (False, 'futures', 'gateio', 'isolated', 0.05, 8.181423084697796),
+    (True, 'futures', 'okx', 'isolated', 0.0, 11.87413417771621),
+    (False, 'futures', 'okx', 'isolated', 0.0, 8.085708510208207),
+])
+def test_execute_entry(mocker, default_conf_usdt, fee, limit_order,
+                       limit_order_open, is_short, trading_mode,
+                       exchange_name, margin_mode, liq_buffer, liq_price) -> None:
+    """
+    exchange_name = binance, is_short = true
+        leverage = 5
+        position = 0.2 * 5
+        ((wb + cum_b) - (side_1 * position * ep1)) / ((position * mmr_b) - (side_1 * position))
+        ((2 + 0.01) - ((-1) * 1 * 10)) / ((1 * 0.01) - ((-1) * 1)) = 11.89108910891089
+
+    exchange_name = binance, is_short = false
+        ((wb + cum_b) - (side_1 * position * ep1)) / ((position * mmr_b) - (side_1 * position))
+        ((2 + 0.01) - (1 * 1 * 10)) / ((1 * 0.01) - (1 * 1)) = 8.070707070707071
+
+    exchange_name = gateio/okx, is_short = true
+        (open_rate + (wallet_balance / position)) / (1 + (mm_ratio + taker_fee_rate))
+        (10 + (2 / 1)) / (1 + (0.01 + 0.0006)) = 11.87413417771621
+
+    exchange_name = gateio/okx, is_short = false
+        (open_rate - (wallet_balance / position)) / (1 - (mm_ratio + taker_fee_rate))
+        (10 - (2 / 1)) / (1 - (0.01 + 0.0006)) = 8.085708510208207
+    """
+    # TODO: Split this test into multiple tests to improve readability
+    open_order = limit_order_open[entry_side(is_short)]
+    order = limit_order[entry_side(is_short)]
+    default_conf_usdt['trading_mode'] = trading_mode
+    default_conf_usdt['liquidation_buffer'] = liq_buffer
+    leverage = 1.0 if trading_mode == 'spot' else 5.0
+    default_conf_usdt['exchange']['name'] = exchange_name
+    if margin_mode:
+        default_conf_usdt['margin_mode'] = margin_mode
+    mocker.patch('freqtrade.exchange.Gateio.validate_ordertypes')
     patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    freqtrade = FreqtradeBot(default_conf)
+    patch_exchange(mocker, id=exchange_name)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=False)
+    freqtrade.strategy.leverage = MagicMock(return_value=leverage)
     stake_amount = 2
     bid = 0.11
-    buy_rate_mock = MagicMock(return_value=bid)
-    buy_mm = MagicMock(return_value=limit_buy_order_open)
+    enter_rate_mock = MagicMock(return_value=bid)
+    enter_mm = MagicMock(return_value=open_order)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_rate=buy_rate_mock,
+        get_rate=enter_rate_mock,
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
         }),
-        create_order=buy_mm,
+        create_order=enter_mm,
         get_min_pair_stake_amount=MagicMock(return_value=1),
+        get_max_pair_stake_amount=MagicMock(return_value=500000),
         get_fee=fee,
+        get_funding_fees=MagicMock(return_value=0),
+        name=exchange_name,
+        get_maintenance_ratio_and_amt=MagicMock(return_value=(0.01, 0.01)),
+        get_max_leverage=MagicMock(return_value=10),
     )
-    pair = 'ETH/BTC'
+    mocker.patch.multiple(
+        'freqtrade.exchange.Okx',
+        get_max_pair_stake_amount=MagicMock(return_value=500000),
+    )
+    pair = 'ETH/USDT'
 
-    assert not freqtrade.execute_entry(pair, stake_amount)
-    assert buy_rate_mock.call_count == 1
-    assert buy_mm.call_count == 0
+    assert not freqtrade.execute_entry(pair, stake_amount, is_short=is_short)
+    assert enter_rate_mock.call_count == 1
+    assert enter_mm.call_count == 0
     assert freqtrade.strategy.confirm_trade_entry.call_count == 1
-    buy_rate_mock.reset_mock()
+    enter_rate_mock.reset_mock()
 
-    limit_buy_order_open['id'] = '22'
+    open_order['id'] = '22'
     freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
     assert freqtrade.execute_entry(pair, stake_amount)
-    assert buy_rate_mock.call_count == 1
-    assert buy_mm.call_count == 1
-    call_args = buy_mm.call_args_list[0][1]
+    assert enter_rate_mock.call_count == 1
+    assert enter_mm.call_count == 1
+    call_args = enter_mm.call_args_list[0][1]
     assert call_args['pair'] == pair
     assert call_args['rate'] == bid
-    assert call_args['amount'] == round(stake_amount / bid, 8)
-    buy_rate_mock.reset_mock()
+    assert pytest.approx(call_args['amount']) == round(stake_amount / bid * leverage, 8)
+    enter_rate_mock.reset_mock()
 
     # Should create an open trade with an open order id
     # As the order is not fulfilled yet
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
     assert trade.is_open is True
     assert trade.open_order_id == '22'
 
     # Test calling with price
-    limit_buy_order_open['id'] = '33'
+    open_order['id'] = '33'
     fix_price = 0.06
-    assert freqtrade.execute_entry(pair, stake_amount, fix_price)
+    assert freqtrade.execute_entry(pair, stake_amount, fix_price, is_short=is_short)
     # Make sure get_rate wasn't called again
-    assert buy_rate_mock.call_count == 0
+    assert enter_rate_mock.call_count == 0
 
-    assert buy_mm.call_count == 2
-    call_args = buy_mm.call_args_list[1][1]
+    assert enter_mm.call_count == 2
+    call_args = enter_mm.call_args_list[1][1]
     assert call_args['pair'] == pair
     assert call_args['rate'] == fix_price
-    assert call_args['amount'] == round(stake_amount / fix_price, 8)
+    assert pytest.approx(call_args['amount']) == round(stake_amount / fix_price * leverage, 8)
 
     # In case of closed order
-    limit_buy_order['status'] = 'closed'
-    limit_buy_order['price'] = 10
-    limit_buy_order['cost'] = 100
-    limit_buy_order['id'] = '444'
+    order['status'] = 'closed'
+    order['price'] = 10
+    order['cost'] = 100
+    order['id'] = '444'
 
     mocker.patch('freqtrade.exchange.Exchange.create_order',
-                 MagicMock(return_value=limit_buy_order))
-    assert freqtrade.execute_entry(pair, stake_amount)
+                 MagicMock(return_value=order))
+    assert freqtrade.execute_entry(pair, stake_amount, is_short=is_short)
     trade = Trade.query.all()[2]
+    trade.is_short = is_short
     assert trade
     assert trade.open_order_id is None
     assert trade.open_rate == 10
-    assert trade.stake_amount == 100
+    assert trade.stake_amount == round(order['price'] * order['filled'] / leverage, 8)
 
     # In case of rejected or expired order and partially filled
-    limit_buy_order['status'] = 'expired'
-    limit_buy_order['amount'] = 90.99181073
-    limit_buy_order['filled'] = 80.99181073
-    limit_buy_order['remaining'] = 10.00
-    limit_buy_order['price'] = 0.5
-    limit_buy_order['cost'] = 40.495905365
-    limit_buy_order['id'] = '555'
+    order['status'] = 'expired'
+    order['amount'] = 30.0
+    order['filled'] = 20.0
+    order['remaining'] = 10.00
+    order['price'] = 0.5
+    order['cost'] = 15.0
+    order['id'] = '555'
     mocker.patch('freqtrade.exchange.Exchange.create_order',
-                 MagicMock(return_value=limit_buy_order))
+                 MagicMock(return_value=order))
     assert freqtrade.execute_entry(pair, stake_amount)
     trade = Trade.query.all()[3]
+    trade.is_short = is_short
     assert trade
     assert trade.open_order_id == '555'
     assert trade.open_rate == 0.5
-    assert trade.stake_amount == 40.495905365
+    assert trade.stake_amount == round(order['price'] * order['filled'] / leverage, 8)
 
     # Test with custom stake
-    limit_buy_order['status'] = 'open'
-    limit_buy_order['id'] = '556'
+    order['status'] = 'open'
+    order['id'] = '556'
 
     freqtrade.strategy.custom_stake_amount = lambda **kwargs: 150.0
-    assert freqtrade.execute_entry(pair, stake_amount)
+    assert freqtrade.execute_entry(pair, stake_amount, is_short=is_short)
     trade = Trade.query.all()[4]
+    trade.is_short = is_short
     assert trade
-    assert trade.stake_amount == 150
+    assert pytest.approx(trade.stake_amount) == 150
 
     # Exception case
-    limit_buy_order['id'] = '557'
+    order['id'] = '557'
     freqtrade.strategy.custom_stake_amount = lambda **kwargs: 20 / 0
-    assert freqtrade.execute_entry(pair, stake_amount)
+    assert freqtrade.execute_entry(pair, stake_amount, is_short=is_short)
     trade = Trade.query.all()[5]
+    trade.is_short = is_short
     assert trade
-    assert trade.stake_amount == 2.0
+    assert pytest.approx(trade.stake_amount) == 2.0
 
     # In case of the order is rejected and not filled at all
-    limit_buy_order['status'] = 'rejected'
-    limit_buy_order['amount'] = 90.99181073
-    limit_buy_order['filled'] = 0.0
-    limit_buy_order['remaining'] = 90.99181073
-    limit_buy_order['price'] = 0.5
-    limit_buy_order['cost'] = 0.0
-    limit_buy_order['id'] = '66'
+    order['status'] = 'rejected'
+    order['amount'] = 30.0 * leverage
+    order['filled'] = 0.0
+    order['remaining'] = 30.0
+    order['price'] = 0.5
+    order['cost'] = 0.0
+    order['id'] = '66'
     mocker.patch('freqtrade.exchange.Exchange.create_order',
-                 MagicMock(return_value=limit_buy_order))
+                 MagicMock(return_value=order))
     assert not freqtrade.execute_entry(pair, stake_amount)
+    assert freqtrade.strategy.leverage.call_count == 0 if trading_mode == 'spot' else 2
 
     # Fail to get price...
     mocker.patch('freqtrade.exchange.Exchange.get_rate', MagicMock(return_value=0.0))
 
-    with pytest.raises(PricingError, match="Could not determine buy price."):
-        freqtrade.execute_entry(pair, stake_amount)
+    with pytest.raises(PricingError, match="Could not determine entry price."):
+        freqtrade.execute_entry(pair, stake_amount, is_short=is_short)
 
     # In case of custom entry price
     mocker.patch('freqtrade.exchange.Exchange.get_rate', return_value=0.50)
-    limit_buy_order['status'] = 'open'
-    limit_buy_order['id'] = '5566'
+    order['status'] = 'open'
+    order['id'] = '5566'
     freqtrade.strategy.custom_entry_price = lambda **kwargs: 0.508
-    assert freqtrade.execute_entry(pair, stake_amount)
+    assert freqtrade.execute_entry(pair, stake_amount, is_short=is_short)
     trade = Trade.query.all()[6]
+    trade.is_short = is_short
     assert trade
     assert trade.open_rate_requested == 0.508
 
     # In case of custom entry price set to None
-    limit_buy_order['status'] = 'open'
-    limit_buy_order['id'] = '5567'
+
+    order['status'] = 'open'
+    order['id'] = '5567'
     freqtrade.strategy.custom_entry_price = lambda **kwargs: None
 
     mocker.patch.multiple(
@@ -838,46 +925,72 @@ def test_execute_entry(mocker, default_conf, fee, limit_buy_order, limit_buy_ord
         get_rate=MagicMock(return_value=10),
     )
 
-    assert freqtrade.execute_entry(pair, stake_amount)
+    assert freqtrade.execute_entry(pair, stake_amount, is_short=is_short)
     trade = Trade.query.all()[7]
+    trade.is_short = is_short
     assert trade
     assert trade.open_rate_requested == 10
 
     # In case of custom entry price not float type
-    limit_buy_order['status'] = 'open'
-    limit_buy_order['id'] = '5568'
+    freqtrade.exchange.get_maintenance_ratio_and_amt = MagicMock(return_value=(0.01, 0.01))
+    freqtrade.exchange.name = exchange_name
+    order['status'] = 'open'
+    order['id'] = '5568'
     freqtrade.strategy.custom_entry_price = lambda **kwargs: "string price"
-    assert freqtrade.execute_entry(pair, stake_amount)
+    assert freqtrade.execute_entry(pair, stake_amount, is_short=is_short)
     trade = Trade.query.all()[8]
+    # Trade(id=9, pair=ETH/USDT, amount=0.20000000, is_short=False,
+    #   leverage=1.0, open_rate=10.00000000, open_since=...)
+    # Trade(id=9, pair=ETH/USDT, amount=0.60000000, is_short=True,
+    #   leverage=3.0, open_rate=10.00000000, open_since=...)
+    trade.is_short = is_short
     assert trade
     assert trade.open_rate_requested == 10
+    assert trade.liquidation_price == liq_price
+
+    # In case of too high stake amount
+
+    order['status'] = 'open'
+    order['id'] = '55672'
+
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_max_pair_stake_amount=MagicMock(return_value=500),
+    )
+    freqtrade.exchange.get_max_pair_stake_amount = MagicMock(return_value=500)
+
+    assert freqtrade.execute_entry(pair, 2000, is_short=is_short)
+    trade = Trade.query.all()[9]
+    trade.is_short = is_short
+    assert pytest.approx(trade.stake_amount) == 500
 
 
-def test_execute_entry_confirm_error(mocker, default_conf, fee, limit_buy_order) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_execute_entry_confirm_error(mocker, default_conf_usdt, fee, limit_order, is_short) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
         }),
-        create_order=MagicMock(return_value=limit_buy_order),
+        create_order=MagicMock(return_value=limit_order[entry_side(is_short)]),
         get_rate=MagicMock(return_value=0.11),
         get_min_pair_stake_amount=MagicMock(return_value=1),
         get_fee=fee,
     )
     stake_amount = 2
-    pair = 'ETH/BTC'
+    pair = 'ETH/USDT'
 
     freqtrade.strategy.confirm_trade_entry = MagicMock(side_effect=ValueError)
     assert freqtrade.execute_entry(pair, stake_amount)
 
-    limit_buy_order['id'] = '222'
+    limit_order[entry_side(is_short)]['id'] = '222'
     freqtrade.strategy.confirm_trade_entry = MagicMock(side_effect=Exception)
     assert freqtrade.execute_entry(pair, stake_amount)
 
-    limit_buy_order['id'] = '2223'
+    limit_order[entry_side(is_short)]['id'] = '2223'
     freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
     assert freqtrade.execute_entry(pair, stake_amount)
 
@@ -885,22 +998,55 @@ def test_execute_entry_confirm_error(mocker, default_conf, fee, limit_buy_order)
     assert not freqtrade.execute_entry(pair, stake_amount)
 
 
-def test_add_stoploss_on_exchange(mocker, default_conf, limit_buy_order) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_execute_entry_min_leverage(mocker, default_conf_usdt, fee, limit_order, is_short) -> None:
+    default_conf_usdt['trading_mode'] = 'futures'
+    default_conf_usdt['margin_mode'] = 'isolated'
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
+        }),
+        create_order=MagicMock(return_value=limit_order[entry_side(is_short)]),
+        get_rate=MagicMock(return_value=0.11),
+        # Minimum stake-amount is ~5$
+        get_maintenance_ratio_and_amt=MagicMock(return_value=(0.0, 0.0)),
+        _fetch_and_calculate_funding_fees=MagicMock(return_value=0),
+        get_fee=fee,
+        get_max_leverage=MagicMock(return_value=5.0),
+    )
+    stake_amount = 2
+    pair = 'SOL/BUSD:BUSD'
+    freqtrade.strategy.leverage = MagicMock(return_value=5.0)
+
+    assert freqtrade.execute_entry(pair, stake_amount, is_short=is_short)
+    trade = Trade.query.first()
+    assert trade.leverage == 5.0
+    # assert trade.stake_amount == 2
+
+
+@pytest.mark.parametrize("is_short", [False, True])
+def test_add_stoploss_on_exchange(mocker, default_conf_usdt, limit_order, is_short) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
+    order = limit_order[entry_side(is_short)]
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
-    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order)
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
-                 return_value=limit_buy_order['amount'])
+                 return_value=order['amount'])
 
     stoploss = MagicMock(return_value={'id': 13434334})
     mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
 
     trade = MagicMock()
+    trade.is_short = is_short
     trade.open_order_id = None
     trade.stoploss_order_id = None
     trade.is_open = True
@@ -912,35 +1058,36 @@ def test_add_stoploss_on_exchange(mocker, default_conf, limit_buy_order) -> None
     assert trade.is_open is True
 
 
-def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
-                                     limit_buy_order, limit_sell_order) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_stoploss_on_exchange(mocker, default_conf_usdt, fee, caplog, is_short,
+                                     limit_order) -> None:
     stoploss = MagicMock(return_value={'id': 13434334})
+    enter_order = limit_order[entry_side(is_short)]
+    exit_order = limit_order[exit_side(is_short)]
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
         }),
         create_order=MagicMock(side_effect=[
-            {'id': limit_buy_order['id']},
-            {'id': limit_sell_order['id']},
+            {'id': enter_order['id']},
+            exit_order,
         ]),
         get_fee=fee,
-    )
-    mocker.patch.multiple(
-        'freqtrade.exchange.Binance',
         stoploss=stoploss
     )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     # First case: when stoploss is not yet set but the order is open
     # should get the stoploss order id immediately
     # and should return false as no trade actually happened
     trade = MagicMock()
+    trade.is_short = is_short
     trade.is_open = True
     trade.open_order_id = None
     trade.stoploss_order_id = None
@@ -956,7 +1103,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     trade.stoploss_order_id = 100
 
     hanging_stoploss_order = MagicMock(return_value={'status': 'open'})
-    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order', hanging_stoploss_order)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', hanging_stoploss_order)
 
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
     assert trade.stoploss_order_id == 100
@@ -969,7 +1116,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     trade.stoploss_order_id = 100
 
     canceled_stoploss_order = MagicMock(return_value={'status': 'canceled'})
-    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order', canceled_stoploss_order)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', canceled_stoploss_order)
     stoploss.reset_mock()
 
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
@@ -982,20 +1129,27 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     caplog.clear()
     freqtrade.enter_positions()
     trade = Trade.query.first()
+    trade.is_short = is_short
     trade.is_open = True
     trade.open_order_id = None
-    trade.stoploss_order_id = 100
+    trade.stoploss_order_id = "100"
+    trade.orders.append(Order(
+        ft_order_side='stoploss',
+        order_id='100',
+        ft_pair=trade.pair,
+        ft_is_open=True,
+    ))
     assert trade
 
     stoploss_order_hit = MagicMock(return_value={
-        'id': 100,
+        'id': "100",
         'status': 'closed',
         'type': 'stop_loss_limit',
         'price': 3,
         'average': 2,
-        'amount': limit_buy_order['amount'],
+        'amount': enter_order['amount'],
     })
-    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order', stoploss_order_hit)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hit)
     assert freqtrade.handle_stoploss_on_exchange(trade) is True
     assert log_has_re(r'STOP_LOSS_LIMIT is hit for Trade\(id=1, .*\)\.', caplog)
     assert trade.stoploss_order_id is None
@@ -1003,7 +1157,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     caplog.clear()
 
     mocker.patch(
-        'freqtrade.exchange.Binance.stoploss',
+        'freqtrade.exchange.Exchange.stoploss',
         side_effect=ExchangeError()
     )
     trade.is_open = True
@@ -1015,9 +1169,9 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     # It should try to add stoploss order
     trade.stoploss_order_id = 100
     stoploss.reset_mock()
-    mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order',
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order',
                  side_effect=InvalidOrderException())
-    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
+    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss)
     freqtrade.handle_stoploss_on_exchange(trade)
     assert stoploss.call_count == 1
 
@@ -1027,26 +1181,56 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
     trade.is_open = False
     stoploss.reset_mock()
     mocker.patch('freqtrade.exchange.Exchange.fetch_order')
-    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
+    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss)
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
     assert stoploss.call_count == 0
 
+    # Seventh case: emergency exit triggered
+    # Trailing stop should not act anymore
+    stoploss_order_cancelled = MagicMock(side_effect=[{
+        'id': "100",
+        'status': 'canceled',
+        'type': 'stop_loss_limit',
+        'price': 3,
+        'average': 2,
+        'amount': enter_order['amount'],
+        'info': {'stopPrice': 22},
+    }])
+    trade.stoploss_order_id = 100
+    trade.is_open = True
+    trade.stoploss_last_update = arrow.utcnow().shift(hours=-1).datetime
+    trade.stop_loss = 24
+    freqtrade.config['trailing_stop'] = True
+    stoploss = MagicMock(side_effect=InvalidOrderException())
 
-def test_handle_sle_cancel_cant_recreate(mocker, default_conf, fee, caplog,
-                                         limit_buy_order, limit_sell_order) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order_with_result',
+                 side_effect=InvalidOrderException())
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_cancelled)
+    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss)
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    assert trade.stoploss_order_id is None
+    assert trade.is_open is False
+    assert trade.exit_reason == str(ExitType.EMERGENCY_EXIT)
+
+
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_sle_cancel_cant_recreate(mocker, default_conf_usdt, fee, caplog, is_short,
+                                         limit_order) -> None:
     # Sixth case: stoploss order was cancelled but couldn't create new one
+    enter_order = limit_order[entry_side(is_short)]
+    exit_order = limit_order[exit_side(is_short)]
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
         }),
         create_order=MagicMock(side_effect=[
-            {'id': limit_buy_order['id']},
-            {'id': limit_sell_order['id']},
+            {'id': enter_order['id']},
+            {'id': exit_order['id']},
         ]),
         get_fee=fee,
     )
@@ -1055,11 +1239,12 @@ def test_handle_sle_cancel_cant_recreate(mocker, default_conf, fee, caplog,
         fetch_stoploss_order=MagicMock(return_value={'status': 'canceled', 'id': 100}),
         stoploss=MagicMock(side_effect=ExchangeError()),
     )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     freqtrade.enter_positions()
     trade = Trade.query.first()
+    trade.is_short = is_short
     trade.is_open = True
     trade.open_order_id = None
     trade.stoploss_order_id = 100
@@ -1071,20 +1256,24 @@ def test_handle_sle_cancel_cant_recreate(mocker, default_conf, fee, caplog,
     assert trade.is_open is True
 
 
-def test_create_stoploss_order_invalid_order(mocker, default_conf, caplog, fee,
-                                             limit_buy_order_open, limit_sell_order):
+@pytest.mark.parametrize("is_short", [False, True])
+def test_create_stoploss_order_invalid_order(
+    mocker, default_conf_usdt, caplog, fee, is_short, limit_order, limit_order_open
+):
+    open_order = limit_order_open[entry_side(is_short)]
+    order = limit_order[exit_side(is_short)]
     rpc_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     create_order_mock = MagicMock(side_effect=[
-        limit_buy_order_open,
-        {'id': limit_sell_order['id']}
+        open_order,
+        {'id': order['id']}
     ])
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
         }),
         create_order=create_order_mock,
         get_fee=fee,
@@ -1094,16 +1283,17 @@ def test_create_stoploss_order_invalid_order(mocker, default_conf, caplog, fee,
         fetch_order=MagicMock(return_value={'status': 'canceled'}),
         stoploss=MagicMock(side_effect=InvalidOrderException()),
     )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
 
     freqtrade.enter_positions()
     trade = Trade.query.first()
+    trade.is_short = is_short
     caplog.clear()
     freqtrade.create_stoploss_order(trade, 200)
     assert trade.stoploss_order_id is None
-    assert trade.sell_reason == SellType.EMERGENCY_SELL.value
+    assert trade.exit_reason == ExitType.EMERGENCY_EXIT.value
     assert log_has("Unable to place a stoploss order on exchange. ", caplog)
     assert log_has("Exiting the trade forcefully", caplog)
 
@@ -1115,26 +1305,28 @@ def test_create_stoploss_order_invalid_order(mocker, default_conf, caplog, fee,
 
     # Rpc is sending first buy, then sell
     assert rpc_mock.call_count == 2
-    assert rpc_mock.call_args_list[1][0][0]['sell_reason'] == SellType.EMERGENCY_SELL.value
+    assert rpc_mock.call_args_list[1][0][0]['sell_reason'] == ExitType.EMERGENCY_EXIT.value
     assert rpc_mock.call_args_list[1][0][0]['order_type'] == 'market'
 
 
-def test_create_stoploss_order_insufficient_funds(mocker, default_conf, caplog, fee,
-                                                  limit_buy_order_open, limit_sell_order):
-    sell_mock = MagicMock(return_value={'id': limit_sell_order['id']})
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_create_stoploss_order_insufficient_funds(
+    mocker, default_conf_usdt, caplog, fee, limit_order, is_short
+):
+    exit_order = limit_order[exit_side(is_short)]['id']
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     mock_insuf = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_insufficient_funds')
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
         }),
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
-            sell_mock,
+            limit_order[entry_side(is_short)],
+            exit_order,
         ]),
         get_fee=fee,
         fetch_order=MagicMock(return_value={'status': 'canceled'}),
@@ -1143,11 +1335,12 @@ def test_create_stoploss_order_insufficient_funds(mocker, default_conf, caplog,
         'freqtrade.exchange.Binance',
         stoploss=MagicMock(side_effect=InsufficientFundsError()),
     )
-    patch_get_signal(freqtrade)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
 
     freqtrade.enter_positions()
     trade = Trade.query.first()
+    trade.is_short = is_short
     caplog.clear()
     freqtrade.create_stoploss_order(trade, 200)
     # stoploss_orderid was empty before
@@ -1162,22 +1355,29 @@ def test_create_stoploss_order_insufficient_funds(mocker, default_conf, caplog,
     assert mock_insuf.call_count == 1
 
 
+@pytest.mark.parametrize("is_short,bid,ask,stop_price,amt,hang_price", [
+    (False, [4.38, 4.16], [4.4, 4.17], ['2.0805', 4.4 * 0.95], 27.39726027, 3),
+    (True, [1.09, 1.21], [1.1, 1.22], ['2.321', 1.09 * 1.05], 27.27272727, 1.5),
+])
 @pytest.mark.usefixtures("init_persistence")
-def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee,
-                                              limit_buy_order, limit_sell_order) -> None:
+def test_handle_stoploss_on_exchange_trailing(
+    mocker, default_conf_usdt, fee, is_short, bid, ask, limit_order, stop_price, amt, hang_price
+) -> None:
     # When trailing stoploss is set
+    enter_order = limit_order[entry_side(is_short)]
+    exit_order = limit_order[exit_side(is_short)]
     stoploss = MagicMock(return_value={'id': 13434334})
     patch_RPCManager(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 2.19,
+            'ask': 2.2,
+            'last': 2.19,
         }),
         create_order=MagicMock(side_effect=[
-            {'id': limit_buy_order['id']},
-            {'id': limit_sell_order['id']},
+            {'id': enter_order['id']},
+            {'id': exit_order['id']},
         ]),
         get_fee=fee,
     )
@@ -1188,26 +1388,27 @@ def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee,
     )
 
     # enabling TSL
-    default_conf['trailing_stop'] = True
+    default_conf_usdt['trailing_stop'] = True
 
     # disabling ROI
-    default_conf['minimal_roi']['0'] = 999999999
+    default_conf_usdt['minimal_roi']['0'] = 999999999
 
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     # enabling stoploss on exchange
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
 
     # setting stoploss
-    freqtrade.strategy.stoploss = -0.05
+    freqtrade.strategy.stoploss = 0.05 if is_short else -0.05
 
     # setting stoploss_on_exchange_interval to 60 seconds
     freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 60
 
-    patch_get_signal(freqtrade)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     freqtrade.enter_positions()
     trade = Trade.query.first()
+    trade.is_short = is_short
     trade.is_open = True
     trade.open_order_id = None
     trade.stoploss_order_id = 100
@@ -1216,10 +1417,10 @@ def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee,
         'id': 100,
         'status': 'open',
         'type': 'stop_loss_limit',
-        'price': 3,
+        'price': hang_price,
         'average': 2,
         'info': {
-            'stopPrice': '0.000011134'
+            'stopPrice': stop_price[0]
         }
     })
 
@@ -1230,11 +1431,14 @@ def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee,
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
 
     # price jumped 2x
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
-        'bid': 0.00002344,
-        'ask': 0.00002346,
-        'last': 0.00002344
-    }))
+    mocker.patch(
+        'freqtrade.exchange.Exchange.fetch_ticker',
+        MagicMock(return_value={
+            'bid': bid[0],
+            'ask': ask[0],
+            'last': bid[0],
+        })
+    )
 
     cancel_order_mock = MagicMock()
     stoploss_order_mock = MagicMock(return_value={'id': 13434334})
@@ -1248,30 +1452,41 @@ def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee,
     stoploss_order_mock.assert_not_called()
 
     assert freqtrade.handle_trade(trade) is False
-    assert trade.stop_loss == 0.00002346 * 0.95
+    assert trade.stop_loss == stop_price[1]
 
     # setting stoploss_on_exchange_interval to 0 seconds
     freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 0
 
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
 
-    cancel_order_mock.assert_called_once_with(100, 'ETH/BTC')
-    stoploss_order_mock.assert_called_once_with(amount=85.32423208,
-                                                pair='ETH/BTC',
-                                                order_types=freqtrade.strategy.order_types,
-                                                stop_price=0.00002346 * 0.95)
+    cancel_order_mock.assert_called_once_with(100, 'ETH/USDT')
+    stoploss_order_mock.assert_called_once_with(
+        amount=pytest.approx(amt),
+        pair='ETH/USDT',
+        order_types=freqtrade.strategy.order_types,
+        stop_price=stop_price[1],
+        side=exit_side(is_short),
+        leverage=1.0
+    )
 
     # price fell below stoploss, so dry-run sells trade.
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
-        'bid': 0.00002144,
-        'ask': 0.00002146,
-        'last': 0.00002144
-    }))
+    mocker.patch(
+        'freqtrade.exchange.Exchange.fetch_ticker',
+        MagicMock(return_value={
+            'bid': bid[1],
+            'ask': ask[1],
+            'last': bid[1],
+        })
+    )
     assert freqtrade.handle_trade(trade) is True
 
 
-def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, caplog,
-                                                    limit_buy_order, limit_sell_order) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_stoploss_on_exchange_trailing_error(
+    mocker, default_conf_usdt, fee, caplog, limit_order, is_short
+) -> None:
+    enter_order = limit_order[entry_side(is_short)]
+    exit_order = limit_order[exit_side(is_short)]
     # When trailing stoploss is set
     stoploss = MagicMock(return_value={'id': 13434334})
     patch_exchange(mocker)
@@ -1279,13 +1494,13 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
         }),
         create_order=MagicMock(side_effect=[
-            {'id': limit_buy_order['id']},
-            {'id': limit_sell_order['id']},
+            {'id': enter_order['id']},
+            {'id': exit_order['id']},
         ]),
         get_fee=fee,
     )
@@ -1296,25 +1511,27 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c
     )
 
     # enabling TSL
-    default_conf['trailing_stop'] = True
+    default_conf_usdt['trailing_stop'] = True
 
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     # enabling stoploss on exchange
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
 
     # setting stoploss
-    freqtrade.strategy.stoploss = -0.05
+    freqtrade.strategy.stoploss = 0.05 if is_short else -0.05
 
     # setting stoploss_on_exchange_interval to 60 seconds
     freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 60
-    patch_get_signal(freqtrade)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.enter_positions()
     trade = Trade.query.first()
+    trade.is_short = is_short
     trade.is_open = True
     trade.open_order_id = None
     trade.stoploss_order_id = "abcd"
     trade.stop_loss = 0.2
     trade.stoploss_last_update = arrow.utcnow().shift(minutes=-601).datetime.replace(tzinfo=None)
+    trade.is_short = is_short
 
     stoploss_order_hanging = {
         'id': "abcd",
@@ -1331,7 +1548,7 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c
     mocker.patch('freqtrade.exchange.Binance.fetch_stoploss_order',
                  return_value=stoploss_order_hanging)
     freqtrade.handle_trailing_stoploss_on_exchange(trade, stoploss_order_hanging)
-    assert log_has_re(r"Could not cancel stoploss order abcd for pair ETH/BTC.*", caplog)
+    assert log_has_re(r"Could not cancel stoploss order abcd for pair ETH/USDT.*", caplog)
 
     # Still try to create order
     assert stoploss.call_count == 1
@@ -1342,25 +1559,55 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c
     mocker.patch("freqtrade.exchange.Binance.stoploss", side_effect=ExchangeError())
     freqtrade.handle_trailing_stoploss_on_exchange(trade, stoploss_order_hanging)
     assert cancel_mock.call_count == 1
-    assert log_has_re(r"Could not create trailing stoploss order for pair ETH/BTC\..*", caplog)
+    assert log_has_re(r"Could not create trailing stoploss order for pair ETH/USDT\..*", caplog)
 
 
+def test_stoploss_on_exchange_price_rounding(
+        mocker, default_conf_usdt, fee, open_trade_usdt) -> None:
+    patch_RPCManager(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_fee=fee,
+    )
+    price_mock = MagicMock(side_effect=lambda p, s: int(s))
+    stoploss_mock = MagicMock(return_value={'id': '13434334'})
+    adjust_mock = MagicMock(return_value=False)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Binance',
+        stoploss=stoploss_mock,
+        stoploss_adjust=adjust_mock,
+        price_to_precision=price_mock,
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    open_trade_usdt.stoploss_order_id = '13434334'
+    open_trade_usdt.stop_loss = 222.55
+
+    freqtrade.handle_trailing_stoploss_on_exchange(open_trade_usdt, {})
+    assert price_mock.call_count == 1
+    assert adjust_mock.call_count == 1
+    assert adjust_mock.call_args_list[0][0][0] == 222
+
+
+@pytest.mark.parametrize("is_short", [False, True])
 @pytest.mark.usefixtures("init_persistence")
-def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee,
-                                                 limit_buy_order, limit_sell_order) -> None:
+def test_handle_stoploss_on_exchange_custom_stop(
+    mocker, default_conf_usdt, fee, is_short, limit_order
+) -> None:
+    enter_order = limit_order[entry_side(is_short)]
+    exit_order = limit_order[exit_side(is_short)]
     # When trailing stoploss is set
     stoploss = MagicMock(return_value={'id': 13434334})
     patch_RPCManager(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
         }),
         create_order=MagicMock(side_effect=[
-            {'id': limit_buy_order['id']},
-            {'id': limit_sell_order['id']},
+            {'id': enter_order['id']},
+            {'id': exit_order['id']},
         ]),
         get_fee=fee,
     )
@@ -1371,12 +1618,12 @@ def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee,
     )
 
     # enabling TSL
-    default_conf['use_custom_stoploss'] = True
+    default_conf_usdt['use_custom_stoploss'] = True
 
     # disabling ROI
-    default_conf['minimal_roi']['0'] = 999999999
+    default_conf_usdt['minimal_roi']['0'] = 999999999
 
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     # enabling stoploss on exchange
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
@@ -1387,10 +1634,11 @@ def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee,
     # setting stoploss_on_exchange_interval to 60 seconds
     freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 60
 
-    patch_get_signal(freqtrade)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     freqtrade.enter_positions()
     trade = Trade.query.first()
+    trade.is_short = is_short
     trade.is_open = True
     trade.open_order_id = None
     trade.stoploss_order_id = 100
@@ -1402,7 +1650,7 @@ def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee,
         'price': 3,
         'average': 2,
         'info': {
-            'stopPrice': '0.000011134'
+            'stopPrice': '2.0805'
         }
     })
 
@@ -1412,11 +1660,14 @@ def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee,
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
 
     # price jumped 2x
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
-        'bid': 0.00002344,
-        'ask': 0.00002346,
-        'last': 0.00002344
-    }))
+    mocker.patch(
+        'freqtrade.exchange.Exchange.fetch_ticker',
+        MagicMock(return_value={
+            'bid': 4.38 if not is_short else 1.9 / 2,
+            'ask': 4.4 if not is_short else 2.2 / 2,
+            'last': 4.38 if not is_short else 1.9 / 2,
+        })
+    )
 
     cancel_order_mock = MagicMock()
     stoploss_order_mock = MagicMock(return_value={'id': 13434334})
@@ -1430,31 +1681,42 @@ def test_handle_stoploss_on_exchange_custom_stop(mocker, default_conf, fee,
     stoploss_order_mock.assert_not_called()
 
     assert freqtrade.handle_trade(trade) is False
-    assert trade.stop_loss == 0.00002346 * 0.96
-    assert trade.stop_loss_pct == -0.04
+    assert trade.stop_loss == 4.4 * 0.96 if not is_short else 1.1
+    assert trade.stop_loss_pct == -0.04 if not is_short else 0.04
 
     # setting stoploss_on_exchange_interval to 0 seconds
     freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 0
 
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
 
-    cancel_order_mock.assert_called_once_with(100, 'ETH/BTC')
-    stoploss_order_mock.assert_called_once_with(amount=85.32423208,
-                                                pair='ETH/BTC',
-                                                order_types=freqtrade.strategy.order_types,
-                                                stop_price=0.00002346 * 0.96)
+    cancel_order_mock.assert_called_once_with(100, 'ETH/USDT')
+    # Long uses modified ask - offset, short modified bid + offset
+    stoploss_order_mock.assert_called_once_with(
+        amount=pytest.approx(trade.amount),
+        pair='ETH/USDT',
+        order_types=freqtrade.strategy.order_types,
+        stop_price=4.4 * 0.96 if not is_short else 0.95 * 1.04,
+        side=exit_side(is_short),
+        leverage=1.0
+    )
 
     # price fell below stoploss, so dry-run sells trade.
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
-        'bid': 0.00002144,
-        'ask': 0.00002146,
-        'last': 0.00002144
-    }))
+    mocker.patch(
+        'freqtrade.exchange.Exchange.fetch_ticker',
+        MagicMock(return_value={
+            'bid': 4.17,
+            'ask': 4.19,
+            'last': 4.17
+        })
+    )
     assert freqtrade.handle_trade(trade) is True
 
 
 def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
-                                              limit_buy_order, limit_sell_order) -> None:
+                                              limit_order) -> None:
+
+    enter_order = limit_order['buy']
+    exit_order = limit_order['sell']
 
     # When trailing stoploss is set
     stoploss = MagicMock(return_value={'id': 13434334})
@@ -1467,13 +1729,13 @@ def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 2.19,
+            'ask': 2.2,
+            'last': 2.19
         }),
         create_order=MagicMock(side_effect=[
-            {'id': limit_buy_order['id']},
-            {'id': limit_sell_order['id']},
+            {'id': enter_order['id']},
+            {'id': exit_order['id']},
         ]),
         get_fee=fee,
         stoploss=stoploss,
@@ -1515,7 +1777,7 @@ def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
         'price': 3,
         'average': 2,
         'info': {
-            'stopPrice': '0.000009384'
+            'stopPrice': '2.178'
         }
     })
 
@@ -1524,7 +1786,7 @@ def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
     # stoploss initially at 20% as edge dictated it.
     assert freqtrade.handle_trade(trade) is False
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
-    assert trade.stop_loss == 0.000009384
+    assert isclose(trade.stop_loss, 1.76)
 
     cancel_order_mock = MagicMock()
     stoploss_order_mock = MagicMock()
@@ -1533,47 +1795,50 @@ def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
 
     # price goes down 5%
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
-        'bid': 0.00001172 * 0.95,
-        'ask': 0.00001173 * 0.95,
-        'last': 0.00001172 * 0.95
+        'bid': 2.19 * 0.95,
+        'ask': 2.2 * 0.95,
+        'last': 2.19 * 0.95
     }))
-
     assert freqtrade.handle_trade(trade) is False
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
 
     # stoploss should remain the same
-    assert trade.stop_loss == 0.000009384
+    assert isclose(trade.stop_loss, 1.76)
 
     # stoploss on exchange should not be canceled
     cancel_order_mock.assert_not_called()
 
     # price jumped 2x
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
-        'bid': 0.00002344,
-        'ask': 0.00002346,
-        'last': 0.00002344
+        'bid': 4.38,
+        'ask': 4.4,
+        'last': 4.38
     }))
 
     assert freqtrade.handle_trade(trade) is False
     assert freqtrade.handle_stoploss_on_exchange(trade) is False
 
     # stoploss should be set to 1% as trailing is on
-    assert trade.stop_loss == 0.00002346 * 0.99
+    assert trade.stop_loss == 4.4 * 0.99
     cancel_order_mock.assert_called_once_with(100, 'NEO/BTC')
-    stoploss_order_mock.assert_called_once_with(amount=2132892.49146757,
-                                                pair='NEO/BTC',
-                                                order_types=freqtrade.strategy.order_types,
-                                                stop_price=0.00002346 * 0.99)
+    stoploss_order_mock.assert_called_once_with(
+        amount=pytest.approx(11.41438356),
+        pair='NEO/BTC',
+        order_types=freqtrade.strategy.order_types,
+        stop_price=4.4 * 0.99,
+        side='sell',
+        leverage=1.0
+    )
 
 
 @pytest.mark.parametrize('return_value,side_effect,log_message', [
-    (False, None, 'Found no buy signals for whitelisted currencies. Trying again...'),
-    (None, DependencyException, 'Unable to create trade for ETH/BTC: ')
+    (False, None, 'Found no enter signals for whitelisted currencies. Trying again...'),
+    (None, DependencyException, 'Unable to create trade for ETH/USDT: ')
 ])
-def test_enter_positions(mocker, default_conf, return_value, side_effect,
+def test_enter_positions(mocker, default_conf_usdt, return_value, side_effect,
                          log_message, caplog) -> None:
     caplog.set_level(logging.DEBUG)
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     mock_ct = mocker.patch(
         'freqtrade.freqtradebot.FreqtradeBot.create_trade',
@@ -1586,19 +1851,22 @@ def test_enter_positions(mocker, default_conf, return_value, side_effect,
     assert n == 0
     assert log_has(log_message, caplog)
     # create_trade should be called once for every pair in the whitelist.
-    assert mock_ct.call_count == len(default_conf['exchange']['pair_whitelist'])
+    assert mock_ct.call_count == len(default_conf_usdt['exchange']['pair_whitelist'])
 
 
-def test_exit_positions(mocker, default_conf, limit_buy_order, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_exit_positions(mocker, default_conf_usdt, limit_order, is_short, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
-    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order',
+                 return_value=limit_order[entry_side(is_short)])
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
-                 return_value=limit_buy_order['amount'])
+                 return_value=limit_order[entry_side(is_short)]['amount'])
 
     trade = MagicMock()
+    trade.is_short = is_short
     trade.open_order_id = '123'
     trade.open_fee = 0.001
     trades = [trade]
@@ -1606,7 +1874,7 @@ def test_exit_positions(mocker, default_conf, limit_buy_order, caplog) -> None:
     assert n == 0
     # Test amount not modified by fee-logic
     assert not log_has(
-        'Applying fee to amount for Trade {} from 90.99181073 to 90.81'.format(trade), caplog
+        'Applying fee to amount for Trade {} from 30.0 to 90.81'.format(trade), caplog
     )
 
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=90.81)
@@ -1615,14 +1883,16 @@ def test_exit_positions(mocker, default_conf, limit_buy_order, caplog) -> None:
     assert n == 0
 
 
-def test_exit_positions_exception(mocker, default_conf, limit_buy_order, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_exit_positions_exception(mocker, default_conf_usdt, limit_order, caplog, is_short) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    order = limit_order[entry_side(is_short)]
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order)
 
     trade = MagicMock()
+    trade.is_short = is_short
     trade.open_order_id = None
-    trade.open_fee = 0.001
-    trade.pair = 'ETH/BTC'
+    trade.pair = 'ETH/USDT'
     trades = [trade]
 
     # Test raise of DependencyException exception
@@ -1630,95 +1900,138 @@ def test_exit_positions_exception(mocker, default_conf, limit_buy_order, caplog)
         'freqtrade.freqtradebot.FreqtradeBot.handle_trade',
         side_effect=DependencyException()
     )
+    caplog.clear()
     n = freqtrade.exit_positions(trades)
     assert n == 0
-    assert log_has('Unable to sell trade ETH/BTC: ', caplog)
+    assert log_has('Unable to exit trade ETH/USDT: ', caplog)
 
 
-def test_update_trade_state(mocker, default_conf, limit_buy_order, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_update_trade_state(mocker, default_conf_usdt, limit_order, is_short, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    order = limit_order[entry_side(is_short)]
 
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
-    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order)
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
-                 return_value=limit_buy_order['amount'])
+                 return_value=order['amount'])
+    order_id = order['id']
 
     trade = Trade(
-        open_order_id=123,
+        open_order_id=order_id,
         fee_open=0.001,
         fee_close=0.001,
         open_rate=0.01,
         open_date=arrow.utcnow().datetime,
         amount=11,
         exchange="binance",
+        is_short=is_short,
+        leverage=1,
     )
+    trade.orders.append(Order(
+        ft_order_side=entry_side(is_short),
+        price=0.01,
+        order_id=order_id,
+
+    ))
     assert not freqtrade.update_trade_state(trade, None)
     assert log_has_re(r'Orderid for trade .* is empty.', caplog)
     caplog.clear()
     # Add datetime explicitly since sqlalchemy defaults apply only once written to database
-    freqtrade.update_trade_state(trade, '123')
+    freqtrade.update_trade_state(trade, order_id)
     # Test amount not modified by fee-logic
     assert not log_has_re(r'Applying fee to .*', caplog)
     caplog.clear()
     assert trade.open_order_id is None
-    assert trade.amount == limit_buy_order['amount']
+    assert trade.amount == order['amount']
 
-    trade.open_order_id = '123'
+    trade.open_order_id = order_id
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=90.81)
     assert trade.amount != 90.81
     # test amount modified by fee-logic
-    freqtrade.update_trade_state(trade, '123')
+    freqtrade.update_trade_state(trade, order_id)
     assert trade.amount == 90.81
     assert trade.open_order_id is None
 
     trade.is_open = True
     trade.open_order_id = None
     # Assert we call handle_trade() if trade is feasible for execution
-    freqtrade.update_trade_state(trade, '123')
+    freqtrade.update_trade_state(trade, order_id)
 
     assert log_has_re('Found open order for.*', caplog)
+    limit_buy_order_usdt_new = deepcopy(limit_order)
+    limit_buy_order_usdt_new['filled'] = 0.0
+    limit_buy_order_usdt_new['status'] = 'canceled'
+
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', side_effect=ValueError)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order_usdt_new)
+    res = freqtrade.update_trade_state(trade, order_id)
+    # Cancelled empty
+    assert res is True
 
 
+@pytest.mark.parametrize("is_short", [False, True])
 @pytest.mark.parametrize('initial_amount,has_rounding_fee', [
-    (90.99181073 + 1e-14, True),
+    (30.0 + 1e-14, True),
     (8.0, False)
 ])
-def test_update_trade_state_withorderdict(default_conf, trades_for_order, limit_buy_order, fee,
-                                          mocker, initial_amount, has_rounding_fee, caplog):
+def test_update_trade_state_withorderdict(
+    default_conf_usdt, trades_for_order, limit_order, fee, mocker, initial_amount,
+    has_rounding_fee, is_short, caplog
+):
+    order = limit_order[entry_side(is_short)]
     trades_for_order[0]['amount'] = initial_amount
+    order_id = "oid_123456"
+    order['id'] = order_id
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
     # fetch_order should not be called!!
     mocker.patch('freqtrade.exchange.Exchange.fetch_order', MagicMock(side_effect=ValueError))
     patch_exchange(mocker)
     amount = sum(x['amount'] for x in trades_for_order)
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    caplog.clear()
     trade = Trade(
-        pair='LTC/ETH',
+        pair='LTC/USDT',
         amount=amount,
         exchange='binance',
-        open_rate=0.245441,
+        open_rate=2.0,
         open_date=arrow.utcnow().datetime,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        open_order_id="123456",
+        open_order_id=order_id,
         is_open=True,
+        leverage=1,
+        is_short=is_short,
     )
-    freqtrade.update_trade_state(trade, '123456', limit_buy_order)
+    trade.orders.append(
+        Order(
+            ft_order_side=entry_side(is_short),
+            ft_pair=trade.pair,
+            ft_is_open=True,
+            order_id=order_id,
+        )
+    )
+    log_text = r'Applying fee on amount for .*'
+    freqtrade.update_trade_state(trade, order_id, order)
     assert trade.amount != amount
-    assert trade.amount == limit_buy_order['amount']
     if has_rounding_fee:
-        assert log_has_re(r'Applying fee on amount for .*', caplog)
+        assert pytest.approx(trade.amount) == 29.992
+        assert log_has_re(log_text, caplog)
+    else:
+        assert pytest.approx(trade.amount) == order['amount']
+        assert not log_has_re(log_text, caplog)
 
 
-def test_update_trade_state_exception(mocker, default_conf,
-                                      limit_buy_order, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_update_trade_state_exception(mocker, default_conf_usdt, is_short, limit_order,
+                                      caplog) -> None:
+    order = limit_order[entry_side(is_short)]
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=order)
 
     trade = MagicMock()
     trade.open_order_id = '123'
-    trade.open_fee = 0.001
 
     # Test raise of OperationalException exception
     mocker.patch(
@@ -1729,14 +2042,13 @@ def test_update_trade_state_exception(mocker, default_conf,
     assert log_has('Could not update trade amount: ', caplog)
 
 
-def test_update_trade_state_orderexception(mocker, default_conf, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+def test_update_trade_state_orderexception(mocker, default_conf_usdt, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     mocker.patch('freqtrade.exchange.Exchange.fetch_order',
                  MagicMock(side_effect=InvalidOrderException))
 
     trade = MagicMock()
     trade.open_order_id = '123'
-    trade.open_fee = 0.001
 
     # Test raise of OperationalException exception
     grm_mock = mocker.patch("freqtrade.freqtradebot.FreqtradeBot.get_real_amount", MagicMock())
@@ -1745,8 +2057,12 @@ def test_update_trade_state_orderexception(mocker, default_conf, caplog) -> None
     assert log_has(f'Unable to fetch order {trade.open_order_id}: ', caplog)
 
 
-def test_update_trade_state_sell(default_conf, trades_for_order, limit_sell_order_open,
-                                 limit_sell_order, mocker):
+@pytest.mark.parametrize("is_short", [False, True])
+def test_update_trade_state_sell(
+    default_conf_usdt, trades_for_order, limit_order_open, limit_order, is_short, mocker,
+):
+    open_order = limit_order_open[exit_side(is_short)]
+    l_order = limit_order[exit_side(is_short)]
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
     # fetch_order should not be called!!
     mocker.patch('freqtrade.exchange.Exchange.fetch_order', MagicMock(side_effect=ValueError))
@@ -1754,8 +2070,8 @@ def test_update_trade_state_sell(default_conf, trades_for_order, limit_sell_orde
     mocker.patch('freqtrade.wallets.Wallets.update', wallet_mock)
 
     patch_exchange(mocker)
-    amount = limit_sell_order["amount"]
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    amount = l_order["amount"]
     wallet_mock.reset_mock()
     trade = Trade(
         pair='LTC/ETH',
@@ -1765,14 +2081,17 @@ def test_update_trade_state_sell(default_conf, trades_for_order, limit_sell_orde
         fee_open=0.0025,
         fee_close=0.0025,
         open_date=arrow.utcnow().datetime,
-        open_order_id="123456",
+        open_order_id=open_order['id'],
         is_open=True,
+        interest_rate=0.0005,
+        leverage=1,
+        is_short=is_short,
     )
-    order = Order.parse_from_ccxt_object(limit_sell_order_open, 'LTC/ETH', 'sell')
+    order = Order.parse_from_ccxt_object(open_order, 'LTC/ETH', exit_side(is_short))
     trade.orders.append(order)
     assert order.status == 'open'
-    freqtrade.update_trade_state(trade, trade.open_order_id, limit_sell_order)
-    assert trade.amount == limit_sell_order['amount']
+    freqtrade.update_trade_state(trade, trade.open_order_id, l_order)
+    assert trade.amount == l_order['amount']
     # Wallet needs to be updated after closing a limit-sell order to reenable buying
     assert wallet_mock.call_count == 1
     assert not trade.is_open
@@ -1780,126 +2099,165 @@ def test_update_trade_state_sell(default_conf, trades_for_order, limit_sell_orde
     assert order.status == 'closed'
 
 
-def test_handle_trade(default_conf, limit_buy_order, limit_sell_order_open, limit_sell_order,
-                      fee, mocker) -> None:
+@pytest.mark.parametrize('is_short,close_profit', [
+    (False, 0.09451372),
+    (True, 0.08635224),
+])
+def test_handle_trade(
+    default_conf_usdt, limit_order_open, limit_order, fee, mocker, is_short, close_profit
+) -> None:
+    open_order = limit_order_open[exit_side(is_short)]
+    enter_order = limit_order[entry_side(is_short)]
+    exit_order = limit_order[exit_side(is_short)]
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 2.19,
+            'ask': 2.2,
+            'last': 2.19
         }),
         create_order=MagicMock(side_effect=[
-            limit_buy_order,
-            limit_sell_order_open,
+            enter_order,
+            open_order,
         ]),
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
 
     time.sleep(0.01)  # Race condition fix
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(enter_order, enter_order['symbol'], entry_side(is_short))
+    trade.update_trade(oobj)
     assert trade.is_open is True
     freqtrade.wallets.update()
 
-    patch_get_signal(freqtrade, value=(False, True, None))
+    patch_get_signal(freqtrade, enter_long=False, exit_short=is_short,
+                     exit_long=not is_short, exit_tag='sell_signal1')
     assert freqtrade.handle_trade(trade) is True
-    assert trade.open_order_id == limit_sell_order['id']
+    assert trade.open_order_id == exit_order['id']
 
     # Simulate fulfilled LIMIT_SELL order for trade
-    trade.update(limit_sell_order)
+    oobj = Order.parse_from_ccxt_object(exit_order, exit_order['symbol'], exit_side(is_short))
+    trade.update_trade(oobj)
 
-    assert trade.close_rate == 0.00001173
-    assert trade.close_profit == 0.06201058
-    assert trade.calc_profit() == 0.00006217
+    assert trade.close_rate == 2.0 if is_short else 2.2
+    assert trade.close_profit == close_profit
+    assert trade.calc_profit() == 5.685
     assert trade.close_date is not None
+    assert trade.exit_reason == 'sell_signal1'
 
 
-def test_handle_overlapping_signals(default_conf, ticker, limit_buy_order_open,
-                                    fee, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_overlapping_signals(
+    default_conf_usdt, ticker_usdt, limit_order_open, fee, mocker, is_short
+) -> None:
+    open_order = limit_order_open[exit_side(is_short)]
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
+            open_order,
             {'id': 1234553382},
         ]),
         get_fee=fee,
     )
 
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade, value=(True, True, None))
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    if is_short:
+        patch_get_signal(freqtrade, enter_long=False, enter_short=True, exit_short=True)
+    else:
+        patch_get_signal(freqtrade, enter_long=True, exit_long=True)
     freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
 
     freqtrade.enter_positions()
 
     # Buy and Sell triggering, so doing nothing ...
     trades = Trade.query.all()
+
     nb_trades = len(trades)
     assert nb_trades == 0
 
     # Buy is triggering, so buying ...
-    patch_get_signal(freqtrade)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.enter_positions()
     trades = Trade.query.all()
+    for trade in trades:
+        trade.is_short = is_short
     nb_trades = len(trades)
     assert nb_trades == 1
     assert trades[0].is_open is True
 
     # Buy and Sell are not triggering, so doing nothing ...
-    patch_get_signal(freqtrade, value=(False, False, None))
+    patch_get_signal(freqtrade, enter_long=False)
     assert freqtrade.handle_trade(trades[0]) is False
     trades = Trade.query.all()
+    for trade in trades:
+        trade.is_short = is_short
     nb_trades = len(trades)
     assert nb_trades == 1
     assert trades[0].is_open is True
 
     # Buy and Sell are triggering, so doing nothing ...
-    patch_get_signal(freqtrade, value=(True, True, None))
+    if is_short:
+        patch_get_signal(freqtrade, enter_long=False, enter_short=True, exit_short=True)
+    else:
+        patch_get_signal(freqtrade, enter_long=True, exit_long=True)
     assert freqtrade.handle_trade(trades[0]) is False
     trades = Trade.query.all()
+    for trade in trades:
+        trade.is_short = is_short
     nb_trades = len(trades)
     assert nb_trades == 1
     assert trades[0].is_open is True
 
     # Sell is triggering, guess what : we are Selling!
-    patch_get_signal(freqtrade, value=(False, True, None))
+    if is_short:
+        patch_get_signal(freqtrade, enter_long=False, exit_short=True)
+    else:
+        patch_get_signal(freqtrade, enter_long=False, exit_long=True)
     trades = Trade.query.all()
+    for trade in trades:
+        trade.is_short = is_short
     assert freqtrade.handle_trade(trades[0]) is True
 
 
-def test_handle_trade_roi(default_conf, ticker, limit_buy_order_open,
-                          fee, mocker, caplog) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_trade_roi(default_conf_usdt, ticker_usdt, limit_order_open, fee, mocker, caplog,
+                          is_short) -> None:
+
+    open_order = limit_order_open[entry_side(is_short)]
+
     caplog.set_level(logging.DEBUG)
 
     patch_RPCManager(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
+            open_order,
             {'id': 1234553382},
         ]),
         get_fee=fee,
     )
 
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.min_roi_reached = MagicMock(return_value=True)
 
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     trade.is_open = True
 
     # FIX: sniffing logs, suggest handle_trade should not execute_trade_exit
@@ -1907,73 +2265,92 @@ def test_handle_trade_roi(default_conf, ticker, limit_buy_order_open,
     #      we might just want to check if we are in a sell condition without
     #      executing
     # if ROI is reached we must sell
-    patch_get_signal(freqtrade, value=(False, True, None))
+    caplog.clear()
+    patch_get_signal(freqtrade)
     assert freqtrade.handle_trade(trade)
-    assert log_has("ETH/BTC - Required profit reached. sell_type=SellType.ROI",
+    assert log_has("ETH/USDT - Required profit reached. exit_type=ExitType.ROI",
                    caplog)
 
 
-def test_handle_trade_use_sell_signal(default_conf, ticker, limit_buy_order_open,
-                                      limit_sell_order_open, fee, mocker, caplog) -> None:
-    # use_sell_signal is True buy default
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_trade_use_exit_signal(
+    default_conf_usdt, ticker_usdt, limit_order_open, fee, mocker, caplog, is_short
+) -> None:
+
+    enter_open_order = limit_order_open[exit_side(is_short)]
+    exit_open_order = limit_order_open[entry_side(is_short)]
+
+    # use_exit_signal is True buy default
     caplog.set_level(logging.DEBUG)
     patch_RPCManager(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
-            limit_sell_order_open,
+            enter_open_order,
+            exit_open_order,
         ]),
         get_fee=fee,
     )
 
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     trade.is_open = True
 
-    patch_get_signal(freqtrade, value=(False, False, None))
+    patch_get_signal(freqtrade, enter_long=False, exit_long=False)
     assert not freqtrade.handle_trade(trade)
 
-    patch_get_signal(freqtrade, value=(False, True, None))
+    if is_short:
+        patch_get_signal(freqtrade, enter_long=False, exit_short=True)
+    else:
+        patch_get_signal(freqtrade, enter_long=False, exit_long=True)
     assert freqtrade.handle_trade(trade)
-    assert log_has("ETH/BTC - Sell signal received. sell_type=SellType.SELL_SIGNAL",
+    assert log_has("ETH/USDT - Sell signal received. exit_type=ExitType.EXIT_SIGNAL",
                    caplog)
 
 
-def test_close_trade(default_conf, ticker, limit_buy_order, limit_buy_order_open, limit_sell_order,
-                     fee, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_close_trade(
+    default_conf_usdt, ticker_usdt, limit_order_open, limit_order, fee, mocker, is_short
+) -> None:
+    open_order = limit_order_open[exit_side(is_short)]
+    enter_order = limit_order[exit_side(is_short)]
+    exit_order = limit_order[entry_side(is_short)]
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value=limit_buy_order_open),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value=open_order),
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     # Create trade and sell it
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
 
-    trade.update(limit_buy_order)
-    trade.update(limit_sell_order)
+    oobj = Order.parse_from_ccxt_object(enter_order, enter_order['symbol'], 'buy')
+    trade.update_trade(oobj)
+    oobj = Order.parse_from_ccxt_object(exit_order, exit_order['symbol'], 'sell')
+    trade.update_trade(oobj)
     assert trade.is_open is False
 
     with pytest.raises(DependencyException, match=r'.*closed trade.*'):
         freqtrade.handle_trade(trade)
 
 
-def test_bot_loop_start_called_once(mocker, default_conf, caplog):
-    ftbot = get_patched_freqtradebot(mocker, default_conf)
+def test_bot_loop_start_called_once(mocker, default_conf_usdt, caplog):
+    ftbot = get_patched_freqtradebot(mocker, default_conf_usdt)
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.create_trade')
     patch_get_signal(ftbot)
     ftbot.strategy.bot_loop_start = MagicMock(side_effect=ValueError)
@@ -1985,27 +2362,36 @@ def test_bot_loop_start_called_once(mocker, default_conf, caplog):
     assert ftbot.strategy.analyze.call_count == 1
 
 
-def test_check_handle_timedout_buy_usercustom(default_conf, ticker, limit_buy_order_old, open_trade,
-                                              fee, mocker) -> None:
-    default_conf["unfilledtimeout"] = {"buy": 1400, "sell": 30}
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_handle_timedout_entry_usercustom(
+    default_conf_usdt, ticker_usdt, limit_buy_order_old, open_trade,
+    limit_sell_order_old, fee, mocker, is_short
+) -> None:
+
+    old_order = limit_sell_order_old if is_short else limit_buy_order_old
+    old_order['id'] = open_trade.open_order_id
+
+    default_conf_usdt["unfilledtimeout"] = {"entry": 1400, "exit": 30}
 
     rpc_mock = patch_RPCManager(mocker)
-    cancel_order_mock = MagicMock(return_value=limit_buy_order_old)
-    cancel_buy_order = deepcopy(limit_buy_order_old)
-    cancel_buy_order['status'] = 'canceled'
-    cancel_order_wr_mock = MagicMock(return_value=cancel_buy_order)
+    cancel_order_mock = MagicMock(return_value=old_order)
+    cancel_enter_order = deepcopy(old_order)
+    cancel_enter_order['status'] = 'canceled'
+    cancel_order_wr_mock = MagicMock(return_value=cancel_enter_order)
 
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        fetch_order=MagicMock(return_value=limit_buy_order_old),
+        fetch_ticker=ticker_usdt,
+        fetch_order=MagicMock(return_value=old_order),
         cancel_order_with_result=cancel_order_wr_mock,
         cancel_order=cancel_order_mock,
         get_fee=fee
     )
-    freqtrade = FreqtradeBot(default_conf)
-
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    open_trade.is_short = is_short
+    open_trade.orders[0].side = 'sell' if is_short else 'buy'
+    open_trade.orders[0].ft_order_side = 'sell' if is_short else 'buy'
     Trade.query.session.add(open_trade)
 
     # Ensure default is to return empty (so not mocked yet)
@@ -2013,24 +2399,23 @@ def test_check_handle_timedout_buy_usercustom(default_conf, ticker, limit_buy_or
     assert cancel_order_mock.call_count == 0
 
     # Return false - trade remains open
-    freqtrade.strategy.check_buy_timeout = MagicMock(return_value=False)
+    freqtrade.strategy.check_entry_timeout = MagicMock(return_value=False)
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 0
     trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
     nb_trades = len(trades)
     assert nb_trades == 1
-    assert freqtrade.strategy.check_buy_timeout.call_count == 1
+    assert freqtrade.strategy.check_entry_timeout.call_count == 1
+    freqtrade.strategy.check_entry_timeout = MagicMock(side_effect=KeyError)
 
-    # Raise Keyerror ... (no impact on trade)
-    freqtrade.strategy.check_buy_timeout = MagicMock(side_effect=KeyError)
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 0
     trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
     nb_trades = len(trades)
     assert nb_trades == 1
-    assert freqtrade.strategy.check_buy_timeout.call_count == 1
+    assert freqtrade.strategy.check_entry_timeout.call_count == 1
+    freqtrade.strategy.check_entry_timeout = MagicMock(return_value=True)
 
-    freqtrade.strategy.check_buy_timeout = MagicMock(return_value=True)
     # Trade should be closed since the function returns true
     freqtrade.check_handle_timedout()
     assert cancel_order_wr_mock.call_count == 1
@@ -2038,28 +2423,34 @@ def test_check_handle_timedout_buy_usercustom(default_conf, ticker, limit_buy_or
     trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
     nb_trades = len(trades)
     assert nb_trades == 0
-    assert freqtrade.strategy.check_buy_timeout.call_count == 1
+    assert freqtrade.strategy.check_entry_timeout.call_count == 1
 
 
-def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, open_trade,
-                                   fee, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_handle_timedout_entry(
+    default_conf_usdt, ticker_usdt, limit_buy_order_old, open_trade,
+    limit_sell_order_old, fee, mocker, is_short
+) -> None:
+    old_order = limit_sell_order_old if is_short else limit_buy_order_old
     rpc_mock = patch_RPCManager(mocker)
-    limit_buy_cancel = deepcopy(limit_buy_order_old)
+    old_order['id'] = open_trade.open_order_id
+    limit_buy_cancel = deepcopy(old_order)
     limit_buy_cancel['status'] = 'canceled'
     cancel_order_mock = MagicMock(return_value=limit_buy_cancel)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        fetch_order=MagicMock(return_value=limit_buy_order_old),
+        fetch_ticker=ticker_usdt,
+        fetch_order=MagicMock(return_value=old_order),
         cancel_order_with_result=cancel_order_mock,
         get_fee=fee
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
+    open_trade.is_short = is_short
     Trade.query.session.add(open_trade)
 
-    freqtrade.strategy.check_buy_timeout = MagicMock(return_value=False)
+    freqtrade.strategy.check_entry_timeout = MagicMock(return_value=False)
     # check it does cancel buy orders over the time limit
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 1
@@ -2068,25 +2459,29 @@ def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, op
     nb_trades = len(trades)
     assert nb_trades == 0
     # Custom user buy-timeout is never called
-    assert freqtrade.strategy.check_buy_timeout.call_count == 0
+    assert freqtrade.strategy.check_entry_timeout.call_count == 0
 
 
-def test_check_handle_cancelled_buy(default_conf, ticker, limit_buy_order_old, open_trade,
-                                    fee, mocker, caplog) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_handle_cancelled_buy(
+    default_conf_usdt, ticker_usdt, limit_buy_order_old, open_trade,
+    limit_sell_order_old, fee, mocker, caplog, is_short
+) -> None:
     """ Handle Buy order cancelled on exchange"""
+    old_order = limit_sell_order_old if is_short else limit_buy_order_old
     rpc_mock = patch_RPCManager(mocker)
     cancel_order_mock = MagicMock()
     patch_exchange(mocker)
-    limit_buy_order_old.update({"status": "canceled", 'filled': 0.0})
+    old_order.update({"status": "canceled", 'filled': 0.0})
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        fetch_order=MagicMock(return_value=limit_buy_order_old),
+        fetch_ticker=ticker_usdt,
+        fetch_order=MagicMock(return_value=old_order),
         cancel_order=cancel_order_mock,
         get_fee=fee
     )
-    freqtrade = FreqtradeBot(default_conf)
-
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    open_trade.is_short = is_short
     Trade.query.session.add(open_trade)
 
     # check it does cancel buy orders over the time limit
@@ -2096,24 +2491,28 @@ def test_check_handle_cancelled_buy(default_conf, ticker, limit_buy_order_old, o
     trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
     nb_trades = len(trades)
     assert nb_trades == 0
-    assert log_has_re("Buy order cancelled on exchange for Trade.*", caplog)
+    assert log_has_re(
+        f"{'Sell' if is_short else 'Buy'} order cancelled on exchange for Trade.*", caplog)
 
 
-def test_check_handle_timedout_buy_exception(default_conf, ticker, limit_buy_order_old, open_trade,
-                                             fee, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_handle_timedout_buy_exception(
+    default_conf_usdt, ticker_usdt, open_trade, is_short, fee, mocker
+) -> None:
     rpc_mock = patch_RPCManager(mocker)
     cancel_order_mock = MagicMock()
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         validate_pairs=MagicMock(),
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         fetch_order=MagicMock(side_effect=ExchangeError),
         cancel_order=cancel_order_mock,
         get_fee=fee
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
+    open_trade.is_short = is_short
     Trade.query.session.add(open_trade)
 
     # check it does cancel buy orders over the time limit
@@ -2125,117 +2524,176 @@ def test_check_handle_timedout_buy_exception(default_conf, ticker, limit_buy_ord
     assert nb_trades == 1
 
 
-def test_check_handle_timedout_sell_usercustom(default_conf, ticker, limit_sell_order_old, mocker,
-                                               open_trade) -> None:
-    default_conf["unfilledtimeout"] = {"buy": 1440, "sell": 1440}
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_handle_timedout_exit_usercustom(
+    default_conf_usdt, ticker_usdt, limit_sell_order_old, mocker,
+    is_short, open_trade_usdt, caplog
+) -> None:
+    default_conf_usdt["unfilledtimeout"] = {"entry": 1440, "exit": 1440, "exit_timeout_count": 1}
+    limit_sell_order_old['id'] = open_trade_usdt.open_order_id
+    if is_short:
+        limit_sell_order_old['side'] = 'buy'
+        open_trade_usdt.is_short = is_short
+
     rpc_mock = patch_RPCManager(mocker)
     cancel_order_mock = MagicMock()
     patch_exchange(mocker)
+    et_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.execute_trade_exit')
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         fetch_order=MagicMock(return_value=limit_sell_order_old),
         cancel_order=cancel_order_mock
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
-    open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
-    open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
-    open_trade.close_profit_abs = 0.001
-    open_trade.is_open = False
+    open_trade_usdt.open_date = arrow.utcnow().shift(hours=-5).datetime
+    open_trade_usdt.close_date = arrow.utcnow().shift(minutes=-601).datetime
+    open_trade_usdt.close_profit_abs = 0.001
+    open_trade_usdt.is_open = False
 
-    Trade.query.session.add(open_trade)
+    Trade.query.session.add(open_trade_usdt)
     # Ensure default is false
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 0
 
-    freqtrade.strategy.check_sell_timeout = MagicMock(return_value=False)
+    freqtrade.strategy.check_exit_timeout = MagicMock(return_value=False)
+    freqtrade.strategy.check_entry_timeout = MagicMock(return_value=False)
     # Return false - No impact
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 0
     assert rpc_mock.call_count == 0
-    assert open_trade.is_open is False
-    assert freqtrade.strategy.check_sell_timeout.call_count == 1
+    assert open_trade_usdt.is_open is False
+    assert freqtrade.strategy.check_exit_timeout.call_count == 1
+    assert freqtrade.strategy.check_entry_timeout.call_count == 0
 
-    freqtrade.strategy.check_sell_timeout = MagicMock(side_effect=KeyError)
+    freqtrade.strategy.check_exit_timeout = MagicMock(side_effect=KeyError)
+    freqtrade.strategy.check_entry_timeout = MagicMock(side_effect=KeyError)
     # Return Error - No impact
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 0
     assert rpc_mock.call_count == 0
-    assert open_trade.is_open is False
-    assert freqtrade.strategy.check_sell_timeout.call_count == 1
+    assert open_trade_usdt.is_open is False
+    assert freqtrade.strategy.check_exit_timeout.call_count == 1
+    assert freqtrade.strategy.check_entry_timeout.call_count == 0
 
     # Return True - sells!
-    freqtrade.strategy.check_sell_timeout = MagicMock(return_value=True)
+    freqtrade.strategy.check_exit_timeout = MagicMock(return_value=True)
+    freqtrade.strategy.check_entry_timeout = MagicMock(return_value=True)
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 1
     assert rpc_mock.call_count == 1
-    assert open_trade.is_open is True
-    assert freqtrade.strategy.check_sell_timeout.call_count == 1
+    assert open_trade_usdt.is_open is True
+    assert freqtrade.strategy.check_exit_timeout.call_count == 1
+    assert freqtrade.strategy.check_entry_timeout.call_count == 0
+
+    # 2nd canceled trade - Fail execute sell
+    caplog.clear()
+    open_trade_usdt.open_order_id = limit_sell_order_old['id']
+    mocker.patch('freqtrade.persistence.Trade.get_exit_order_count', return_value=1)
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.execute_trade_exit',
+                 side_effect=DependencyException)
+    freqtrade.check_handle_timedout()
+    assert log_has_re('Unable to emergency sell .*', caplog)
+
+    et_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.execute_trade_exit')
+    caplog.clear()
+    # 2nd canceled trade ...
+    open_trade_usdt.open_order_id = limit_sell_order_old['id']
+
+    # If cancelling fails - no emergency sell!
+    with patch('freqtrade.freqtradebot.FreqtradeBot.handle_cancel_exit', return_value=False):
+        freqtrade.check_handle_timedout()
+        assert et_mock.call_count == 0
+
+    freqtrade.check_handle_timedout()
+    assert log_has_re('Emergency exiting trade.*', caplog)
+    assert et_mock.call_count == 1
 
 
-def test_check_handle_timedout_sell(default_conf, ticker, limit_sell_order_old, mocker,
-                                    open_trade) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_handle_timedout_exit(
+    default_conf_usdt, ticker_usdt, limit_sell_order_old, mocker, is_short, open_trade_usdt
+) -> None:
     rpc_mock = patch_RPCManager(mocker)
     cancel_order_mock = MagicMock()
+    limit_sell_order_old['id'] = open_trade_usdt.open_order_id
+    limit_sell_order_old['side'] = 'buy' if is_short else 'sell'
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         fetch_order=MagicMock(return_value=limit_sell_order_old),
         cancel_order=cancel_order_mock
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
-    open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
-    open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
-    open_trade.close_profit_abs = 0.001
-    open_trade.is_open = False
+    open_trade_usdt.open_date = arrow.utcnow().shift(hours=-5).datetime
+    open_trade_usdt.close_date = arrow.utcnow().shift(minutes=-601).datetime
+    open_trade_usdt.close_profit_abs = 0.001
+    open_trade_usdt.is_open = False
+    open_trade_usdt.is_short = is_short
 
-    Trade.query.session.add(open_trade)
+    Trade.query.session.add(open_trade_usdt)
 
-    freqtrade.strategy.check_sell_timeout = MagicMock(return_value=False)
+    freqtrade.strategy.check_exit_timeout = MagicMock(return_value=False)
+    freqtrade.strategy.check_entry_timeout = MagicMock(return_value=False)
     # check it does cancel sell orders over the time limit
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 1
     assert rpc_mock.call_count == 1
-    assert open_trade.is_open is True
+    assert open_trade_usdt.is_open is True
     # Custom user sell-timeout is never called
-    assert freqtrade.strategy.check_sell_timeout.call_count == 0
+    assert freqtrade.strategy.check_exit_timeout.call_count == 0
+    assert freqtrade.strategy.check_entry_timeout.call_count == 0
 
 
-def test_check_handle_cancelled_sell(default_conf, ticker, limit_sell_order_old, open_trade,
-                                     mocker, caplog) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_handle_cancelled_exit(
+    default_conf_usdt, ticker_usdt, limit_sell_order_old, open_trade_usdt,
+    is_short, mocker, caplog
+) -> None:
     """ Handle sell order cancelled on exchange"""
     rpc_mock = patch_RPCManager(mocker)
     cancel_order_mock = MagicMock()
     limit_sell_order_old.update({"status": "canceled", 'filled': 0.0})
+    limit_sell_order_old['side'] = 'buy' if is_short else 'sell'
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         fetch_order=MagicMock(return_value=limit_sell_order_old),
         cancel_order_with_result=cancel_order_mock
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
-    open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
-    open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
-    open_trade.is_open = False
+    open_trade_usdt.open_date = arrow.utcnow().shift(hours=-5).datetime
+    open_trade_usdt.close_date = arrow.utcnow().shift(minutes=-601).datetime
+    open_trade_usdt.is_open = False
+    open_trade_usdt.is_short = is_short
 
-    Trade.query.session.add(open_trade)
+    Trade.query.session.add(open_trade_usdt)
 
     # check it does cancel sell orders over the time limit
     freqtrade.check_handle_timedout()
     assert cancel_order_mock.call_count == 0
     assert rpc_mock.call_count == 1
-    assert open_trade.is_open is True
-    assert log_has_re("Sell order cancelled on exchange for Trade.*", caplog)
+    assert open_trade_usdt.is_open is True
+    exit_name = 'Buy' if is_short else 'Sell'
+    assert log_has_re(f"{exit_name} order cancelled on exchange for Trade.*", caplog)
 
 
-def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old_partial,
-                                       open_trade, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+@pytest.mark.parametrize("leverage", [1, 3, 5, 10])
+def test_check_handle_timedout_partial(
+    default_conf_usdt, ticker_usdt, limit_buy_order_old_partial, is_short, leverage,
+    open_trade, mocker
+) -> None:
     rpc_mock = patch_RPCManager(mocker)
+    open_trade.is_short = is_short
+    open_trade.leverage = leverage
+    limit_buy_order_old_partial['id'] = open_trade.open_order_id
+    limit_buy_order_old_partial['side'] = 'sell' if is_short else 'buy'
     limit_buy_canceled = deepcopy(limit_buy_order_old_partial)
     limit_buy_canceled['status'] = 'canceled'
 
@@ -2243,12 +2701,12 @@ def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         fetch_order=MagicMock(return_value=limit_buy_order_old_partial),
         cancel_order_with_result=cancel_order_mock
     )
-    freqtrade = FreqtradeBot(default_conf)
-
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    prior_stake = open_trade.stake_amount
     Trade.query.session.add(open_trade)
 
     # check it does cancel buy orders over the time limit
@@ -2259,24 +2717,35 @@ def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old
     trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
     assert len(trades) == 1
     assert trades[0].amount == 23.0
-    assert trades[0].stake_amount == open_trade.open_rate * trades[0].amount
+    assert trades[0].stake_amount == open_trade.open_rate * trades[0].amount / leverage
+    assert trades[0].stake_amount != prior_stake
 
 
-def test_check_handle_timedout_partial_fee(default_conf, ticker, open_trade, caplog, fee,
-                                           limit_buy_order_old_partial, trades_for_order,
-                                           limit_buy_order_old_partial_canceled, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_handle_timedout_partial_fee(
+    default_conf_usdt, ticker_usdt, open_trade, caplog, fee, is_short,
+    limit_buy_order_old_partial, trades_for_order,
+    limit_buy_order_old_partial_canceled, mocker
+) -> None:
+    open_trade.is_short = is_short
+    open_trade.orders[0].ft_order_side = 'sell' if is_short else 'buy'
     rpc_mock = patch_RPCManager(mocker)
+    limit_buy_order_old_partial['id'] = open_trade.open_order_id
+    limit_buy_order_old_partial_canceled['id'] = open_trade.open_order_id
+    limit_buy_order_old_partial['side'] = 'sell' if is_short else 'buy'
+    limit_buy_order_old_partial_canceled['side'] = 'sell' if is_short else 'buy'
+
     cancel_order_mock = MagicMock(return_value=limit_buy_order_old_partial_canceled)
     mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=0))
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         fetch_order=MagicMock(return_value=limit_buy_order_old_partial),
         cancel_order_with_result=cancel_order_mock,
         get_trades_for_order=MagicMock(return_value=trades_for_order),
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
     assert open_trade.amount == limit_buy_order_old_partial['amount']
 
@@ -2297,26 +2766,34 @@ def test_check_handle_timedout_partial_fee(default_conf, ticker, open_trade, cap
     assert trades[0].amount == (limit_buy_order_old_partial['amount'] -
                                 limit_buy_order_old_partial['remaining']) - 0.023
     assert trades[0].open_order_id is None
-    assert trades[0].fee_updated('buy')
+    assert trades[0].fee_updated(open_trade.entry_side)
     assert pytest.approx(trades[0].fee_open) == 0.001
 
 
-def test_check_handle_timedout_partial_except(default_conf, ticker, open_trade, caplog, fee,
-                                              limit_buy_order_old_partial, trades_for_order,
-                                              limit_buy_order_old_partial_canceled, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_handle_timedout_partial_except(
+    default_conf_usdt, ticker_usdt, open_trade, caplog, fee, is_short,
+    limit_buy_order_old_partial, trades_for_order,
+    limit_buy_order_old_partial_canceled, mocker
+) -> None:
+    open_trade.is_short = is_short
     rpc_mock = patch_RPCManager(mocker)
+    limit_buy_order_old_partial_canceled['id'] = open_trade.open_order_id
+    limit_buy_order_old_partial['id'] = open_trade.open_order_id
+    if is_short:
+        limit_buy_order_old_partial['side'] = 'sell'
     cancel_order_mock = MagicMock(return_value=limit_buy_order_old_partial_canceled)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         fetch_order=MagicMock(return_value=limit_buy_order_old_partial),
         cancel_order_with_result=cancel_order_mock,
         get_trades_for_order=MagicMock(return_value=trades_for_order),
     )
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
                  MagicMock(side_effect=DependencyException))
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
     assert open_trade.amount == limit_buy_order_old_partial['amount']
 
@@ -2341,7 +2818,8 @@ def test_check_handle_timedout_partial_except(default_conf, ticker, open_trade,
     assert trades[0].fee_open == fee()
 
 
-def test_check_handle_timedout_exception(default_conf, ticker, open_trade, mocker, caplog) -> None:
+def test_check_handle_timedout_exception(default_conf_usdt, ticker_usdt, open_trade_usdt, mocker,
+                                         caplog) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     cancel_order_mock = MagicMock()
@@ -2353,68 +2831,78 @@ def test_check_handle_timedout_exception(default_conf, ticker, open_trade, mocke
     )
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         fetch_order=MagicMock(side_effect=ExchangeError('Oh snap')),
         cancel_order=cancel_order_mock
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
-    Trade.query.session.add(open_trade)
+    Trade.query.session.add(open_trade_usdt)
 
+    caplog.clear()
     freqtrade.check_handle_timedout()
-    assert log_has_re(r"Cannot query order for Trade\(id=1, pair=ETH/BTC, amount=90.99181073, "
-                      r"open_rate=0.00001099, open_since="
-                      f"{open_trade.open_date.strftime('%Y-%m-%d %H:%M:%S')}"
+    assert log_has_re(r"Cannot query order for Trade\(id=1, pair=ADA/USDT, amount=30.00000000, "
+                      r"is_short=False, leverage=1.0, "
+                      r"open_rate=2.00000000, open_since="
+                      f"{open_trade_usdt.open_date.strftime('%Y-%m-%d %H:%M:%S')}"
                       r"\) due to Traceback \(most recent call last\):\n*",
                       caplog)
 
 
-def test_handle_cancel_enter(mocker, caplog, default_conf, limit_buy_order) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_cancel_enter(mocker, caplog, default_conf_usdt, limit_order, is_short) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    cancel_buy_order = deepcopy(limit_buy_order)
+    l_order = limit_order[entry_side(is_short)]
+    cancel_buy_order = deepcopy(limit_order[entry_side(is_short)])
     cancel_buy_order['status'] = 'canceled'
     del cancel_buy_order['filled']
 
     cancel_order_mock = MagicMock(return_value=cancel_buy_order)
     mocker.patch('freqtrade.exchange.Exchange.cancel_order_with_result', cancel_order_mock)
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     freqtrade._notify_enter_cancel = MagicMock()
 
     trade = MagicMock()
     trade.pair = 'LTC/USDT'
     trade.open_rate = 200
-    limit_buy_order['filled'] = 0.0
-    limit_buy_order['status'] = 'open'
+    trade.is_short = False
+    trade.entry_side = "buy"
+    l_order['filled'] = 0.0
+    l_order['status'] = 'open'
     reason = CANCEL_REASON['TIMEOUT']
-    assert freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
+    assert freqtrade.handle_cancel_enter(trade, l_order, reason)
     assert cancel_order_mock.call_count == 1
 
     cancel_order_mock.reset_mock()
     caplog.clear()
-    limit_buy_order['filled'] = 0.01
-    assert not freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
+    l_order['filled'] = 0.01
+    assert not freqtrade.handle_cancel_enter(trade, l_order, reason)
     assert cancel_order_mock.call_count == 0
-    assert log_has_re("Order .* for .* not cancelled, as the filled amount.* unsellable.*", caplog)
+    assert log_has_re("Order .* for .* not cancelled, as the filled amount.* unexitable.*", caplog)
 
     caplog.clear()
     cancel_order_mock.reset_mock()
-    limit_buy_order['filled'] = 2
-    assert not freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
+    l_order['filled'] = 2
+    assert not freqtrade.handle_cancel_enter(trade, l_order, reason)
     assert cancel_order_mock.call_count == 1
 
     # Order remained open for some reason (cancel failed)
     cancel_buy_order['status'] = 'open'
     cancel_order_mock = MagicMock(return_value=cancel_buy_order)
     mocker.patch('freqtrade.exchange.Exchange.cancel_order_with_result', cancel_order_mock)
-    assert not freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
+    assert not freqtrade.handle_cancel_enter(trade, l_order, reason)
     assert log_has_re(r"Order .* for .* not cancelled.", caplog)
+    # min_pair_stake empty should not crash
+    mocker.patch('freqtrade.exchange.Exchange.get_min_pair_stake_amount', return_value=None)
+    assert not freqtrade.handle_cancel_enter(trade, limit_order[entry_side(is_short)], reason)
 
 
+@pytest.mark.parametrize("is_short", [False, True])
 @pytest.mark.parametrize("limit_buy_order_canceled_empty", ['binance', 'ftx', 'kraken', 'bittrex'],
                          indirect=['limit_buy_order_canceled_empty'])
-def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf,
+def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf_usdt, is_short,
                                        limit_buy_order_canceled_empty) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
@@ -2422,52 +2910,61 @@ def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf,
         'freqtrade.exchange.Exchange.cancel_order_with_result',
         return_value=limit_buy_order_canceled_empty)
     nofiy_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot._notify_enter_cancel')
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
     reason = CANCEL_REASON['TIMEOUT']
     trade = MagicMock()
     trade.pair = 'LTC/ETH'
+    trade.entry_side = "sell" if is_short else "buy"
     assert freqtrade.handle_cancel_enter(trade, limit_buy_order_canceled_empty, reason)
     assert cancel_order_mock.call_count == 0
-    assert log_has_re(r'Buy order fully cancelled. Removing .* from database\.', caplog)
+    assert log_has_re(
+        f'{trade.entry_side.capitalize()} order fully cancelled. '
+        r'Removing .* from database\.',
+        caplog
+    )
     assert nofiy_mock.call_count == 1
 
 
+@pytest.mark.parametrize("is_short", [False, True])
 @pytest.mark.parametrize('cancelorder', [
     {},
     {'remaining': None},
     'String Return value',
     123
 ])
-def test_handle_cancel_enter_corder_empty(mocker, default_conf, limit_buy_order,
+def test_handle_cancel_enter_corder_empty(mocker, default_conf_usdt, limit_order, is_short,
                                           cancelorder) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
+    l_order = limit_order[entry_side(is_short)]
     cancel_order_mock = MagicMock(return_value=cancelorder)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         cancel_order=cancel_order_mock
     )
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     freqtrade._notify_enter_cancel = MagicMock()
 
     trade = MagicMock()
     trade.pair = 'LTC/USDT'
+    trade.entry_side = "buy"
     trade.open_rate = 200
-    limit_buy_order['filled'] = 0.0
-    limit_buy_order['status'] = 'open'
+    trade.entry_side = "buy"
+    l_order['filled'] = 0.0
+    l_order['status'] = 'open'
     reason = CANCEL_REASON['TIMEOUT']
-    assert freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
+    assert freqtrade.handle_cancel_enter(trade, l_order, reason)
     assert cancel_order_mock.call_count == 1
 
     cancel_order_mock.reset_mock()
-    limit_buy_order['filled'] = 1.0
-    assert not freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
+    l_order['filled'] = 1.0
+    assert not freqtrade.handle_cancel_enter(trade, l_order, reason)
     assert cancel_order_mock.call_count == 1
 
 
-def test_handle_cancel_exit_limit(mocker, default_conf, fee) -> None:
+def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None:
     send_msg_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     cancel_order_mock = MagicMock()
@@ -2477,7 +2974,7 @@ def test_handle_cancel_exit_limit(mocker, default_conf, fee) -> None:
     )
     mocker.patch('freqtrade.exchange.Exchange.get_rate', return_value=0.245441)
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
     trade = Trade(
         pair='LTC/ETH',
@@ -2485,9 +2982,12 @@ def test_handle_cancel_exit_limit(mocker, default_conf, fee) -> None:
         exchange='binance',
         open_rate=0.245441,
         open_order_id="123456",
-        open_date=arrow.utcnow().datetime,
+        open_date=arrow.utcnow().shift(days=-2).datetime,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
+        close_rate=0.555,
+        close_date=arrow.utcnow().datetime,
+        exit_reason="sell_reason_whatever",
     )
     order = {'remaining': 1,
              'amount': 1,
@@ -2496,50 +2996,61 @@ def test_handle_cancel_exit_limit(mocker, default_conf, fee) -> None:
     assert freqtrade.handle_cancel_exit(trade, order, reason)
     assert cancel_order_mock.call_count == 1
     assert send_msg_mock.call_count == 1
+    assert trade.close_rate is None
+    assert trade.exit_reason is None
 
     send_msg_mock.reset_mock()
 
     order['amount'] = 2
-    assert freqtrade.handle_cancel_exit(trade, order, reason
-                                        ) == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
+    assert not freqtrade.handle_cancel_exit(trade, order, reason)
     # Assert cancel_order was not called (callcount remains unchanged)
     assert cancel_order_mock.call_count == 1
     assert send_msg_mock.call_count == 1
-    assert freqtrade.handle_cancel_exit(trade, order, reason
-                                        ) == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
+    assert (send_msg_mock.call_args_list[0][0][0]['reason']
+            == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN'])
+
+    assert not freqtrade.handle_cancel_exit(trade, order, reason)
+
+    send_msg_mock.call_args_list[0][0][0]['reason'] = CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
+
     # Message should not be iterated again
-    assert trade.sell_order_status == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
+    assert trade.exit_order_status == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
     assert send_msg_mock.call_count == 1
 
 
-def test_handle_cancel_exit_cancel_exception(mocker, default_conf) -> None:
+def test_handle_cancel_exit_cancel_exception(mocker, default_conf_usdt) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch(
         'freqtrade.exchange.Exchange.cancel_order_with_result', side_effect=InvalidOrderException())
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
     trade = MagicMock()
     reason = CANCEL_REASON['TIMEOUT']
     order = {'remaining': 1,
              'amount': 1,
              'status': "open"}
-    assert freqtrade.handle_cancel_exit(trade, order, reason) == 'error cancelling order'
+    assert not freqtrade.handle_cancel_exit(trade, order, reason)
 
 
-def test_execute_trade_exit_up(default_conf, ticker, fee, ticker_sell_up, mocker) -> None:
+@pytest.mark.parametrize("is_short, open_rate, amt", [
+    (False, 2.0, 30.0),
+    (True, 2.02, 29.70297029),
+])
+def test_execute_trade_exit_up(default_conf_usdt, ticker_usdt, fee, ticker_usdt_sell_up, mocker,
+                               ticker_usdt_sell_down, is_short, open_rate, amt) -> None:
     rpc_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         _is_dry_limit_order_filled=MagicMock(return_value=False),
     )
-    patch_whitelist(mocker, default_conf)
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    patch_whitelist(mocker, default_conf_usdt)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=False)
 
     # Create some test data
@@ -2547,116 +3058,145 @@ def test_execute_trade_exit_up(default_conf, ticker, fee, ticker_sell_up, mocker
     rpc_mock.reset_mock()
 
     trade = Trade.query.first()
+    assert trade.is_short == is_short
     assert trade
     assert freqtrade.strategy.confirm_trade_exit.call_count == 0
 
     # Increase the price and sell it
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker_sell_up
+        fetch_ticker=ticker_usdt_sell_down if is_short else ticker_usdt_sell_up
     )
     # Prevented sell ...
-    freqtrade.execute_trade_exit(trade=trade, limit=ticker_sell_up()['bid'],
-                                 sell_reason=SellCheckTuple(sell_type=SellType.ROI))
+    freqtrade.execute_trade_exit(
+        trade=trade,
+        limit=(ticker_usdt_sell_down()['ask'] if is_short else ticker_usdt_sell_up()['bid']),
+        exit_check=ExitCheckTuple(exit_type=ExitType.ROI)
+    )
     assert rpc_mock.call_count == 0
     assert freqtrade.strategy.confirm_trade_exit.call_count == 1
+    assert id(freqtrade.strategy.confirm_trade_exit.call_args_list[0][1]['trade']) != id(trade)
+    assert freqtrade.strategy.confirm_trade_exit.call_args_list[0][1]['trade'].id == trade.id
 
     # Repatch with true
     freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=True)
-
-    freqtrade.execute_trade_exit(trade=trade, limit=ticker_sell_up()['bid'],
-                                 sell_reason=SellCheckTuple(sell_type=SellType.ROI))
+    freqtrade.execute_trade_exit(
+        trade=trade,
+        limit=(ticker_usdt_sell_down()['ask'] if is_short else ticker_usdt_sell_up()['bid']),
+        exit_check=ExitCheckTuple(exit_type=ExitType.ROI)
+    )
     assert freqtrade.strategy.confirm_trade_exit.call_count == 1
 
     assert rpc_mock.call_count == 1
     last_msg = rpc_mock.call_args_list[-1][0][0]
     assert {
         'trade_id': 1,
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'exchange': 'Binance',
-        'pair': 'ETH/BTC',
+        'pair': 'ETH/USDT',
         'gain': 'profit',
-        'limit': 1.172e-05,
-        'amount': 91.07468123,
+        'limit': 2.0 if is_short else 2.2,
+        'amount': pytest.approx(amt),
         'order_type': 'limit',
-        'open_rate': 1.098e-05,
-        'current_rate': 1.173e-05,
-        'profit_amount': 6.223e-05,
-        'profit_ratio': 0.0620716,
-        'stake_currency': 'BTC',
+        'buy_tag': None,
+        'direction': 'Short' if trade.is_short else 'Long',
+        'leverage': 1.0,
+        'enter_tag': None,
+        'open_rate': open_rate,
+        'current_rate': 2.01 if is_short else 2.3,
+        'profit_amount': 0.29554455 if is_short else 5.685,
+        'profit_ratio': 0.00493809 if is_short else 0.09451372,
+        'stake_currency': 'USDT',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.ROI.value,
+        'sell_reason': ExitType.ROI.value,
+        'exit_reason': ExitType.ROI.value,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
     } == last_msg
 
 
-def test_execute_trade_exit_down(default_conf, ticker, fee, ticker_sell_down, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_execute_trade_exit_down(default_conf_usdt, ticker_usdt, fee, ticker_usdt_sell_down,
+                                 ticker_usdt_sell_up, mocker, is_short) -> None:
     rpc_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         _is_dry_limit_order_filled=MagicMock(return_value=False),
     )
-    patch_whitelist(mocker, default_conf)
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    patch_whitelist(mocker, default_conf_usdt)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     # Create some test data
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
 
     # Decrease the price and sell it
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker_sell_down
+        fetch_ticker=ticker_usdt_sell_up if is_short else ticker_usdt_sell_down
     )
-
-    freqtrade.execute_trade_exit(trade=trade, limit=ticker_sell_down()['bid'],
-                                 sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
+    freqtrade.execute_trade_exit(
+        trade=trade, limit=(ticker_usdt_sell_up if is_short else ticker_usdt_sell_down)()['bid'],
+        exit_check=ExitCheckTuple(exit_type=ExitType.STOP_LOSS))
 
     assert rpc_mock.call_count == 2
     last_msg = rpc_mock.call_args_list[-1][0][0]
     assert {
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'trade_id': 1,
         'exchange': 'Binance',
-        'pair': 'ETH/BTC',
+        'pair': 'ETH/USDT',
+        'direction': 'Short' if trade.is_short else 'Long',
+        'leverage': 1.0,
         'gain': 'loss',
-        'limit': 1.044e-05,
-        'amount': 91.07468123,
+        'limit': 2.2 if is_short else 2.01,
+        'amount': pytest.approx(29.70297029) if is_short else 30.0,
         'order_type': 'limit',
-        'open_rate': 1.098e-05,
-        'current_rate': 1.043e-05,
-        'profit_amount': -5.406e-05,
-        'profit_ratio': -0.05392257,
-        'stake_currency': 'BTC',
+        'buy_tag': None,
+        'enter_tag': None,
+        'open_rate': 2.02 if is_short else 2.0,
+        'current_rate': 2.2 if is_short else 2.0,
+        'profit_amount': -5.65990099 if is_short else -0.00075,
+        'profit_ratio': -0.0945681 if is_short else -1.247e-05,
+        'stake_currency': 'USDT',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.STOP_LOSS.value,
+        'sell_reason': ExitType.STOP_LOSS.value,
+        'exit_reason': ExitType.STOP_LOSS.value,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
     } == last_msg
 
 
-def test_execute_trade_exit_custom_exit_price(default_conf, ticker, fee, ticker_sell_up,
-                                              mocker) -> None:
+@pytest.mark.parametrize(
+    "is_short,amount,open_rate,current_rate,limit,profit_amount,profit_ratio,profit_or_loss", [
+        (False, 30, 2.0, 2.3, 2.25, 7.18125, 0.11938903, 'profit'),
+        (True, 29.70297029, 2.02, 2.2, 2.25, -7.14876237, -0.11944465, 'loss'),
+    ])
+def test_execute_trade_exit_custom_exit_price(
+        default_conf_usdt, ticker_usdt, fee, ticker_usdt_sell_up, is_short, amount, open_rate,
+        current_rate, limit, profit_amount, profit_ratio, profit_or_loss, mocker) -> None:
     rpc_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         _is_dry_limit_order_filled=MagicMock(return_value=False),
     )
-    patch_whitelist(mocker, default_conf)
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    config = deepcopy(default_conf_usdt)
+    config['custom_price_max_distance_ratio'] = 0.1
+    patch_whitelist(mocker, config)
+    freqtrade = FreqtradeBot(config)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=False)
 
     # Create some test data
@@ -2664,22 +3204,25 @@ def test_execute_trade_exit_custom_exit_price(default_conf, ticker, fee, ticker_
     rpc_mock.reset_mock()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
     assert freqtrade.strategy.confirm_trade_exit.call_count == 0
 
     # Increase the price and sell it
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker_sell_up
+        fetch_ticker=ticker_usdt_sell_up
     )
 
     freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=True)
 
     # Set a custom exit price
-    freqtrade.strategy.custom_exit_price = lambda **kwargs: 1.170e-05
-
-    freqtrade.execute_trade_exit(trade=trade, limit=ticker_sell_up()['bid'],
-                                 sell_reason=SellCheckTuple(sell_type=SellType.SELL_SIGNAL))
+    freqtrade.strategy.custom_exit_price = lambda **kwargs: 2.25
+    freqtrade.execute_trade_exit(
+        trade=trade,
+        limit=ticker_usdt_sell_up()['ask' if is_short else 'bid'],
+        exit_check=ExitCheckTuple(exit_type=ExitType.EXIT_SIGNAL)
+    )
 
     # Sell price must be different to default bid price
 
@@ -2689,79 +3232,93 @@ def test_execute_trade_exit_custom_exit_price(default_conf, ticker, fee, ticker_
     last_msg = rpc_mock.call_args_list[-1][0][0]
     assert {
         'trade_id': 1,
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'exchange': 'Binance',
-        'pair': 'ETH/BTC',
-        'gain': 'profit',
-        'limit': 1.170e-05,
-        'amount': 91.07468123,
+        'pair': 'ETH/USDT',
+        'direction': 'Short' if trade.is_short else 'Long',
+        'leverage': 1.0,
+        'gain': profit_or_loss,
+        'limit': limit,
+        'amount': pytest.approx(amount),
         'order_type': 'limit',
-        'open_rate': 1.098e-05,
-        'current_rate': 1.173e-05,
-        'profit_amount': 6.041e-05,
-        'profit_ratio': 0.06025919,
-        'stake_currency': 'BTC',
+        'buy_tag': None,
+        'enter_tag': None,
+        'open_rate': open_rate,
+        'current_rate': current_rate,
+        'profit_amount': pytest.approx(profit_amount),
+        'profit_ratio': profit_ratio,
+        'stake_currency': 'USDT',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.SELL_SIGNAL.value,
+        'sell_reason': ExitType.EXIT_SIGNAL.value,
+        'exit_reason': ExitType.EXIT_SIGNAL.value,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
     } == last_msg
 
 
-def test_execute_trade_exit_down_stoploss_on_exchange_dry_run(default_conf, ticker, fee,
-                                                              ticker_sell_down, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_execute_trade_exit_down_stoploss_on_exchange_dry_run(
+        default_conf_usdt, ticker_usdt, fee, is_short, ticker_usdt_sell_down,
+        ticker_usdt_sell_up, mocker) -> None:
     rpc_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         _is_dry_limit_order_filled=MagicMock(return_value=False),
     )
-    patch_whitelist(mocker, default_conf)
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    patch_whitelist(mocker, default_conf_usdt)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     # Create some test data
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    assert trade.is_short == is_short
     assert trade
 
     # Decrease the price and sell it
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker_sell_down
+        fetch_ticker=ticker_usdt_sell_up if is_short else ticker_usdt_sell_down
     )
 
-    default_conf['dry_run'] = True
+    default_conf_usdt['dry_run'] = True
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
     # Setting trade stoploss to 0.01
 
-    trade.stop_loss = 0.00001099 * 0.99
-    freqtrade.execute_trade_exit(trade=trade, limit=ticker_sell_down()['bid'],
-                                 sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
+    trade.stop_loss = 2.0 * 1.01 if is_short else 2.0 * 0.99
+    freqtrade.execute_trade_exit(
+        trade=trade, limit=(ticker_usdt_sell_up if is_short else ticker_usdt_sell_down())['bid'],
+        exit_check=ExitCheckTuple(exit_type=ExitType.STOP_LOSS))
 
     assert rpc_mock.call_count == 2
     last_msg = rpc_mock.call_args_list[-1][0][0]
 
     assert {
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'trade_id': 1,
         'exchange': 'Binance',
-        'pair': 'ETH/BTC',
+        'pair': 'ETH/USDT',
+        'direction': 'Short' if trade.is_short else 'Long',
+        'leverage': 1.0,
         'gain': 'loss',
-        'limit': 1.08801e-05,
-        'amount': 91.07468123,
+        'limit': 2.02 if is_short else 1.98,
+        'amount': pytest.approx(29.70297029 if is_short else 30.0),
         'order_type': 'limit',
-        'open_rate': 1.098e-05,
-        'current_rate': 1.043e-05,
-        'profit_amount': -1.408e-05,
-        'profit_ratio': -0.01404051,
-        'stake_currency': 'BTC',
+        'buy_tag': None,
+        'enter_tag': None,
+        'open_rate': 2.02 if is_short else 2.0,
+        'current_rate': 2.2 if is_short else 2.0,
+        'profit_amount': -0.3 if is_short else -0.8985,
+        'profit_ratio': -0.00501253 if is_short else -0.01493766,
+        'stake_currency': 'USDT',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.STOP_LOSS.value,
+        'sell_reason': ExitType.STOP_LOSS.value,
+        'exit_reason': ExitType.STOP_LOSS.value,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
@@ -2769,8 +3326,8 @@ def test_execute_trade_exit_down_stoploss_on_exchange_dry_run(default_conf, tick
 
 
 def test_execute_trade_exit_sloe_cancel_exception(
-        mocker, default_conf, ticker, fee, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+        mocker, default_conf_usdt, ticker_usdt, fee, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order',
                  side_effect=InvalidOrderException())
     mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=300))
@@ -2781,7 +3338,7 @@ def test_execute_trade_exit_sloe_cancel_exception(
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         create_order=create_order_mock,
     )
@@ -2797,15 +3354,16 @@ def test_execute_trade_exit_sloe_cancel_exception(
     trade.stoploss_order_id = "abcd"
 
     freqtrade.execute_trade_exit(trade=trade, limit=1234,
-                                 sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
+                                 exit_check=ExitCheckTuple(exit_type=ExitType.STOP_LOSS))
     assert create_order_mock.call_count == 2
     assert log_has('Could not cancel stoploss order abcd', caplog)
 
 
-def test_execute_trade_exit_with_stoploss_on_exchange(default_conf, ticker, fee, ticker_sell_up,
-                                                      mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_execute_trade_exit_with_stoploss_on_exchange(
+        default_conf_usdt, ticker_usdt, fee, ticker_usdt_sell_up, is_short, mocker) -> None:
 
-    default_conf['exchange']['name'] = 'binance'
+    default_conf_usdt['exchange']['name'] = 'binance'
     rpc_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     stoploss = MagicMock(return_value={
@@ -2818,7 +3376,7 @@ def test_execute_trade_exit_with_stoploss_on_exchange(default_conf, ticker, fee,
     cancel_order = MagicMock(return_value=True)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         amount_to_precision=lambda s, x, y: y,
         price_to_precision=lambda s, x, y: y,
@@ -2827,14 +3385,15 @@ def test_execute_trade_exit_with_stoploss_on_exchange(default_conf, ticker, fee,
         _is_dry_limit_order_filled=MagicMock(side_effect=[True, False]),
     )
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-    patch_get_signal(freqtrade)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     # Create some test data
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
     trades = [trade]
 
@@ -2844,26 +3403,31 @@ def test_execute_trade_exit_with_stoploss_on_exchange(default_conf, ticker, fee,
     # Increase the price and sell it
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker_sell_up
+        fetch_ticker=ticker_usdt_sell_up
     )
 
-    freqtrade.execute_trade_exit(trade=trade, limit=ticker_sell_up()['bid'],
-                                 sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
+    freqtrade.execute_trade_exit(
+        trade=trade,
+        limit=ticker_usdt_sell_up()['ask' if is_short else 'bid'],
+        exit_check=ExitCheckTuple(exit_type=ExitType.STOP_LOSS)
+    )
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
     assert cancel_order.call_count == 1
     assert rpc_mock.call_count == 3
 
 
-def test_may_execute_trade_exit_after_stoploss_on_exchange_hit(default_conf, ticker, fee,
-                                                               mocker) -> None:
-    default_conf['exchange']['name'] = 'binance'
+@pytest.mark.parametrize("is_short", [False, True])
+def test_may_execute_trade_exit_after_stoploss_on_exchange_hit(
+        default_conf_usdt, ticker_usdt, fee, mocker, is_short) -> None:
+    default_conf_usdt['exchange']['name'] = 'binance'
     rpc_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         amount_to_precision=lambda s, x, y: y,
         price_to_precision=lambda s, x, y: y,
@@ -2879,9 +3443,9 @@ def test_may_execute_trade_exit_after_stoploss_on_exchange_hit(default_conf, tic
 
     mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-    patch_get_signal(freqtrade)
+    patch_get_signal(freqtrade, enter_long=not is_short, enter_short=is_short)
 
     # Create some test data
     freqtrade.enter_positions()
@@ -2895,7 +3459,7 @@ def test_may_execute_trade_exit_after_stoploss_on_exchange_hit(default_conf, tic
     assert trade.stoploss_order_id == '123'
     assert trade.open_order_id is None
 
-    # Assuming stoploss on exchnage is hit
+    # Assuming stoploss on exchange is hit
     # stoploss_order_id should become None
     # and trade should be sold at the price of stoploss
     stoploss_executed = MagicMock(return_value={
@@ -2921,64 +3485,98 @@ def test_may_execute_trade_exit_after_stoploss_on_exchange_hit(default_conf, tic
     freqtrade.exit_positions(trades)
     assert trade.stoploss_order_id is None
     assert trade.is_open is False
-    assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
+    assert trade.exit_reason == ExitType.STOPLOSS_ON_EXCHANGE.value
     assert rpc_mock.call_count == 3
-    assert rpc_mock.call_args_list[0][0][0]['type'] == RPCMessageType.BUY
-    assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.BUY_FILL
-    assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.SELL
+    assert rpc_mock.call_args_list[0][0][0]['type'] == RPCMessageType.ENTRY
+    assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.ENTRY_FILL
+    assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.EXIT
 
 
-def test_execute_trade_exit_market_order(default_conf, ticker, fee,
-                                         ticker_sell_up, mocker) -> None:
+@pytest.mark.parametrize(
+    "is_short,amount,current_rate,limit,profit_amount,profit_ratio,profit_or_loss", [
+        (False, 30, 2.3, 2.2, 5.685, 0.09451372, 'profit'),
+        (True, 29.70297029, 2.2, 2.3, -8.63762376, -0.1443212, 'loss'),
+    ])
+def test_execute_trade_exit_market_order(
+    default_conf_usdt, ticker_usdt, fee, is_short, current_rate, amount,
+    limit, profit_amount, profit_ratio, profit_or_loss, ticker_usdt_sell_up, mocker
+) -> None:
+    """
+    amount
+        long: 60 / 2.0 = 30
+        short: 60 / 2.02 = 29.70297029
+    open_value
+        long: (30 * 2.0) + (30 * 2.0 * 0.0025) = 60.15
+        short: (29.702970297029704 * 2.02) - (29.702970297029704 * 2.02 * 0.0025) = 59.85
+    close_value
+        long: (30 * 2.2) - (30 * 2.2 * 0.0025) = 65.835
+        short: (29.702970297029704 * 2.3) + (29.702970297029704 * 2.3 * 0.0025) = 68.48762376237624
+    profit
+        long: 65.835 - 60.15 = 5.684999999999995
+        short: 59.85 - 68.48762376237624 = -8.637623762376244
+    profit_ratio
+        long: (65.835/60.15) - 1 = 0.0945137157107232
+        short: 1 - (68.48762376237624/59.85) = -0.1443211990371971
+    """
+    open_rate = ticker_usdt.return_value['ask' if is_short else 'bid']
     rpc_mock = patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         _is_dry_limit_order_filled=MagicMock(return_value=False),
     )
-    patch_whitelist(mocker, default_conf)
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    patch_whitelist(mocker, default_conf_usdt)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     # Create some test data
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
 
     # Increase the price and sell it
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker_sell_up
+        fetch_ticker=ticker_usdt_sell_up
     )
-    freqtrade.config['order_types']['sell'] = 'market'
+    freqtrade.config['order_types']['exit'] = 'market'
 
-    freqtrade.execute_trade_exit(trade=trade, limit=ticker_sell_up()['bid'],
-                                 sell_reason=SellCheckTuple(sell_type=SellType.ROI))
+    freqtrade.execute_trade_exit(
+        trade=trade,
+        limit=ticker_usdt_sell_up()['ask' if is_short else 'bid'],
+        exit_check=ExitCheckTuple(exit_type=ExitType.ROI)
+    )
 
     assert not trade.is_open
-    assert trade.close_profit == 0.0620716
+    assert trade.close_profit == profit_ratio
 
     assert rpc_mock.call_count == 3
-    last_msg = rpc_mock.call_args_list[-1][0][0]
+    last_msg = rpc_mock.call_args_list[-2][0][0]
     assert {
-        'type': RPCMessageType.SELL,
+        'type': RPCMessageType.EXIT,
         'trade_id': 1,
         'exchange': 'Binance',
-        'pair': 'ETH/BTC',
-        'gain': 'profit',
-        'limit': 1.172e-05,
-        'amount': 91.07468123,
+        'pair': 'ETH/USDT',
+        'direction': 'Short' if trade.is_short else 'Long',
+        'leverage': 1.0,
+        'gain': profit_or_loss,
+        'limit': limit,
+        'amount': pytest.approx(amount),
         'order_type': 'market',
-        'open_rate': 1.098e-05,
-        'current_rate': 1.173e-05,
-        'profit_amount': 6.223e-05,
-        'profit_ratio': 0.0620716,
-        'stake_currency': 'BTC',
+        'buy_tag': None,
+        'enter_tag': None,
+        'open_rate': open_rate,
+        'current_rate': current_rate,
+        'profit_amount': pytest.approx(profit_amount),
+        'profit_ratio': profit_ratio,
+        'stake_currency': 'USDT',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.ROI.value,
+        'sell_reason': ExitType.ROI.value,
+        'exit_reason': ExitType.ROI.value,
         'open_date': ANY,
         'close_date': ANY,
         'close_rate': ANY,
@@ -2986,55 +3584,65 @@ def test_execute_trade_exit_market_order(default_conf, ticker, fee,
     } == last_msg
 
 
-def test_execute_trade_exit_insufficient_funds_error(default_conf, ticker, fee,
-                                                     ticker_sell_up, mocker) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_execute_trade_exit_insufficient_funds_error(default_conf_usdt, ticker_usdt, fee, is_short,
+                                                     ticker_usdt_sell_up, mocker) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     mock_insuf = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_insufficient_funds')
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
         create_order=MagicMock(side_effect=[
             {'id': 1234553382},
             InsufficientFundsError(),
         ]),
     )
-    patch_get_signal(freqtrade)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     # Create some test data
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
 
     # Increase the price and sell it
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker_sell_up
+        fetch_ticker=ticker_usdt_sell_up
     )
 
-    sell_reason = SellCheckTuple(sell_type=SellType.ROI)
-    assert not freqtrade.execute_trade_exit(trade=trade, limit=ticker_sell_up()['bid'],
-                                            sell_reason=sell_reason)
+    sell_reason = ExitCheckTuple(exit_type=ExitType.ROI)
+    assert not freqtrade.execute_trade_exit(
+        trade=trade,
+        limit=ticker_usdt_sell_up()['ask' if is_short else 'bid'],
+        exit_check=sell_reason
+    )
     assert mock_insuf.call_count == 1
 
 
-@pytest.mark.parametrize('profit_only,bid,ask,handle_first,handle_second,sell_type', [
+@pytest.mark.parametrize('profit_only,bid,ask,handle_first,handle_second,exit_type,is_short', [
     # Enable profit
-    (True, 0.00001172, 0.00001173, False, True, SellType.SELL_SIGNAL.value),
-    # Disable profit
-    (False, 0.00002172, 0.00002173, True,  False, SellType.SELL_SIGNAL.value),
-    # Enable loss
-    # * Shouldn't this be SellType.STOP_LOSS.value
-    (True, 0.00000172, 0.00000173, False, False, None),
+    (True, 2.18, 2.2, False, True, ExitType.EXIT_SIGNAL.value, False),
+    (True, 2.18, 2.2, False, True, ExitType.EXIT_SIGNAL.value, True),
+    # # Disable profit
+    (False, 3.19, 3.2, True,  False, ExitType.EXIT_SIGNAL.value, False),
+    (False, 3.19, 3.2, True,  False, ExitType.EXIT_SIGNAL.value, True),
+    # # Enable loss
+    # # * Shouldn't this be ExitType.STOP_LOSS.value
+    (True, 0.21, 0.22, False, False, None, False),
+    (True, 2.41, 2.42, False, False, None, True),
     # Disable loss
-    (False, 0.00000172, 0.00000173, True, False, SellType.SELL_SIGNAL.value),
+    (False, 0.10, 0.22, True, False, ExitType.EXIT_SIGNAL.value, False),
+    (False, 0.10, 0.22, True, False, ExitType.EXIT_SIGNAL.value, True),
 ])
-def test_sell_profit_only(
-        default_conf, limit_buy_order, limit_buy_order_open,
-        fee, mocker, profit_only, bid, ask, handle_first, handle_second, sell_type) -> None:
+def test_exit_profit_only(
+        default_conf_usdt, limit_order, limit_order_open, is_short,
+        fee, mocker, profit_only, bid, ask, handle_first, handle_second, exit_type) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
+    eside = entry_side(is_short)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
@@ -3043,39 +3651,45 @@ def test_sell_profit_only(
             'last': bid
         }),
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
+            limit_order_open[eside],
             {'id': 1234553382},
         ]),
         get_fee=fee,
     )
-    default_conf.update({
-        'use_sell_signal': True,
-        'sell_profit_only': profit_only,
-        'sell_profit_offset': 0.1,
+    default_conf_usdt.update({
+        'use_exit_signal': True,
+        'exit_profit_only': profit_only,
+        'exit_profit_offset': 0.1,
     })
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    if sell_type == SellType.SELL_SIGNAL.value:
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
+    freqtrade.strategy.custom_exit = MagicMock(return_value=None)
+    if exit_type == ExitType.EXIT_SIGNAL.value:
         freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
     else:
-        freqtrade.strategy.stop_loss_reached = MagicMock(return_value=SellCheckTuple(
-            sell_type=SellType.NONE))
+        freqtrade.strategy.stop_loss_reached = MagicMock(return_value=ExitCheckTuple(
+            exit_type=ExitType.NONE))
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
-    trade.update(limit_buy_order)
+    assert trade.is_short == is_short
+    oobj = Order.parse_from_ccxt_object(limit_order[eside], limit_order[eside]['symbol'], eside)
+    trade.update_trade(oobj)
     freqtrade.wallets.update()
-    patch_get_signal(freqtrade, value=(False, True, None))
+    if profit_only:
+        assert freqtrade.handle_trade(trade) is False
+        # Custom-exit is called
+        freqtrade.strategy.custom_exit.call_count == 1
+
+    patch_get_signal(freqtrade, enter_long=False, exit_short=is_short, exit_long=not is_short)
     assert freqtrade.handle_trade(trade) is handle_first
 
     if handle_second:
-        freqtrade.strategy.sell_profit_offset = 0.0
+        freqtrade.strategy.exit_profit_offset = 0.0
         assert freqtrade.handle_trade(trade) is True
 
-    assert trade.sell_reason == sell_type
 
-
-def test_sell_not_enough_balance(default_conf, limit_buy_order, limit_buy_order_open,
+def test_sell_not_enough_balance(default_conf_usdt, limit_order, limit_order_open,
                                  fee, mocker, caplog) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
@@ -3087,13 +3701,13 @@ def test_sell_not_enough_balance(default_conf, limit_buy_order, limit_buy_order_
             'last': 0.00002172
         }),
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
+            limit_order_open['buy'],
             {'id': 1234553382},
         ]),
         get_fee=fee,
     )
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
     freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
 
@@ -3101,8 +3715,10 @@ def test_sell_not_enough_balance(default_conf, limit_buy_order, limit_buy_order_
 
     trade = Trade.query.first()
     amnt = trade.amount
-    trade.update(limit_buy_order)
-    patch_get_signal(freqtrade, value=(False, True, None))
+
+    oobj = Order.parse_from_ccxt_object(limit_order['buy'], limit_order['buy']['symbol'], 'buy')
+    trade.update_trade(oobj)
+    patch_get_signal(freqtrade, enter_long=False, exit_long=True)
     mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=trade.amount * 0.985))
 
     assert freqtrade.handle_trade(trade) is True
@@ -3114,7 +3730,7 @@ def test_sell_not_enough_balance(default_conf, limit_buy_order, limit_buy_order_
     (95.29, False),
     (91.29, True)
 ])
-def test__safe_exit_amount(default_conf, fee, caplog, mocker, amount_wallet, has_err):
+def test__safe_exit_amount(default_conf_usdt, fee, caplog, mocker, amount_wallet, has_err):
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     amount = 95.33
@@ -3130,10 +3746,10 @@ def test__safe_exit_amount(default_conf, fee, caplog, mocker, amount_wallet, has
         fee_open=fee.return_value,
         fee_close=fee.return_value,
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
     if has_err:
-        with pytest.raises(DependencyException, match=r"Not enough amount to sell."):
+        with pytest.raises(DependencyException, match=r"Not enough amount to exit trade."):
             assert freqtrade._safe_exit_amount(trade.pair, trade.amount)
     else:
         wallet_update.reset_mock()
@@ -3147,32 +3763,38 @@ def test__safe_exit_amount(default_conf, fee, caplog, mocker, amount_wallet, has
         assert wallet_update.call_count == 1
 
 
-def test_locked_pairs(default_conf, ticker, fee, ticker_sell_down, mocker, caplog) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_locked_pairs(default_conf_usdt, ticker_usdt, fee,
+                      ticker_usdt_sell_down, mocker, caplog, is_short) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
+        fetch_ticker=ticker_usdt,
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
 
     # Create some test data
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
+    trade.is_short = is_short
     assert trade
 
     # Decrease the price and sell it
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker_sell_down
+        fetch_ticker=ticker_usdt_sell_down
     )
 
-    freqtrade.execute_trade_exit(trade=trade, limit=ticker_sell_down()['bid'],
-                                 sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
-    trade.close(ticker_sell_down()['bid'])
+    freqtrade.execute_trade_exit(
+        trade=trade,
+        limit=ticker_usdt_sell_down()['ask' if is_short else 'bid'],
+        exit_check=ExitCheckTuple(exit_type=ExitType.STOP_LOSS)
+    )
+    trade.close(ticker_usdt_sell_down()['bid'])
     assert freqtrade.strategy.is_pair_locked(trade.pair)
 
     # reinit - should buy other pair.
@@ -3182,325 +3804,271 @@ def test_locked_pairs(default_conf, ticker, fee, ticker_sell_down, mocker, caplo
     assert log_has_re(f"Pair {trade.pair} is still locked.*", caplog)
 
 
-def test_ignore_roi_if_buy_signal(default_conf, limit_buy_order, limit_buy_order_open,
-                                  fee, mocker) -> None:
+@pytest.mark.parametrize("is_short", [False, True])
+def test_ignore_roi_if_entry_signal(default_conf_usdt, limit_order, limit_order_open, is_short,
+                                    fee, mocker) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
+    eside = entry_side(is_short)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.0000172,
-            'ask': 0.0000173,
-            'last': 0.0000172
+            'bid': 2.19,
+            'ask': 2.2,
+            'last': 2.19
         }),
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
+            limit_order_open[eside],
             {'id': 1234553382},
         ]),
         get_fee=fee,
     )
-    default_conf['ignore_roi_if_buy_signal'] = True
+    default_conf_usdt['ignore_roi_if_entry_signal'] = True
 
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.min_roi_reached = MagicMock(return_value=True)
 
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
-    trade.update(limit_buy_order)
+    trade.is_short = is_short
+    oobj = Order.parse_from_ccxt_object(
+        limit_order[eside], limit_order[eside]['symbol'], eside)
+    trade.update_trade(oobj)
     freqtrade.wallets.update()
-    patch_get_signal(freqtrade, value=(True, True, None))
+    if is_short:
+        patch_get_signal(freqtrade, enter_long=False, enter_short=True, exit_short=True)
+    else:
+        patch_get_signal(freqtrade, enter_long=True, exit_long=True)
+
     assert freqtrade.handle_trade(trade) is False
 
-    # Test if buy-signal is absent (should sell due to roi = true)
-    patch_get_signal(freqtrade, value=(False, True, None))
+    # Test if entry-signal is absent (should sell due to roi = true)
+    if is_short:
+        patch_get_signal(freqtrade, enter_long=False, exit_short=False)
+    else:
+        patch_get_signal(freqtrade, enter_long=False, exit_long=False)
     assert freqtrade.handle_trade(trade) is True
-    assert trade.sell_reason == SellType.ROI.value
+    assert trade.exit_reason == ExitType.ROI.value
 
 
-def test_trailing_stop_loss(default_conf, limit_buy_order_open, limit_buy_order,
-                            fee, caplog, mocker) -> None:
+@pytest.mark.parametrize("is_short,val1,val2", [
+    (False, 1.5, 1.1),
+    (True, 0.5, 0.9)
+])
+def test_trailing_stop_loss(default_conf_usdt, limit_order_open,
+                            is_short, val1, val2, fee, caplog, mocker) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001099,
-            'ask': 0.00001099,
-            'last': 0.00001099
+            'bid': 2.0,
+            'ask': 2.0,
+            'last': 2.0
         }),
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
+            limit_order_open[entry_side(is_short)],
             {'id': 1234553382},
         ]),
         get_fee=fee,
     )
-    default_conf['trailing_stop'] = True
-    patch_whitelist(mocker, default_conf)
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    default_conf_usdt['trailing_stop'] = True
+    patch_whitelist(mocker, default_conf_usdt)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
 
     freqtrade.enter_positions()
     trade = Trade.query.first()
+    assert trade.is_short == is_short
     assert freqtrade.handle_trade(trade) is False
 
-    # Raise ticker above buy price
+    # Raise praise into profits
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  MagicMock(return_value={
-                     'bid': 0.00001099 * 1.5,
-                     'ask': 0.00001099 * 1.5,
-                     'last': 0.00001099 * 1.5
+                     'bid': 2.0 * val1,
+                     'ask': 2.0 * val1,
+                     'last': 2.0 * val1
                  }))
 
     # Stoploss should be adjusted
     assert freqtrade.handle_trade(trade) is False
-
+    caplog.clear()
     # Price fell
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  MagicMock(return_value={
-                     'bid': 0.00001099 * 1.1,
-                     'ask': 0.00001099 * 1.1,
-                     'last': 0.00001099 * 1.1
+                     'bid': 2.0 * val2,
+                     'ask': 2.0 * val2,
+                     'last': 2.0 * val2
                  }))
 
     caplog.set_level(logging.DEBUG)
     # Sell as trailing-stop is reached
     assert freqtrade.handle_trade(trade) is True
-    assert log_has("ETH/BTC - HIT STOP: current price at 0.000012, stoploss is 0.000015, "
-                   "initial stoploss was at 0.000010, trade opened at 0.000011", caplog)
-    assert trade.sell_reason == SellType.TRAILING_STOP_LOSS.value
+    stop_multi = 1.1 if is_short else 0.9
+    assert log_has(f"ETH/USDT - HIT STOP: current price at {(2.0 * val2):6f}, "
+                   f"stoploss is {(2.0 * val1 * stop_multi):6f}, "
+                   f"initial stoploss was at {(2.0 * stop_multi):6f}, trade opened at 2.000000",
+                   caplog)
+    assert trade.exit_reason == ExitType.TRAILING_STOP_LOSS.value
 
 
-def test_trailing_stop_loss_positive(default_conf, limit_buy_order, limit_buy_order_open, fee,
-                                     caplog, mocker) -> None:
-    buy_price = limit_buy_order['price']
+@pytest.mark.parametrize('offset,trail_if_reached,second_sl,is_short', [
+    (0, False, 2.0394, False),
+    (0.011, False, 2.0394, False),
+    (0.055, True, 1.8, False),
+    (0, False, 2.1614, True),
+    (0.011, False, 2.1614, True),
+    (0.055, True, 2.42, True),
+])
+def test_trailing_stop_loss_positive(
+    default_conf_usdt, limit_order, limit_order_open,
+    offset, fee, caplog, mocker, trail_if_reached, second_sl, is_short
+) -> None:
+    enter_price = limit_order[entry_side(is_short)]['price']
     patch_RPCManager(mocker)
     patch_exchange(mocker)
+    eside = entry_side(is_short)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': buy_price - 0.000001,
-            'ask': buy_price - 0.000001,
-            'last': buy_price - 0.000001
+            'bid': enter_price - (-0.01 if is_short else 0.01),
+            'ask': enter_price - (-0.01 if is_short else 0.01),
+            'last': enter_price - (-0.01 if is_short else 0.01),
         }),
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
+            limit_order_open[eside],
             {'id': 1234553382},
         ]),
         get_fee=fee,
     )
-    default_conf['trailing_stop'] = True
-    default_conf['trailing_stop_positive'] = 0.01
-    patch_whitelist(mocker, default_conf)
+    default_conf_usdt['trailing_stop'] = True
+    default_conf_usdt['trailing_stop_positive'] = 0.01
+    if offset:
+        default_conf_usdt['trailing_stop_positive_offset'] = offset
+        default_conf_usdt['trailing_only_offset_is_reached'] = trail_if_reached
+    patch_whitelist(mocker, default_conf_usdt)
 
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
-    trade.update(limit_buy_order)
+    assert trade.is_short == is_short
+    oobj = Order.parse_from_ccxt_object(limit_order[eside], limit_order[eside]['symbol'], eside)
+    trade.update_trade(oobj)
     caplog.set_level(logging.DEBUG)
     # stop-loss not reached
     assert freqtrade.handle_trade(trade) is False
 
-    # Raise ticker above buy price
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.000003,
-                     'ask': buy_price + 0.000003,
-                     'last': buy_price + 0.000003
-                 }))
+    # Raise ticker_usdt above buy price
+    mocker.patch(
+        'freqtrade.exchange.Exchange.fetch_ticker',
+        MagicMock(return_value={
+            'bid': enter_price + (-0.06 if is_short else 0.06),
+            'ask': enter_price + (-0.06 if is_short else 0.06),
+            'last': enter_price + (-0.06 if is_short else 0.06),
+        })
+    )
     # stop-loss not reached, adjusted stoploss
     assert freqtrade.handle_trade(trade) is False
-    assert log_has("ETH/BTC - Using positive stoploss: 0.01 offset: 0 profit: 0.2666%", caplog)
-    assert log_has("ETH/BTC - Adjusting stoploss...", caplog)
-    assert trade.stop_loss == 0.0000138501
+    caplog_text = (f"ETH/USDT - Using positive stoploss: 0.01 offset: {offset} profit: "
+                   f"{'2.49' if not is_short else '2.24'}%")
+    if trail_if_reached:
+        assert not log_has(caplog_text, caplog)
+        assert not log_has("ETH/USDT - Adjusting stoploss...", caplog)
+    else:
+        assert log_has(caplog_text, caplog)
+        assert log_has("ETH/USDT - Adjusting stoploss...", caplog)
+    assert pytest.approx(trade.stop_loss) == second_sl
     caplog.clear()
 
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.000002,
-                     'ask': buy_price + 0.000002,
-                     'last': buy_price + 0.000002
-                 }))
+    mocker.patch(
+        'freqtrade.exchange.Exchange.fetch_ticker',
+        MagicMock(return_value={
+            'bid': enter_price + (-0.135 if is_short else 0.125),
+            'ask': enter_price + (-0.135 if is_short else 0.125),
+            'last': enter_price + (-0.135 if is_short else 0.125),
+        })
+    )
+    assert freqtrade.handle_trade(trade) is False
+    assert log_has(
+        f"ETH/USDT - Using positive stoploss: 0.01 offset: {offset} profit: "
+        f"{'5.72' if not is_short else '5.67'}%",
+        caplog
+    )
+    assert log_has("ETH/USDT - Adjusting stoploss...", caplog)
+
+    mocker.patch(
+        'freqtrade.exchange.Exchange.fetch_ticker',
+        MagicMock(return_value={
+            'bid': enter_price + (-0.02 if is_short else 0.02),
+            'ask': enter_price + (-0.02 if is_short else 0.02),
+            'last': enter_price + (-0.02 if is_short else 0.02),
+        })
+    )
     # Lower price again (but still positive)
     assert freqtrade.handle_trade(trade) is True
     assert log_has(
-        f"ETH/BTC - HIT STOP: current price at {buy_price + 0.000002:.6f}, "
+        f"ETH/USDT - HIT STOP: current price at {enter_price + (-0.02 if is_short else 0.02):.6f}, "
         f"stoploss is {trade.stop_loss:.6f}, "
-        f"initial stoploss was at 0.000010, trade opened at 0.000011", caplog)
+        f"initial stoploss was at {'2.42' if is_short else '1.80'}0000, "
+        f"trade opened at {2.2 if is_short else 2.0}00000",
+        caplog)
+    assert trade.exit_reason == ExitType.TRAILING_STOP_LOSS.value
 
 
-def test_trailing_stop_loss_offset(default_conf, limit_buy_order, limit_buy_order_open, fee,
-                                   caplog, mocker) -> None:
-    buy_price = limit_buy_order['price']
+@pytest.mark.parametrize("is_short", [False, True])
+def test_disable_ignore_roi_if_entry_signal(default_conf_usdt, limit_order, limit_order_open,
+                                            is_short, fee, mocker) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
+    eside = entry_side(is_short)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': buy_price - 0.000001,
-            'ask': buy_price - 0.000001,
-            'last': buy_price - 0.000001
+            'bid': 2.0,
+            'ask': 2.0,
+            'last': 2.0
         }),
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
-            {'id': 1234553382},
-        ]),
-        get_fee=fee,
-    )
-    patch_whitelist(mocker, default_conf)
-    default_conf['trailing_stop'] = True
-    default_conf['trailing_stop_positive'] = 0.01
-    default_conf['trailing_stop_positive_offset'] = 0.011
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-    freqtrade.enter_positions()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    caplog.set_level(logging.DEBUG)
-    # stop-loss not reached
-    assert freqtrade.handle_trade(trade) is False
-
-    # Raise ticker above buy price
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.000003,
-                     'ask': buy_price + 0.000003,
-                     'last': buy_price + 0.000003
-                 }))
-    # stop-loss not reached, adjusted stoploss
-    assert freqtrade.handle_trade(trade) is False
-    assert log_has("ETH/BTC - Using positive stoploss: 0.01 offset: 0.011 profit: 0.2666%", caplog)
-    assert log_has("ETH/BTC - Adjusting stoploss...", caplog)
-    assert trade.stop_loss == 0.0000138501
-    caplog.clear()
-
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.000002,
-                     'ask': buy_price + 0.000002,
-                     'last': buy_price + 0.000002
-                 }))
-    # Lower price again (but still positive)
-    assert freqtrade.handle_trade(trade) is True
-    assert log_has(
-        f"ETH/BTC - HIT STOP: current price at {buy_price + 0.000002:.6f}, "
-        f"stoploss is {trade.stop_loss:.6f}, "
-        f"initial stoploss was at 0.000010, trade opened at 0.000011", caplog)
-    assert trade.sell_reason == SellType.TRAILING_STOP_LOSS.value
-
-
-def test_tsl_only_offset_reached(default_conf, limit_buy_order, limit_buy_order_open, fee,
-                                 caplog, mocker) -> None:
-    buy_price = limit_buy_order['price']
-    # buy_price: 0.00001099
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        fetch_ticker=MagicMock(return_value={
-            'bid': buy_price,
-            'ask': buy_price,
-            'last': buy_price
-        }),
-        create_order=MagicMock(return_value=limit_buy_order_open),
-        get_fee=fee,
-    )
-    patch_whitelist(mocker, default_conf)
-    default_conf['trailing_stop'] = True
-    default_conf['trailing_stop_positive'] = 0.05
-    default_conf['trailing_stop_positive_offset'] = 0.055
-    default_conf['trailing_only_offset_is_reached'] = True
-
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-    freqtrade.enter_positions()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    caplog.set_level(logging.DEBUG)
-    # stop-loss not reached
-    assert freqtrade.handle_trade(trade) is False
-    assert trade.stop_loss == 0.0000098910
-
-    # Raise ticker above buy price
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.0000004,
-                     'ask': buy_price + 0.0000004,
-                     'last': buy_price + 0.0000004
-                 }))
-
-    # stop-loss should not be adjusted as offset is not reached yet
-    assert freqtrade.handle_trade(trade) is False
-
-    assert not log_has("ETH/BTC - Adjusting stoploss...", caplog)
-    assert trade.stop_loss == 0.0000098910
-    caplog.clear()
-
-    # price rises above the offset (rises 12% when the offset is 5.5%)
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.0000014,
-                     'ask': buy_price + 0.0000014,
-                     'last': buy_price + 0.0000014
-                 }))
-
-    assert freqtrade.handle_trade(trade) is False
-    assert log_has("ETH/BTC - Using positive stoploss: 0.05 offset: 0.055 profit: 0.1218%", caplog)
-    assert log_has("ETH/BTC - Adjusting stoploss...", caplog)
-    assert trade.stop_loss == 0.0000117705
-
-
-def test_disable_ignore_roi_if_buy_signal(default_conf, limit_buy_order, limit_buy_order_open,
-                                          fee, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        fetch_ticker=MagicMock(return_value={
-            'bid': 0.00000172,
-            'ask': 0.00000173,
-            'last': 0.00000172
-        }),
-        create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
+            limit_order_open[eside],
             {'id': 1234553382},
             {'id': 1234553383}
         ]),
         get_fee=fee,
         _is_dry_limit_order_filled=MagicMock(return_value=False),
     )
-    default_conf['ask_strategy'] = {
-        'ignore_roi_if_buy_signal': False
+    default_conf_usdt['exit_pricing'] = {
+        'ignore_roi_if_entry_signal': False
     }
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.strategy.min_roi_reached = MagicMock(return_value=True)
 
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
-    trade.update(limit_buy_order)
+    trade.is_short = is_short
+
+    oobj = Order.parse_from_ccxt_object(
+        limit_order[eside], limit_order[eside]['symbol'], eside)
+    trade.update_trade(oobj)
     # Sell due to min_roi_reached
-    patch_get_signal(freqtrade, value=(True, True, None))
+    patch_get_signal(freqtrade, enter_long=not is_short, enter_short=is_short, exit_short=is_short)
     assert freqtrade.handle_trade(trade) is True
 
-    # Test if buy-signal is absent
-    patch_get_signal(freqtrade, value=(False, True, None))
+    # Test if entry-signal is absent
+    patch_get_signal(freqtrade)
     assert freqtrade.handle_trade(trade) is True
-    assert trade.sell_reason == SellType.SELL_SIGNAL.value
+    assert trade.exit_reason == ExitType.ROI.value
 
 
-def test_get_real_amount_quote(default_conf, trades_for_order, buy_order_fee, fee, caplog, mocker):
+def test_get_real_amount_quote(default_conf_usdt, trades_for_order, buy_order_fee, fee, caplog,
+                               mocker):
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
     amount = sum(x['amount'] for x in trades_for_order)
     trade = Trade(
@@ -3512,16 +4080,20 @@ def test_get_real_amount_quote(default_conf, trades_for_order, buy_order_fee, fe
         fee_close=fee.return_value,
         open_order_id="123456"
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
+    caplog.clear()
+    order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy')
     # Amount is reduced by "fee"
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount - (amount * 0.001)
-    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
-                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.992).',
-                   caplog)
+    assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) == amount - (amount * 0.001)
+    assert log_has(
+        'Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, is_short=False,'
+        ' leverage=1.0, open_rate=0.24544100, open_since=closed) (from 8.0 to 7.992).',
+        caplog
+    )
 
 
-def test_get_real_amount_quote_dust(default_conf, trades_for_order, buy_order_fee, fee,
+def test_get_real_amount_quote_dust(default_conf_usdt, trades_for_order, buy_order_fee, fee,
                                     caplog, mocker):
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
     walletmock = mocker.patch('freqtrade.wallets.Wallets.update')
@@ -3536,17 +4108,18 @@ def test_get_real_amount_quote_dust(default_conf, trades_for_order, buy_order_fe
         fee_close=fee.return_value,
         open_order_id="123456"
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     walletmock.reset_mock()
+    order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy')
     # Amount is kept as is
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
+    assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) == amount
     assert walletmock.call_count == 1
     assert log_has_re(r'Fee amount for Trade.* was in base currency '
                       '- Eating Fee 0.008 into dust', caplog)
 
 
-def test_get_real_amount_no_trade(default_conf, buy_order_fee, caplog, mocker, fee):
+def test_get_real_amount_no_trade(default_conf_usdt, buy_order_fee, caplog, mocker, fee):
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
 
     amount = buy_order_fee['amount']
@@ -3559,17 +4132,48 @@ def test_get_real_amount_no_trade(default_conf, buy_order_fee, caplog, mocker, f
         fee_close=fee.return_value,
         open_order_id="123456"
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
+    order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy')
     # Amount is reduced by "fee"
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
-    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
-                   'open_rate=0.24544100, open_since=closed) failed: myTrade-Dict empty found',
-                   caplog)
+    assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) == amount
+    assert log_has(
+        'Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
+        'is_short=False, leverage=1.0, open_rate=0.24544100, open_since=closed) failed: '
+        'myTrade-Dict empty found',
+        caplog
+    )
 
 
-def test_get_real_amount_stake(default_conf, trades_for_order, buy_order_fee, fee, mocker):
-    trades_for_order[0]['fee']['currency'] = 'ETH'
+@pytest.mark.parametrize(
+    'fee_par,fee_reduction_amount,use_ticker_usdt_rate,expected_log', [
+        # basic, amount does not change
+        ({'cost': 0.008, 'currency': 'ETH'}, 0, False, None),
+        # no currency in fee
+        ({'cost': 0.004, 'currency': None}, 0, True, None),
+        # BNB no rate
+        ({'cost': 0.00094518, 'currency': 'BNB'}, 0, True, (
+            'Fee for Trade Trade(id=None, pair=LTC/ETH, amount=8.00000000, is_short=False, '
+            'leverage=1.0, open_rate=0.24544100, open_since=closed) [buy]: 0.00094518 BNB -'
+            ' rate: None'
+        )),
+        # from order
+        ({'cost': 0.004, 'currency': 'LTC'}, 0.004, False, (
+            'Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
+            'is_short=False, leverage=1.0, open_rate=0.24544100, open_since=closed) (from'
+            ' 8.0 to 7.996).'
+        )),
+        # invalid, no currency in from fee dict
+        ({'cost': 0.008, 'currency': None}, 0, True, None),
+    ])
+def test_get_real_amount(
+    default_conf_usdt, trades_for_order, buy_order_fee, fee, mocker, caplog,
+    fee_par, fee_reduction_amount, use_ticker_usdt_rate, expected_log
+):
+
+    buy_order = deepcopy(buy_order_fee)
+    buy_order['fee'] = fee_par
+    trades_for_order[0]['fee'] = fee_par
 
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
     amount = sum(x['amount'] for x in trades_for_order)
@@ -3582,21 +4186,41 @@ def test_get_real_amount_stake(default_conf, trades_for_order, buy_order_fee, fe
         open_rate=0.245441,
         open_order_id="123456"
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
-    # Amount does not change
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
+    if not use_ticker_usdt_rate:
+        mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', side_effect=ExchangeError)
+
+    caplog.clear()
+    order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy')
+    assert freqtrade.get_real_amount(trade, buy_order, order_obj) == amount - fee_reduction_amount
+
+    if expected_log:
+        assert log_has(expected_log, caplog)
 
 
-def test_get_real_amount_no_currency_in_fee(default_conf, trades_for_order, buy_order_fee,
-                                            fee, mocker):
+@pytest.mark.parametrize(
+    'fee_cost, fee_currency, fee_reduction_amount, expected_fee, expected_log_amount', [
+        # basic, amount is reduced by fee
+        (None, None, 0.001, 0.001, 7.992),
+        # different fee currency on both trades, fee is average of both trade's fee
+        (0.02, 'BNB', 0.0005, 0.001518575, 7.996),
+    ])
+def test_get_real_amount_multi(
+    default_conf_usdt, trades_for_order2, buy_order_fee, caplog, fee, mocker, markets,
+    fee_cost, fee_currency, fee_reduction_amount, expected_fee, expected_log_amount,
+):
 
-    limit_buy_order = deepcopy(buy_order_fee)
-    limit_buy_order['fee'] = {'cost': 0.004, 'currency': None}
-    trades_for_order[0]['fee']['currency'] = None
+    trades_for_order = deepcopy(trades_for_order2)
+    if fee_cost:
+        trades_for_order[0]['fee']['cost'] = fee_cost
+    if fee_currency:
+        trades_for_order[0]['fee']['currency'] = fee_currency
 
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    amount = sum(x['amount'] for x in trades_for_order)
+    amount = float(sum(x['amount'] for x in trades_for_order))
+    default_conf_usdt['stake_currency'] = "ETH"
+
     trade = Trade(
         pair='LTC/ETH',
         amount=amount,
@@ -3606,127 +4230,39 @@ def test_get_real_amount_no_currency_in_fee(default_conf, trades_for_order, buy_
         open_rate=0.245441,
         open_order_id="123456"
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
 
-    # Amount does not change
-    assert freqtrade.get_real_amount(trade, limit_buy_order) == amount
-
-
-def test_get_real_amount_BNB(default_conf, trades_for_order, buy_order_fee, fee, mocker):
-    trades_for_order[0]['fee']['currency'] = 'BNB'
-    trades_for_order[0]['fee']['cost'] = 0.00094518
-
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    amount = sum(x['amount'] for x in trades_for_order)
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-
-    # Amount does not change
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
-
-
-def test_get_real_amount_multi(default_conf, trades_for_order2, buy_order_fee, caplog, fee, mocker):
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order2)
-    amount = float(sum(x['amount'] for x in trades_for_order2))
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-
-    # Amount is reduced by "fee"
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount - (amount * 0.001)
-    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
-                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.992).',
-                   caplog)
-
-    assert trade.fee_open == 0.001
-    assert trade.fee_close == 0.001
-    assert trade.fee_open_cost is not None
-    assert trade.fee_open_currency is not None
-    assert trade.fee_close_cost is None
-    assert trade.fee_close_currency is None
-
-
-def test_get_real_amount_multi2(default_conf, trades_for_order3, buy_order_fee, caplog, fee,
-                                mocker, markets):
-    # Different fee currency on both trades
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order3)
-    amount = float(sum(x['amount'] for x in trades_for_order3))
-    default_conf['stake_currency'] = 'ETH'
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
     # Fake markets entry to enable fee parsing
-    markets['BNB/ETH'] = markets['ETH/BTC']
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    markets['BNB/ETH'] = markets['ETH/USDT']
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  return_value={'ask': 0.19, 'last': 0.2})
 
     # Amount is reduced by "fee"
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount - (amount * 0.0005)
-    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
-                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.996).',
-                   caplog)
-    # Overall fee is average of both trade's fee
-    assert trade.fee_open == 0.001518575
+    expected_amount = amount - (amount * fee_reduction_amount)
+    order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy')
+    assert freqtrade.get_real_amount(trade, buy_order_fee, order_obj) == expected_amount
+    assert log_has(
+        (
+            'Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
+            'is_short=False, leverage=1.0, open_rate=0.24544100, open_since=closed) '
+            f'(from 8.0 to {expected_log_amount}).'
+        ),
+        caplog
+    )
+
+    assert trade.fee_open == expected_fee
+    assert trade.fee_close == expected_fee
     assert trade.fee_open_cost is not None
     assert trade.fee_open_currency is not None
     assert trade.fee_close_cost is None
     assert trade.fee_close_currency is None
 
 
-def test_get_real_amount_fromorder(default_conf, trades_for_order, buy_order_fee, fee,
-                                   caplog, mocker):
-    limit_buy_order = deepcopy(buy_order_fee)
-    limit_buy_order['fee'] = {'cost': 0.004, 'currency': 'LTC'}
-
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order',
-                 return_value=[trades_for_order])
-    amount = float(sum(x['amount'] for x in trades_for_order))
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    # Ticker rate cannot be found for this to work.
-    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', side_effect=ExchangeError)
-
-    # Amount is reduced by "fee"
-    assert freqtrade.get_real_amount(trade, limit_buy_order) == amount - 0.004
-    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
-                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.996).',
-                   caplog)
-
-
-def test_get_real_amount_invalid_order(default_conf, trades_for_order, buy_order_fee, fee, mocker):
-    limit_buy_order = deepcopy(buy_order_fee)
-    limit_buy_order['fee'] = {'cost': 0.004}
+def test_get_real_amount_invalid_order(default_conf_usdt, trades_for_order, buy_order_fee, fee,
+                                       mocker):
+    limit_buy_order_usdt = deepcopy(buy_order_fee)
+    limit_buy_order_usdt['fee'] = {'cost': 0.004}
 
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
     amount = float(sum(x['amount'] for x in trades_for_order))
@@ -3739,15 +4275,43 @@ def test_get_real_amount_invalid_order(default_conf, trades_for_order, buy_order
         open_rate=0.245441,
         open_order_id="123456"
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+
+    order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy')
+    # Amount does not change
+    assert freqtrade.get_real_amount(trade, limit_buy_order_usdt, order_obj) == amount
+
+
+def test_get_real_amount_fees_order(default_conf_usdt, market_buy_order_usdt_doublefee,
+                                    fee, mocker):
+
+    tfo_mock = mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
+    mocker.patch('freqtrade.exchange.Exchange.get_valid_pair_combination', return_value='BNB/USDT')
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', return_value={'last': 200})
+    trade = Trade(
+        pair='LTC/USDT',
+        amount=30.0,
+        exchange='binance',
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.245441,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     # Amount does not change
-    assert freqtrade.get_real_amount(trade, limit_buy_order) == amount
+    assert trade.fee_open == 0.0025
+    order_obj = Order.parse_from_ccxt_object(market_buy_order_usdt_doublefee, 'LTC/ETH', 'buy')
+    assert freqtrade.get_real_amount(trade, market_buy_order_usdt_doublefee, order_obj) == 30.0
+    assert tfo_mock.call_count == 0
+    # Fetch fees from trades dict if available to get "proper" values
+    assert round(trade.fee_open, 4) == 0.001
 
 
-def test_get_real_amount_wrong_amount(default_conf, trades_for_order, buy_order_fee, fee, mocker):
-    limit_buy_order = deepcopy(buy_order_fee)
-    limit_buy_order['amount'] = limit_buy_order['amount'] - 0.001
+def test_get_real_amount_wrong_amount(default_conf_usdt, trades_for_order, buy_order_fee, fee,
+                                      mocker):
+    limit_buy_order_usdt = deepcopy(buy_order_fee)
+    limit_buy_order_usdt['amount'] = limit_buy_order_usdt['amount'] - 0.001
 
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
     amount = float(sum(x['amount'] for x in trades_for_order))
@@ -3760,17 +4324,18 @@ def test_get_real_amount_wrong_amount(default_conf, trades_for_order, buy_order_
         fee_close=fee.return_value,
         open_order_id="123456"
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
+    order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy')
     # Amount does not change
     with pytest.raises(DependencyException, match=r"Half bought\? Amounts don't match"):
-        freqtrade.get_real_amount(trade, limit_buy_order)
+        freqtrade.get_real_amount(trade, limit_buy_order_usdt, order_obj)
 
 
-def test_get_real_amount_wrong_amount_rounding(default_conf, trades_for_order, buy_order_fee, fee,
-                                               mocker):
+def test_get_real_amount_wrong_amount_rounding(default_conf_usdt, trades_for_order, buy_order_fee,
+                                               fee, mocker):
     # Floats should not be compared directly.
-    limit_buy_order = deepcopy(buy_order_fee)
+    limit_buy_order_usdt = deepcopy(buy_order_fee)
     trades_for_order[0]['amount'] = trades_for_order[0]['amount'] + 1e-15
 
     mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
@@ -3784,35 +4349,18 @@ def test_get_real_amount_wrong_amount_rounding(default_conf, trades_for_order, b
         open_rate=0.245441,
         open_order_id="123456"
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
+    order_obj = Order.parse_from_ccxt_object(buy_order_fee, 'LTC/ETH', 'buy')
     # Amount changes by fee amount.
-    assert isclose(freqtrade.get_real_amount(trade, limit_buy_order), amount - (amount * 0.001),
-                   abs_tol=MATH_CLOSE_PREC,)
-
-
-def test_get_real_amount_invalid(default_conf, trades_for_order, buy_order_fee, fee, mocker):
-    # Remove "Currency" from fee dict
-    trades_for_order[0]['fee'] = {'cost': 0.008}
-
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    amount = sum(x['amount'] for x in trades_for_order)
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-
-        open_order_id="123456"
+    assert isclose(
+        freqtrade.get_real_amount(trade, limit_buy_order_usdt, order_obj),
+        amount - (amount * 0.001),
+        abs_tol=MATH_CLOSE_PREC,
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    # Amount does not change
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
 
 
-def test_get_real_amount_open_trade(default_conf, fee, mocker):
+def test_get_real_amount_open_trade_usdt(default_conf_usdt, fee, mocker):
     amount = 12345
     trade = Trade(
         pair='LTC/ETH',
@@ -3829,8 +4377,9 @@ def test_get_real_amount_open_trade(default_conf, fee, mocker):
         'status': 'open',
         'side': 'buy',
     }
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    assert freqtrade.get_real_amount(trade, order) == amount
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    order_obj = Order.parse_from_ccxt_object(order, 'LTC/ETH', 'buy')
+    assert freqtrade.get_real_amount(trade, order, order_obj) == amount
 
 
 @pytest.mark.parametrize('amount,fee_abs,wallet,amount_exp', [
@@ -3841,7 +4390,7 @@ def test_get_real_amount_open_trade(default_conf, fee, mocker):
     (8.0, 0.1, 8.0, 8.0),
     (8.0, 0.1, 7.9, 7.9),
 ])
-def test_apply_fee_conditional(default_conf, fee, caplog, mocker,
+def test_apply_fee_conditional(default_conf_usdt, fee, mocker,
                                amount, fee_abs, wallet, amount_exp):
     walletmock = mocker.patch('freqtrade.wallets.Wallets.update')
     mocker.patch('freqtrade.wallets.Wallets.get_free', return_value=wallet)
@@ -3854,7 +4403,7 @@ def test_apply_fee_conditional(default_conf, fee, caplog, mocker,
         fee_close=fee.return_value,
         open_order_id="123456"
     )
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     walletmock.reset_mock()
     # Amount is kept as is
@@ -3862,99 +4411,92 @@ def test_apply_fee_conditional(default_conf, fee, caplog, mocker,
     assert walletmock.call_count == 1
 
 
-def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order_open, limit_buy_order,
-                                    fee, mocker, order_book_l2):
-    default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
-    default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 0.1
+@pytest.mark.parametrize("delta, is_high_delta", [
+    (0.1, False),
+    (100, True),
+])
+@pytest.mark.parametrize('is_short', [False, True])
+def test_order_book_depth_of_market(
+    default_conf_usdt, ticker_usdt, limit_order_open,
+    fee, mocker, order_book_l2, delta, is_high_delta, is_short
+):
+    ticker_side = 'ask' if is_short else 'bid'
+
+    default_conf_usdt['entry_pricing']['check_depth_of_market']['enabled'] = True
+    default_conf_usdt['entry_pricing']['check_depth_of_market']['bids_to_ask_delta'] = delta
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value=limit_buy_order_open),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value=limit_order_open[entry_side(is_short)]),
         get_fee=fee,
     )
 
     # Save state of current whitelist
-    whitelist = deepcopy(default_conf['exchange']['pair_whitelist'])
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
+    whitelist = deepcopy(default_conf_usdt['exchange']['pair_whitelist'])
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    patch_get_signal(freqtrade, enter_short=is_short, enter_long=not is_short)
     freqtrade.enter_positions()
 
     trade = Trade.query.first()
-    assert trade is not None
-    assert trade.stake_amount == 0.001
-    assert trade.is_open
-    assert trade.open_date is not None
-    assert trade.exchange == 'binance'
+    if is_high_delta:
+        assert trade is None
+    else:
+        trade.is_short = is_short
+        assert trade is not None
+        assert pytest.approx(trade.stake_amount) == 60.0
+        assert trade.is_open
+        assert trade.open_date is not None
+        assert trade.exchange == 'binance'
 
-    assert len(Trade.query.all()) == 1
+        assert len(Trade.query.all()) == 1
 
-    # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
+        # Simulate fulfilled LIMIT_BUY order for trade
+        oobj = Order.parse_from_ccxt_object(
+            limit_order_open[entry_side(is_short)], 'ADA/USDT', entry_side(is_short))
+        trade.update_trade(oobj)
 
-    assert trade.open_rate == 0.00001099
-    assert whitelist == default_conf['exchange']['pair_whitelist']
-
-
-def test_order_book_depth_of_market_high_delta(default_conf, ticker, limit_buy_order,
-                                               fee, mocker, order_book_l2):
-    default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
-    # delta is 100 which is impossible to reach. hence check_depth_of_market will return false
-    default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 100
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-    )
-    # Save state of current whitelist
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.enter_positions()
-
-    trade = Trade.query.first()
-    assert trade is None
+        assert trade.open_rate == ticker_usdt.return_value[ticker_side]
+        assert whitelist == default_conf_usdt['exchange']['pair_whitelist']
 
 
 @pytest.mark.parametrize('exception_thrown,ask,last,order_book_top,order_book', [
     (False, 0.045, 0.046, 2, None),
     (True,  0.042, 0.046, 1, {'bids': [[]], 'asks': [[]]})
 ])
-def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2, exception_thrown,
-                                  ask, last, order_book_top, order_book, caplog) -> None:
+def test_order_book_entry_pricing1(mocker, default_conf_usdt, order_book_l2, exception_thrown,
+                                   ask, last, order_book_top, order_book, caplog) -> None:
     """
     test if function get_rate will return the order book price instead of the ask rate
     """
     patch_exchange(mocker)
-    ticker_mock = MagicMock(return_value={'ask': ask, 'last': last})
+    ticker_usdt_mock = MagicMock(return_value={'ask': ask, 'last': last})
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_l2_order_book=MagicMock(return_value=order_book) if order_book else order_book_l2,
-        fetch_ticker=ticker_mock,
+        fetch_ticker=ticker_usdt_mock,
     )
-    default_conf['exchange']['name'] = 'binance'
-    default_conf['bid_strategy']['use_order_book'] = True
-    default_conf['bid_strategy']['order_book_top'] = order_book_top
-    default_conf['bid_strategy']['ask_last_balance'] = 0
-    default_conf['telegram']['enabled'] = False
+    default_conf_usdt['exchange']['name'] = 'binance'
+    default_conf_usdt['entry_pricing']['use_order_book'] = True
+    default_conf_usdt['entry_pricing']['order_book_top'] = order_book_top
+    default_conf_usdt['entry_pricing']['price_last_balance'] = 0
+    default_conf_usdt['telegram']['enabled'] = False
 
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     if exception_thrown:
         with pytest.raises(PricingError):
-            freqtrade.exchange.get_rate('ETH/BTC', refresh=True, side="buy")
+            freqtrade.exchange.get_rate('ETH/USDT', side="entry", is_short=False, refresh=True)
         assert log_has_re(
-            r'Buy Price at location 1 from orderbook could not be determined.', caplog)
+            r'Entry Price at location 1 from orderbook could not be determined.', caplog)
     else:
-        assert freqtrade.exchange.get_rate('ETH/BTC', refresh=True, side="buy") == 0.043935
-        assert ticker_mock.call_count == 0
+        assert freqtrade.exchange.get_rate(
+            'ETH/USDT', side="entry", is_short=False, refresh=True) == 0.043935
+        assert ticker_usdt_mock.call_count == 0
 
 
-def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2) -> None:
+def test_check_depth_of_market(default_conf_usdt, mocker, order_book_l2) -> None:
     """
     test check depth of market
     """
@@ -3963,43 +4505,45 @@ def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2) -> None:
         'freqtrade.exchange.Exchange',
         fetch_l2_order_book=order_book_l2
     )
-    default_conf['telegram']['enabled'] = False
-    default_conf['exchange']['name'] = 'binance'
-    default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
+    default_conf_usdt['telegram']['enabled'] = False
+    default_conf_usdt['exchange']['name'] = 'binance'
+    default_conf_usdt['entry_pricing']['check_depth_of_market']['enabled'] = True
     # delta is 100 which is impossible to reach. hence function will return false
-    default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 100
-    freqtrade = FreqtradeBot(default_conf)
+    default_conf_usdt['entry_pricing']['check_depth_of_market']['bids_to_ask_delta'] = 100
+    freqtrade = FreqtradeBot(default_conf_usdt)
 
-    conf = default_conf['bid_strategy']['check_depth_of_market']
-    assert freqtrade._check_depth_of_market_buy('ETH/BTC', conf) is False
+    conf = default_conf_usdt['entry_pricing']['check_depth_of_market']
+    assert freqtrade._check_depth_of_market('ETH/BTC', conf, side=SignalDirection.LONG) is False
 
 
-def test_order_book_ask_strategy(default_conf, limit_buy_order_open, limit_buy_order, fee,
-                                 limit_sell_order_open, mocker, order_book_l2, caplog) -> None:
+@pytest.mark.parametrize('is_short', [False, True])
+def test_order_book_exit_pricing(
+        default_conf_usdt, limit_buy_order_usdt_open, limit_buy_order_usdt, fee, is_short,
+        limit_sell_order_usdt_open, mocker, order_book_l2, caplog) -> None:
     """
     test order book ask strategy
     """
     mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
-    default_conf['exchange']['name'] = 'binance'
-    default_conf['ask_strategy']['use_order_book'] = True
-    default_conf['ask_strategy']['order_book_top'] = 1
-    default_conf['telegram']['enabled'] = False
+    default_conf_usdt['exchange']['name'] = 'binance'
+    default_conf_usdt['exit_pricing']['use_order_book'] = True
+    default_conf_usdt['exit_pricing']['order_book_top'] = 1
+    default_conf_usdt['telegram']['enabled'] = False
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
         }),
         create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
-            limit_sell_order_open,
+            limit_buy_order_usdt_open,
+            limit_sell_order_usdt_open,
         ]),
         get_fee=fee,
     )
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     patch_get_signal(freqtrade)
 
     freqtrade.enter_positions()
@@ -4008,11 +4552,15 @@ def test_order_book_ask_strategy(default_conf, limit_buy_order_open, limit_buy_o
     assert trade
 
     time.sleep(0.01)  # Race condition fix
-    trade.update(limit_buy_order)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order_usdt, limit_buy_order_usdt['symbol'], 'buy')
+    trade.update_trade(oobj)
     freqtrade.wallets.update()
     assert trade.is_open is True
 
-    patch_get_signal(freqtrade, value=(False, True, None))
+    if is_short:
+        patch_get_signal(freqtrade, enter_long=False,  exit_short=True)
+    else:
+        patch_get_signal(freqtrade, enter_long=False, exit_long=True)
     assert freqtrade.handle_trade(trade) is True
     assert trade.close_rate_requested == order_book_l2.return_value['asks'][0][0]
 
@@ -4020,26 +4568,26 @@ def test_order_book_ask_strategy(default_conf, limit_buy_order_open, limit_buy_o
                  return_value={'bids': [[]], 'asks': [[]]})
     with pytest.raises(PricingError):
         freqtrade.handle_trade(trade)
-    assert log_has_re(r'Sell Price at location 1 from orderbook could not be determined\..*',
+    assert log_has_re(r'Exit Price at location 1 from orderbook could not be determined\..*',
                       caplog)
 
 
-def test_startup_state(default_conf, mocker):
-    default_conf['pairlist'] = {'method': 'VolumePairList',
-                                'config': {'number_assets': 20}
-                                }
+def test_startup_state(default_conf_usdt, mocker):
+    default_conf_usdt['pairlist'] = {'method': 'VolumePairList',
+                                     'config': {'number_assets': 20}
+                                     }
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
-    worker = get_patched_worker(mocker, default_conf)
+    worker = get_patched_worker(mocker, default_conf_usdt)
     assert worker.freqtrade.state is State.RUNNING
 
 
-def test_startup_trade_reinit(default_conf, edge_conf, mocker):
+def test_startup_trade_reinit(default_conf_usdt, edge_conf, mocker):
 
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
     reinit_mock = MagicMock()
     mocker.patch('freqtrade.persistence.Trade.stoploss_reinitialization', reinit_mock)
 
-    ftbot = get_patched_freqtradebot(mocker, default_conf)
+    ftbot = get_patched_freqtradebot(mocker, default_conf_usdt)
     ftbot.startup()
     assert reinit_mock.call_count == 1
 
@@ -4051,23 +4599,24 @@ def test_startup_trade_reinit(default_conf, edge_conf, mocker):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_sync_wallet_dry_run(mocker, default_conf, ticker, fee, limit_buy_order_open, caplog):
-    default_conf['dry_run'] = True
+def test_sync_wallet_dry_run(mocker, default_conf_usdt, ticker_usdt, fee, limit_buy_order_usdt_open,
+                             caplog):
+    default_conf_usdt['dry_run'] = True
     # Initialize to 2 times stake amount
-    default_conf['dry_run_wallet'] = 0.002
-    default_conf['max_open_trades'] = 2
-    default_conf['tradable_balance_ratio'] = 1.0
+    default_conf_usdt['dry_run_wallet'] = 120.0
+    default_conf_usdt['max_open_trades'] = 2
+    default_conf_usdt['tradable_balance_ratio'] = 1.0
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=MagicMock(return_value=limit_buy_order_open),
+        fetch_ticker=ticker_usdt,
+        create_order=MagicMock(return_value=limit_buy_order_usdt_open),
         get_fee=fee,
     )
 
-    bot = get_patched_freqtradebot(mocker, default_conf)
+    bot = get_patched_freqtradebot(mocker, default_conf_usdt)
     patch_get_signal(bot)
-    assert bot.wallets.get_free('BTC') == 0.002
+    assert bot.wallets.get_free('USDT') == 120.0
 
     n = bot.enter_positions()
     assert n == 2
@@ -4077,38 +4626,51 @@ def test_sync_wallet_dry_run(mocker, default_conf, ticker, fee, limit_buy_order_
     bot.config['max_open_trades'] = 3
     n = bot.enter_positions()
     assert n == 0
-    assert log_has_re(r"Unable to create trade for XRP/BTC: "
-                      r"Available balance \(0.0 BTC\) is lower than stake amount \(0.001 BTC\)",
+    assert log_has_re(r"Unable to create trade for XRP/USDT: "
+                      r"Available balance \(0.0 USDT\) is lower than stake amount \(60.0 USDT\)",
                       caplog)
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_cancel_all_open_orders(mocker, default_conf, fee, limit_buy_order, limit_sell_order):
-    default_conf['cancel_open_orders_on_exit'] = True
-    mocker.patch('freqtrade.exchange.Exchange.fetch_order',
-                 side_effect=[
-                     ExchangeError(), limit_sell_order, limit_buy_order, limit_sell_order])
+@pytest.mark.parametrize("is_short,buy_calls,sell_calls", [
+    (False, 1, 2),
+    (True, 1, 2),
+])
+def test_cancel_all_open_orders(mocker, default_conf_usdt, fee, limit_order, limit_order_open,
+                                is_short, buy_calls, sell_calls):
+    default_conf_usdt['cancel_open_orders_on_exit'] = True
+    mocker.patch(
+        'freqtrade.exchange.Exchange.fetch_order',
+        side_effect=[
+            ExchangeError(),
+            limit_order[exit_side(is_short)],
+            limit_order_open[entry_side(is_short)],
+            limit_order_open[exit_side(is_short)],
+        ]
+    )
     buy_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_cancel_enter')
     sell_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_cancel_exit')
 
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    create_mock_trades(fee)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    create_mock_trades(fee, is_short=is_short)
     trades = Trade.query.all()
     assert len(trades) == MOCK_TRADE_COUNT
     freqtrade.cancel_all_open_orders()
-    assert buy_mock.call_count == 1
-    assert sell_mock.call_count == 2
+    assert buy_mock.call_count == buy_calls
+    assert sell_mock.call_count == sell_calls
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_check_for_open_trades(mocker, default_conf, fee):
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_check_for_open_trades(mocker, default_conf_usdt, fee, is_short):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     freqtrade.check_for_open_trades()
     assert freqtrade.rpc.send_msg.call_count == 0
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short)
     trade = Trade.query.first()
+    trade.is_short = is_short
     trade.is_open = True
 
     freqtrade.check_for_open_trades()
@@ -4116,35 +4678,37 @@ def test_check_for_open_trades(mocker, default_conf, fee):
     assert 'Handle these trades manually' in freqtrade.rpc.send_msg.call_args[0][0]['status']
 
 
+@pytest.mark.parametrize("is_short", [False, True])
 @pytest.mark.usefixtures("init_persistence")
-def test_update_open_orders(mocker, default_conf, fee, caplog):
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    create_mock_trades(fee)
+def test_startup_update_open_orders(mocker, default_conf_usdt, fee, caplog, is_short):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    create_mock_trades(fee, is_short=is_short)
 
-    freqtrade.update_open_orders()
+    freqtrade.startup_update_open_orders()
     assert not log_has_re(r"Error updating Order .*", caplog)
     caplog.clear()
 
     freqtrade.config['dry_run'] = False
-    freqtrade.update_open_orders()
+    freqtrade.startup_update_open_orders()
 
     assert log_has_re(r"Error updating Order .*", caplog)
     caplog.clear()
 
     assert len(Order.get_open_orders()) == 3
-    matching_buy_order = mock_order_4()
+    matching_buy_order = mock_order_4(is_short=is_short)
     matching_buy_order.update({
         'status': 'closed',
     })
     mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=matching_buy_order)
-    freqtrade.update_open_orders()
+    freqtrade.startup_update_open_orders()
     # Only stoploss and sell orders are kept open
     assert len(Order.get_open_orders()) == 2
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_update_closed_trades_without_assigned_fees(mocker, default_conf, fee):
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_update_closed_trades_without_assigned_fees(mocker, default_conf_usdt, fee, is_short):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
 
     def patch_with_fee(order):
         order.update({'fee': {'cost': 0.1, 'rate': 0.01,
@@ -4153,19 +4717,20 @@ def test_update_closed_trades_without_assigned_fees(mocker, default_conf, fee):
 
     mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
                  side_effect=[
-                     patch_with_fee(mock_order_2_sell()),
-                     patch_with_fee(mock_order_3_sell()),
-                     patch_with_fee(mock_order_1()),
-                     patch_with_fee(mock_order_2()),
-                     patch_with_fee(mock_order_3()),
-                     patch_with_fee(mock_order_4()),
+                     patch_with_fee(mock_order_2_sell(is_short=is_short)),
+                     patch_with_fee(mock_order_3_sell(is_short=is_short)),
+                     patch_with_fee(mock_order_1(is_short=is_short)),
+                     patch_with_fee(mock_order_2(is_short=is_short)),
+                     patch_with_fee(mock_order_3(is_short=is_short)),
+                     patch_with_fee(mock_order_4(is_short=is_short)),
                  ]
                  )
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
     trades = Trade.get_trades().all()
     assert len(trades) == MOCK_TRADE_COUNT
     for trade in trades:
+        trade.is_short = is_short
         assert trade.fee_open_cost is None
         assert trade.fee_open_currency is None
         assert trade.fee_close_cost is None
@@ -4192,7 +4757,7 @@ def test_update_closed_trades_without_assigned_fees(mocker, default_conf, fee):
     for trade in trades:
         if trade.is_open:
             # Exclude Trade 4 - as the order is still open.
-            if trade.select_order('buy', False):
+            if trade.select_order(entry_side(is_short), False):
                 assert trade.fee_open_cost is not None
                 assert trade.fee_open_currency is not None
             else:
@@ -4205,84 +4770,50 @@ def test_update_closed_trades_without_assigned_fees(mocker, default_conf, fee):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_reupdate_enter_order_fees(mocker, default_conf, fee, caplog):
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+@pytest.mark.parametrize("is_short", [False, True])
+def test_reupdate_enter_order_fees(mocker, default_conf_usdt, fee, caplog, is_short):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     mock_uts = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.update_trade_state')
 
-    create_mock_trades(fee)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 return_value={'status': 'open'})
+    create_mock_trades(fee, is_short)
     trades = Trade.get_trades().all()
 
-    freqtrade.reupdate_enter_order_fees(trades[0])
-    assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
+    freqtrade.handle_insufficient_funds(trades[3])
+    # assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
     assert mock_uts.call_count == 1
-    assert mock_uts.call_args_list[0][0][0] == trades[0]
-    assert mock_uts.call_args_list[0][0][1] == mock_order_1()['id']
-    assert log_has_re(r"Updating buy-fee on trade .* for order .*\.", caplog)
+    assert mock_uts.call_args_list[0][0][0] == trades[3]
+    assert mock_uts.call_args_list[0][0][1] == mock_order_4(is_short)['id']
+    assert log_has_re(r"Trying to refind lost order for .*", caplog)
     mock_uts.reset_mock()
     caplog.clear()
 
     # Test with trade without orders
     trade = Trade(
         pair='XRP/ETH',
-        stake_amount=0.001,
+        stake_amount=60.0,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         open_date=arrow.utcnow().datetime,
         is_open=True,
-        amount=20,
-        open_rate=0.01,
+        amount=30,
+        open_rate=2.0,
         exchange='binance',
+        is_short=is_short
     )
     Trade.query.session.add(trade)
 
-    freqtrade.reupdate_enter_order_fees(trade)
-    assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
+    freqtrade.handle_insufficient_funds(trade)
+    # assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
     assert mock_uts.call_count == 0
-    assert not log_has_re(r"Updating buy-fee on trade .* for order .*\.", caplog)
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_handle_insufficient_funds(mocker, default_conf, fee):
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mock_rlo = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.refind_lost_order')
-    mock_bof = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.reupdate_enter_order_fees')
-    create_mock_trades(fee)
-    trades = Trade.get_trades().all()
-
-    # Trade 0 has only a open buy order, no closed order
-    freqtrade.handle_insufficient_funds(trades[0])
-    assert mock_rlo.call_count == 0
-    assert mock_bof.call_count == 1
-
-    mock_rlo.reset_mock()
-    mock_bof.reset_mock()
-
-    # Trade 1 has closed buy and sell orders
-    freqtrade.handle_insufficient_funds(trades[1])
-    assert mock_rlo.call_count == 1
-    assert mock_bof.call_count == 0
-
-    mock_rlo.reset_mock()
-    mock_bof.reset_mock()
-
-    # Trade 2 has closed buy and sell orders
-    freqtrade.handle_insufficient_funds(trades[2])
-    assert mock_rlo.call_count == 1
-    assert mock_bof.call_count == 0
-
-    mock_rlo.reset_mock()
-    mock_bof.reset_mock()
-
-    # Trade 3 has an opne buy order
-    freqtrade.handle_insufficient_funds(trades[3])
-    assert mock_rlo.call_count == 0
-    assert mock_bof.call_count == 1
-
-
-@pytest.mark.usefixtures("init_persistence")
-def test_refind_lost_order(mocker, default_conf, fee, caplog):
+@pytest.mark.parametrize("is_short", [False, True])
+def test_handle_insufficient_funds(mocker, default_conf_usdt, fee, is_short, caplog):
     caplog.set_level(logging.DEBUG)
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
     mock_uts = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.update_trade_state')
 
     mock_fo = mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
@@ -4291,8 +4822,9 @@ def test_refind_lost_order(mocker, default_conf, fee, caplog):
     def reset_open_orders(trade):
         trade.open_order_id = None
         trade.stoploss_order_id = None
+        trade.is_short = is_short
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short=is_short)
     trades = Trade.get_trades().all()
 
     caplog.clear()
@@ -4303,8 +4835,8 @@ def test_refind_lost_order(mocker, default_conf, fee, caplog):
     assert trade.open_order_id is None
     assert trade.stoploss_order_id is None
 
-    freqtrade.refind_lost_order(trade)
-    order = mock_order_1()
+    freqtrade.handle_insufficient_funds(trade)
+    order = mock_order_1(is_short=is_short)
     assert log_has_re(r"Order Order(.*order_id=" + order['id'] + ".*) is no longer open.", caplog)
     assert mock_fo.call_count == 0
     assert mock_uts.call_count == 0
@@ -4321,13 +4853,13 @@ def test_refind_lost_order(mocker, default_conf, fee, caplog):
     assert trade.open_order_id is None
     assert trade.stoploss_order_id is None
 
-    freqtrade.refind_lost_order(trade)
-    order = mock_order_4()
+    freqtrade.handle_insufficient_funds(trade)
+    order = mock_order_4(is_short=is_short)
     assert log_has_re(r"Trying to refind Order\(.*", caplog)
-    assert mock_fo.call_count == 0
-    assert mock_uts.call_count == 0
-    # No change to orderid - as update_trade_state is mocked
-    assert trade.open_order_id is None
+    assert mock_fo.call_count == 1
+    assert mock_uts.call_count == 1
+    # Found open buy order
+    assert trade.open_order_id is not None
     assert trade.stoploss_order_id is None
 
     caplog.clear()
@@ -4339,11 +4871,11 @@ def test_refind_lost_order(mocker, default_conf, fee, caplog):
     assert trade.open_order_id is None
     assert trade.stoploss_order_id is None
 
-    freqtrade.refind_lost_order(trade)
-    order = mock_order_5_stoploss()
+    freqtrade.handle_insufficient_funds(trade)
+    order = mock_order_5_stoploss(is_short=is_short)
     assert log_has_re(r"Trying to refind Order\(.*", caplog)
     assert mock_fo.call_count == 1
-    assert mock_uts.call_count == 1
+    assert mock_uts.call_count == 2
     # stoploss_order_id is "refound" and added to the trade
     assert trade.open_order_id is None
     assert trade.stoploss_order_id is not None
@@ -4358,8 +4890,8 @@ def test_refind_lost_order(mocker, default_conf, fee, caplog):
     assert trade.open_order_id is None
     assert trade.stoploss_order_id is None
 
-    freqtrade.refind_lost_order(trade)
-    order = mock_order_6_sell()
+    freqtrade.handle_insufficient_funds(trade)
+    order = mock_order_6_sell(is_short=is_short)
     assert log_has_re(r"Trying to refind Order\(.*", caplog)
     assert mock_fo.call_count == 1
     assert mock_uts.call_count == 1
@@ -4372,16 +4904,16 @@ def test_refind_lost_order(mocker, default_conf, fee, caplog):
     # Test error case
     mock_fo = mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
                            side_effect=ExchangeError())
-    order = mock_order_5_stoploss()
+    order = mock_order_5_stoploss(is_short=is_short)
 
-    freqtrade.refind_lost_order(trades[4])
+    freqtrade.handle_insufficient_funds(trades[4])
     assert log_has(f"Error updating {order['id']}.", caplog)
 
 
-def test_get_valid_price(mocker, default_conf) -> None:
+def test_get_valid_price(mocker, default_conf_usdt) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
-    freqtrade = FreqtradeBot(default_conf)
+    freqtrade = FreqtradeBot(default_conf_usdt)
     freqtrade.config['custom_price_max_distance_ratio'] = 0.02
 
     custom_price_string = "10"
@@ -4416,3 +4948,463 @@ def test_get_valid_price(mocker, default_conf) -> None:
 
     assert valid_price_at_min_alwd > custom_price_under_min_alwd
     assert valid_price_at_min_alwd < proposed_price
+
+
+@pytest.mark.parametrize('trading_mode,calls,t1,t2', [
+    ('spot', 0, "2021-09-01 00:00:00", "2021-09-01 08:00:00"),
+    ('margin', 0, "2021-09-01 00:00:00", "2021-09-01 08:00:00"),
+    ('futures', 31, "2021-09-01 00:00:02", "2021-09-01 08:00:01"),
+    ('futures', 32, "2021-08-31 23:59:59", "2021-09-01 08:00:01"),
+    ('futures', 32, "2021-09-01 00:00:02", "2021-09-01 08:00:02"),
+    ('futures', 33, "2021-08-31 23:59:59", "2021-09-01 08:00:02"),
+    ('futures', 33, "2021-08-31 23:59:59", "2021-09-01 08:00:03"),
+    ('futures', 33, "2021-08-31 23:59:59", "2021-09-01 08:00:04"),
+    ('futures', 33, "2021-08-31 23:59:59", "2021-09-01 08:00:05"),
+    ('futures', 33, "2021-08-31 23:59:59", "2021-09-01 08:00:06"),
+    ('futures', 33, "2021-08-31 23:59:59", "2021-09-01 08:00:07"),
+    ('futures', 33, "2021-08-31 23:59:58", "2021-09-01 08:00:07"),
+])
+def test_update_funding_fees_schedule(mocker, default_conf, trading_mode, calls, time_machine,
+                                      t1, t2):
+    time_machine.move_to(f"{t1} +00:00")
+
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.update_funding_fees', return_value=True)
+    default_conf['trading_mode'] = trading_mode
+    default_conf['margin_mode'] = 'isolated'
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    time_machine.move_to(f"{t2} +00:00")
+    # Check schedule jobs in debugging with freqtrade._schedule.jobs
+    freqtrade._schedule.run_pending()
+
+    assert freqtrade.update_funding_fees.call_count == calls
+
+
+@pytest.mark.parametrize('schedule_off', [False, True])
+@pytest.mark.parametrize('is_short', [True, False])
+def test_update_funding_fees(
+    mocker,
+    default_conf,
+    time_machine,
+    fee,
+    ticker_usdt_sell_up,
+    is_short,
+    limit_order_open,
+    schedule_off
+):
+    """
+    nominal_value = mark_price * size
+    funding_fee = nominal_value * funding_rate
+    size = 123
+    "LTC/USDT"
+        time: 0, mark: 3.3, fundRate: 0.00032583, nominal_value: 405.9, fundFee: 0.132254397
+        time: 8, mark: 3.2, fundRate: 0.00024472, nominal_value: 393.6, fundFee: 0.096321792
+    "ETH/USDT"
+        time: 0, mark: 2.4, fundRate: 0.0001, nominal_value: 295.2, fundFee: 0.02952
+        time: 8, mark: 2.5, fundRate: 0.0001, nominal_value: 307.5, fundFee: 0.03075
+    "ETC/USDT"
+        time: 0, mark: 4.3, fundRate: 0.00031077, nominal_value: 528.9, fundFee: 0.164366253
+        time: 8, mark: 4.1, fundRate: 0.00022655, nominal_value: 504.3, fundFee: 0.114249165
+    "XRP/USDT"
+        time: 0, mark: 1.2, fundRate: 0.00049426, nominal_value: 147.6, fundFee: 0.072952776
+        time: 8, mark: 1.2, fundRate: 0.00032715, nominal_value: 147.6, fundFee: 0.04828734
+    """
+    # SETUP
+    time_machine.move_to("2021-09-01 00:00:00 +00:00")
+
+    open_order = limit_order_open[entry_side(is_short)]
+    open_exit_order = limit_order_open[exit_side(is_short)]
+    bid = 0.11
+    enter_rate_mock = MagicMock(return_value=bid)
+    enter_mm = MagicMock(return_value=open_order)
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+
+    date_midnight = arrow.get('2021-09-01 00:00:00').datetime
+    date_eight = arrow.get('2021-09-01 08:00:00').datetime
+    date_sixteen = arrow.get('2021-09-01 16:00:00').datetime
+    columns = ['date', 'open', 'high', 'low', 'close', 'volume']
+    # 16:00 entry is actually never used
+    # But should be kept in the test to ensure we're filtering correctly.
+    funding_rates = {
+        "LTC/USDT":
+            DataFrame([
+                [date_midnight, 0.00032583, 0, 0, 0, 0],
+                [date_eight, 0.00024472, 0, 0, 0, 0],
+                [date_sixteen, 0.00024472, 0, 0, 0, 0],
+            ], columns=columns),
+        "ETH/USDT":
+            DataFrame([
+                [date_midnight, 0.0001, 0, 0, 0, 0],
+                [date_eight, 0.0001, 0, 0, 0, 0],
+                [date_sixteen, 0.0001, 0, 0, 0, 0],
+            ], columns=columns),
+        "XRP/USDT":
+            DataFrame([
+                [date_midnight, 0.00049426, 0, 0, 0, 0],
+                [date_eight, 0.00032715, 0, 0, 0, 0],
+                [date_sixteen, 0.00032715, 0, 0, 0, 0],
+            ], columns=columns)
+    }
+
+    mark_prices = {
+        "LTC/USDT":
+            DataFrame([
+                [date_midnight, 3.3, 0, 0, 0, 0],
+                [date_eight, 3.2, 0, 0, 0, 0],
+                [date_sixteen, 3.2, 0, 0, 0, 0],
+            ], columns=columns),
+        "ETH/USDT":
+            DataFrame([
+                [date_midnight, 2.4, 0, 0, 0, 0],
+                [date_eight, 2.5, 0, 0, 0, 0],
+                [date_sixteen, 2.5, 0, 0, 0, 0],
+            ], columns=columns),
+        "XRP/USDT":
+            DataFrame([
+                [date_midnight, 1.2, 0, 0, 0, 0],
+                [date_eight, 1.2, 0, 0, 0, 0],
+                [date_sixteen, 1.2, 0, 0, 0, 0],
+            ], columns=columns)
+    }
+
+    def refresh_latest_ohlcv_mock(pairlist, **kwargs):
+        ret = {}
+        for p, tf, ct in pairlist:
+            if ct == CandleType.MARK:
+                ret[(p, tf, ct)] = mark_prices[p]
+            else:
+                ret[(p, tf, ct)] = funding_rates[p]
+
+        return ret
+
+    mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv',
+                 side_effect=refresh_latest_ohlcv_mock)
+
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_rate=enter_rate_mock,
+        fetch_ticker=MagicMock(return_value={
+            'bid': 1.9,
+            'ask': 2.2,
+            'last': 1.9
+        }),
+        create_order=enter_mm,
+        get_min_pair_stake_amount=MagicMock(return_value=1),
+        get_fee=fee,
+        get_maintenance_ratio_and_amt=MagicMock(return_value=(0.01, 0.01)),
+    )
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # initial funding fees,
+    freqtrade.execute_entry('ETH/USDT', 123, is_short=is_short)
+    freqtrade.execute_entry('LTC/USDT', 2.0, is_short=is_short)
+    freqtrade.execute_entry('XRP/USDT', 123, is_short=is_short)
+    multipl = 1 if is_short else -1
+    trades = Trade.get_open_trades()
+    assert len(trades) == 3
+    for trade in trades:
+        assert pytest.approx(trade.funding_fees) == 0
+    mocker.patch('freqtrade.exchange.Exchange.create_order', return_value=open_exit_order)
+    time_machine.move_to("2021-09-01 08:00:00 +00:00")
+    if schedule_off:
+        for trade in trades:
+            freqtrade.execute_trade_exit(
+                trade=trade,
+                # The values of the next 2 params are irrelevant for this test
+                limit=ticker_usdt_sell_up()['bid'],
+                exit_check=ExitCheckTuple(exit_type=ExitType.ROI)
+            )
+            assert trade.funding_fees == pytest.approx(sum(
+                trade.amount *
+                mark_prices[trade.pair].iloc[1:2]['open'] *
+                funding_rates[trade.pair].iloc[1:2]['open'] * multipl
+            ))
+
+    else:
+        freqtrade._schedule.run_pending()
+
+    # Funding fees for 00:00 and 08:00
+    for trade in trades:
+        assert trade.funding_fees == pytest.approx(sum(
+            trade.amount *
+            mark_prices[trade.pair].iloc[1:2]['open'] *
+            funding_rates[trade.pair].iloc[1:2]['open'] *
+            multipl
+        ))
+
+
+def test_position_adjust(mocker, default_conf_usdt, fee) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    patch_wallet(mocker, free=10000)
+    default_conf_usdt.update({
+        "position_adjustment_enable": True,
+        "dry_run": False,
+        "stake_amount": 10.0,
+        "dry_run_wallet": 1000.0,
+    })
+    freqtrade = FreqtradeBot(default_conf_usdt)
+    freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
+    bid = 11
+    stake_amount = 10
+    buy_rate_mock = MagicMock(return_value=bid)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_rate=buy_rate_mock,
+        fetch_ticker=MagicMock(return_value={
+            'bid': 10,
+            'ask': 12,
+            'last': 11
+        }),
+        get_min_pair_stake_amount=MagicMock(return_value=1),
+        get_fee=fee,
+    )
+    pair = 'ETH/USDT'
+
+    # Initial buy
+    closed_successful_buy_order = {
+        'pair': pair,
+        'ft_pair': pair,
+        'ft_order_side': 'buy',
+        'side': 'buy',
+        'type': 'limit',
+        'status': 'closed',
+        'price': bid,
+        'average': bid,
+        'cost': bid * stake_amount,
+        'amount': stake_amount,
+        'filled': stake_amount,
+        'ft_is_open': False,
+        'id': '650',
+        'order_id': '650'
+    }
+    mocker.patch('freqtrade.exchange.Exchange.create_order',
+                 MagicMock(return_value=closed_successful_buy_order))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 MagicMock(return_value=closed_successful_buy_order))
+    assert freqtrade.execute_entry(pair, stake_amount)
+    # Should create an closed trade with an no open order id
+    # Order is filled and trade is open
+    orders = Order.query.all()
+    assert orders
+    assert len(orders) == 1
+    trade = Trade.query.first()
+    assert trade
+    assert trade.is_open is True
+    assert trade.open_order_id is None
+    assert trade.open_rate == 11
+    assert trade.stake_amount == 110
+
+    # Assume it does nothing since order is closed and trade is open
+    freqtrade.update_closed_trades_without_assigned_fees()
+
+    trade = Trade.query.first()
+    assert trade
+    assert trade.is_open is True
+    assert trade.open_order_id is None
+    assert trade.open_rate == 11
+    assert trade.stake_amount == 110
+    assert not trade.fee_updated('buy')
+
+    freqtrade.check_handle_timedout()
+
+    trade = Trade.query.first()
+    assert trade
+    assert trade.is_open is True
+    assert trade.open_order_id is None
+    assert trade.open_rate == 11
+    assert trade.stake_amount == 110
+    assert not trade.fee_updated('buy')
+
+    # First position adjustment buy.
+    open_dca_order_1 = {
+        'ft_pair': pair,
+        'ft_order_side': 'buy',
+        'side': 'buy',
+        'type': 'limit',
+        'status': None,
+        'price': 9,
+        'amount': 12,
+        'cost': 100,
+        'ft_is_open': True,
+        'id': '651',
+        'order_id': '651'
+    }
+    mocker.patch('freqtrade.exchange.Exchange.create_order',
+                 MagicMock(return_value=open_dca_order_1))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 MagicMock(return_value=open_dca_order_1))
+    assert freqtrade.execute_entry(pair, stake_amount, trade=trade)
+
+    orders = Order.query.all()
+    assert orders
+    assert len(orders) == 2
+    trade = Trade.query.first()
+    assert trade
+    assert trade.open_order_id == '651'
+    assert trade.open_rate == 11
+    assert trade.amount == 10
+    assert trade.stake_amount == 110
+    assert not trade.fee_updated('buy')
+    trades: List[Trade] = Trade.get_open_trades_without_assigned_fees()
+    assert len(trades) == 1
+    assert trade.is_open
+    assert not trade.fee_updated('buy')
+    order = trade.select_order('buy', False)
+    assert order
+    assert order.order_id == '650'
+
+    def make_sure_its_651(*args, **kwargs):
+
+        if args[0] == '650':
+            return closed_successful_buy_order
+        if args[0] == '651':
+            return open_dca_order_1
+        return None
+
+    # Assume it does nothing since order is still open
+    fetch_order_mm = MagicMock(side_effect=make_sure_its_651)
+    mocker.patch('freqtrade.exchange.Exchange.create_order', fetch_order_mm)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', fetch_order_mm)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order', fetch_order_mm)
+    freqtrade.update_closed_trades_without_assigned_fees()
+
+    orders = Order.query.all()
+    assert orders
+    assert len(orders) == 2
+    # Assert that the trade is found as open and without fees
+    trades: List[Trade] = Trade.get_open_trades_without_assigned_fees()
+    assert len(trades) == 1
+    # Assert trade is as expected
+    trade = Trade.query.first()
+    assert trade
+    assert trade.open_order_id == '651'
+    assert trade.open_rate == 11
+    assert trade.amount == 10
+    assert trade.stake_amount == 110
+    assert not trade.fee_updated('buy')
+
+    # Make sure the closed order is found as the first order.
+    order = trade.select_order('buy', False)
+    assert order.order_id == '650'
+
+    # Now close the order so it should update.
+    closed_dca_order_1 = {
+        'ft_pair': pair,
+        'ft_order_side': 'buy',
+        'side': 'buy',
+        'type': 'limit',
+        'status': 'closed',
+        'price': 9,
+        'average': 9,
+        'amount': 12,
+        'filled': 12,
+        'cost': 108,
+        'ft_is_open': False,
+        'id': '651',
+        'order_id': '651',
+        'datetime': arrow.utcnow().isoformat(),
+    }
+
+    mocker.patch('freqtrade.exchange.Exchange.create_order',
+                 MagicMock(return_value=closed_dca_order_1))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order',
+                 MagicMock(return_value=closed_dca_order_1))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 MagicMock(return_value=closed_dca_order_1))
+    freqtrade.check_handle_timedout()
+
+    # Assert trade is as expected (averaged dca)
+    trade = Trade.query.first()
+    assert trade
+    assert trade.open_order_id is None
+    assert pytest.approx(trade.open_rate) == 9.90909090909
+    assert trade.amount == 22
+    assert trade.stake_amount == 218
+
+    orders = Order.query.all()
+    assert orders
+    assert len(orders) == 2
+
+    # Make sure the closed order is found as the second order.
+    order = trade.select_order('buy', False)
+    assert order.order_id == '651'
+
+    # Assert that the trade is not found as open and without fees
+    trades: List[Trade] = Trade.get_open_trades_without_assigned_fees()
+    assert len(trades) == 1
+
+    # Add a second DCA
+    closed_dca_order_2 = {
+        'ft_pair': pair,
+        'status': 'closed',
+        'ft_order_side': 'buy',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 7,
+        'average': 7,
+        'amount': 15,
+        'filled': 15,
+        'cost': 105,
+        'ft_is_open': False,
+        'id': '652',
+        'order_id': '652'
+    }
+    mocker.patch('freqtrade.exchange.Exchange.create_order',
+                 MagicMock(return_value=closed_dca_order_2))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order',
+                 MagicMock(return_value=closed_dca_order_2))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 MagicMock(return_value=closed_dca_order_2))
+    assert freqtrade.execute_entry(pair, stake_amount, trade=trade)
+
+    # Assert trade is as expected (averaged dca)
+    trade = Trade.query.first()
+    assert trade
+    assert trade.open_order_id is None
+    assert pytest.approx(trade.open_rate) == 8.729729729729
+    assert trade.amount == 37
+    assert trade.stake_amount == 323
+
+    orders = Order.query.all()
+    assert orders
+    assert len(orders) == 3
+
+    # Make sure the closed order is found as the second order.
+    order = trade.select_order('buy', False)
+    assert order.order_id == '652'
+
+
+def test_process_open_trade_positions_exception(mocker, default_conf_usdt, fee, caplog) -> None:
+    default_conf_usdt.update({
+        "position_adjustment_enable": True,
+    })
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.check_and_call_adjust_trade_position',
+                 side_effect=DependencyException())
+
+    create_mock_trades(fee)
+
+    freqtrade.process_open_trade_positions()
+    assert log_has_re(r"Unable to adjust position of trade for .*", caplog)
+
+
+def test_check_and_call_adjust_trade_position(mocker, default_conf_usdt, fee, caplog) -> None:
+    default_conf_usdt.update({
+        "position_adjustment_enable": True,
+        "max_entry_position_adjustment": 0,
+    })
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+
+    create_mock_trades(fee)
+    caplog.set_level(logging.DEBUG)
+
+    freqtrade.process_open_trade_positions()
+    assert log_has_re(r"Max adjustment entries for .* has been reached\.", caplog)
diff --git a/tests/test_integration.py b/tests/test_integration.py
index a3484d438..8f56c1fea 100644
--- a/tests/test_integration.py
+++ b/tests/test_integration.py
@@ -2,10 +2,10 @@ from unittest.mock import MagicMock
 
 import pytest
 
-from freqtrade.enums import SellType
+from freqtrade.enums import ExitCheckTuple, ExitType
 from freqtrade.persistence import Trade
+from freqtrade.persistence.models import Order
 from freqtrade.rpc.rpc import RPC
-from freqtrade.strategy.interface import SellCheckTuple
 from tests.conftest import get_patched_freqtradebot, patch_get_signal
 
 
@@ -52,8 +52,8 @@ def test_may_execute_exit_stoploss_on_exchange_multi(default_conf, ticker, fee,
         side_effect=[stoploss_order_closed, stoploss_order_open, stoploss_order_open])
     # Sell 3rd trade (not called for the first trade)
     should_sell_mock = MagicMock(side_effect=[
-        SellCheckTuple(sell_type=SellType.NONE),
-        SellCheckTuple(sell_type=SellType.SELL_SIGNAL)]
+        ExitCheckTuple(exit_type=ExitType.NONE),
+        ExitCheckTuple(exit_type=ExitType.EXIT_SIGNAL)]
     )
     cancel_order_mock = MagicMock()
     mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
@@ -72,14 +72,14 @@ def test_may_execute_exit_stoploss_on_exchange_multi(default_conf, ticker, fee,
         create_stoploss_order=MagicMock(return_value=True),
         _notify_exit=MagicMock(),
     )
-    mocker.patch("freqtrade.strategy.interface.IStrategy.should_sell", should_sell_mock)
+    mocker.patch("freqtrade.strategy.interface.IStrategy.should_exit", should_sell_mock)
     wallets_mock = mocker.patch("freqtrade.wallets.Wallets.update", MagicMock())
     mocker.patch("freqtrade.wallets.Wallets.get_free", MagicMock(return_value=1000))
 
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
     # Switch ordertype to market to close trade immediately
-    freqtrade.strategy.order_types['sell'] = 'market'
+    freqtrade.strategy.order_types['exit'] = 'market'
     freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
     freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=True)
     patch_get_signal(freqtrade)
@@ -94,7 +94,11 @@ def test_may_execute_exit_stoploss_on_exchange_multi(default_conf, ticker, fee,
     trades = Trade.query.all()
     # Make sure stoploss-order is open and trade is bought (since we mock update_trade_state)
     for trade in trades:
-        trade.stoploss_order_id = 3
+        stoploss_order_closed['id'] = '3'
+        oobj = Order.parse_from_ccxt_object(stoploss_order_closed, trade.pair, 'stoploss')
+
+        trade.orders.append(oobj)
+        trade.stoploss_order_id = '3'
         trade.open_order_id = None
 
     n = freqtrade.exit_positions(trades)
@@ -111,15 +115,15 @@ def test_may_execute_exit_stoploss_on_exchange_multi(default_conf, ticker, fee,
     assert wallets_mock.call_count == 4
 
     trade = trades[0]
-    assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
+    assert trade.exit_reason == ExitType.STOPLOSS_ON_EXCHANGE.value
     assert not trade.is_open
 
     trade = trades[1]
-    assert not trade.sell_reason
+    assert not trade.exit_reason
     assert trade.is_open
 
     trade = trades[2]
-    assert trade.sell_reason == SellType.SELL_SIGNAL.value
+    assert trade.exit_reason == ExitType.EXIT_SIGNAL.value
     assert not trade.is_open
 
 
@@ -127,8 +131,7 @@ def test_may_execute_exit_stoploss_on_exchange_multi(default_conf, ticker, fee,
                         (1, 200),
                         (0.99, 198),
 ])
-def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, mocker, balance_ratio,
-                                 result1) -> None:
+def test_forcebuy_last_unlimited(default_conf, ticker, fee, mocker, balance_ratio, result1) -> None:
     """
     Tests workflow unlimited stake-amount
     Buy 4 trades, forcebuy a 5th trade
@@ -136,7 +139,7 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc
     one trade was sold at a loss.
     """
     default_conf['max_open_trades'] = 5
-    default_conf['forcebuy_enable'] = True
+    default_conf['force_entry_enable'] = True
     default_conf['stake_amount'] = 'unlimited'
     default_conf['tradable_balance_ratio'] = balance_ratio
     default_conf['dry_run_wallet'] = 1000
@@ -157,19 +160,19 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc
         _notify_exit=MagicMock(),
     )
     should_sell_mock = MagicMock(side_effect=[
-        SellCheckTuple(sell_type=SellType.NONE),
-        SellCheckTuple(sell_type=SellType.SELL_SIGNAL),
-        SellCheckTuple(sell_type=SellType.NONE),
-        SellCheckTuple(sell_type=SellType.NONE),
-        SellCheckTuple(sell_type=SellType.NONE)]
+        ExitCheckTuple(exit_type=ExitType.NONE),
+        ExitCheckTuple(exit_type=ExitType.EXIT_SIGNAL),
+        ExitCheckTuple(exit_type=ExitType.NONE),
+        ExitCheckTuple(exit_type=ExitType.NONE),
+        ExitCheckTuple(exit_type=ExitType.NONE)]
     )
-    mocker.patch("freqtrade.strategy.interface.IStrategy.should_sell", should_sell_mock)
+    mocker.patch("freqtrade.strategy.interface.IStrategy.should_exit", should_sell_mock)
 
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
     rpc = RPC(freqtrade)
     freqtrade.strategy.order_types['stoploss_on_exchange'] = True
     # Switch ordertype to market to close trade immediately
-    freqtrade.strategy.order_types['sell'] = 'market'
+    freqtrade.strategy.order_types['exit'] = 'market'
     patch_get_signal(freqtrade)
 
     # Create 4 trades
@@ -180,7 +183,7 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc
     assert len(trades) == 4
     assert freqtrade.wallets.get_trade_stake_amount('XRP/BTC') == result1
 
-    rpc._rpc_forcebuy('TKN/BTC', None)
+    rpc._rpc_force_entry('TKN/BTC', None)
 
     trades = Trade.query.all()
     assert len(trades) == 5
@@ -207,3 +210,144 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc
     assert len(bals2) == 5
     assert 'LTC' in bals
     assert 'LTC' not in bals2
+
+
+def test_dca_buying(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
+    default_conf_usdt['position_adjustment_enable'] = True
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_usdt,
+        get_fee=fee,
+        amount_to_precision=lambda s, x, y: y,
+        price_to_precision=lambda s, x, y: y,
+    )
+
+    patch_get_signal(freqtrade)
+    freqtrade.enter_positions()
+
+    assert len(Trade.get_trades().all()) == 1
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 1
+    assert pytest.approx(trade.stake_amount) == 60
+    assert trade.open_rate == 2.0
+    # No adjustment
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 1
+    assert pytest.approx(trade.stake_amount) == 60
+
+    # Reduce bid amount
+    ticker_usdt_modif = ticker_usdt.return_value
+    ticker_usdt_modif['bid'] = ticker_usdt_modif['bid'] * 0.995
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', return_value=ticker_usdt_modif)
+
+    # additional buy order
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 2
+    for o in trade.orders:
+        assert o.status == "closed"
+    assert trade.stake_amount == 120
+
+    # Open-rate averaged between 2.0 and 2.0 * 0.995
+    assert trade.open_rate < 2.0
+    assert trade.open_rate > 2.0 * 0.995
+
+    # No action - profit raised above 1% (the bar set in the strategy).
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 2
+    assert trade.stake_amount == 120
+    assert trade.orders[0].amount == 30
+    assert trade.orders[1].amount == 60 / ticker_usdt_modif['bid']
+
+    assert trade.amount == trade.orders[0].amount + trade.orders[1].amount
+    assert trade.nr_of_successful_buys == 2
+    assert trade.nr_of_successful_entries == 2
+
+    # Sell
+    patch_get_signal(freqtrade, enter_long=False, exit_long=True)
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert trade.is_open is False
+    assert trade.orders[0].amount == 30
+    assert trade.orders[0].side == 'buy'
+    assert trade.orders[1].amount == 60 / ticker_usdt_modif['bid']
+    # Sold everything
+    assert trade.orders[-1].side == 'sell'
+    assert trade.orders[2].amount == trade.amount
+
+    assert trade.nr_of_successful_buys == 2
+    assert trade.nr_of_successful_entries == 2
+
+
+def test_dca_short(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
+    default_conf_usdt['position_adjustment_enable'] = True
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_usdt,
+        get_fee=fee,
+        amount_to_precision=lambda s, x, y: y,
+        price_to_precision=lambda s, x, y: y,
+    )
+
+    patch_get_signal(freqtrade, enter_long=False, enter_short=True)
+    freqtrade.enter_positions()
+
+    assert len(Trade.get_trades().all()) == 1
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 1
+    assert pytest.approx(trade.stake_amount) == 60
+    assert trade.open_rate == 2.02
+    # No adjustment
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 1
+    assert pytest.approx(trade.stake_amount) == 60
+
+    # Reduce bid amount
+    ticker_usdt_modif = ticker_usdt.return_value
+    ticker_usdt_modif['ask'] = ticker_usdt_modif['ask'] * 1.004
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', return_value=ticker_usdt_modif)
+
+    # additional buy order
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 2
+    for o in trade.orders:
+        assert o.status == "closed"
+    assert pytest.approx(trade.stake_amount) == 120
+
+    # Open-rate averaged between 2.0 and 2.0 * 1.015
+    assert trade.open_rate >= 2.02
+    assert trade.open_rate < 2.02 * 1.015
+
+    # No action - profit raised above 1% (the bar set in the strategy).
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert len(trade.orders) == 2
+    assert pytest.approx(trade.stake_amount) == 120
+    # assert trade.orders[0].amount == 30
+    assert trade.orders[1].amount == 60 / ticker_usdt_modif['ask']
+
+    assert trade.amount == trade.orders[0].amount + trade.orders[1].amount
+    assert trade.nr_of_successful_entries == 2
+
+    # Buy
+    patch_get_signal(freqtrade, enter_long=False, exit_short=True)
+    freqtrade.process()
+    trade = Trade.get_trades().first()
+    assert trade.is_open is False
+    # assert trade.orders[0].amount == 30
+    assert trade.orders[0].side == 'sell'
+    assert trade.orders[1].amount == 60 / ticker_usdt_modif['ask']
+    # Sold everything
+    assert trade.orders[-1].side == 'buy'
+    assert trade.orders[2].amount == trade.amount
+
+    assert trade.nr_of_successful_entries == 2
+    assert trade.nr_of_successful_exits == 1
diff --git a/tests/test_misc.py b/tests/test_misc.py
index 221c7b712..107932be4 100644
--- a/tests/test_misc.py
+++ b/tests/test_misc.py
@@ -1,15 +1,16 @@
 # pragma pylint: disable=missing-docstring,C0103
 
 import datetime
+from copy import deepcopy
 from pathlib import Path
 from unittest.mock import MagicMock
 
 import pytest
 
-from freqtrade.misc import (decimals_per_coin, file_dump_json, file_load_json, format_ms_time,
-                            pair_to_filename, parse_db_uri_for_logging, plural, render_template,
-                            render_template_with_fallback, round_coin_value, safe_value_fallback,
-                            safe_value_fallback2, shorten_date)
+from freqtrade.misc import (decimals_per_coin, deep_merge_dicts, file_dump_json, file_load_json,
+                            format_ms_time, pair_to_filename, parse_db_uri_for_logging, plural,
+                            render_template, render_template_with_fallback, round_coin_value,
+                            safe_value_fallback, safe_value_fallback2, shorten_date)
 
 
 def test_decimals_per_coin():
@@ -21,16 +22,19 @@ def test_decimals_per_coin():
 
 def test_round_coin_value():
     assert round_coin_value(222.222222, 'USDT') == '222.222 USDT'
-    assert round_coin_value(222.2, 'USDT') == '222.200 USDT'
+    assert round_coin_value(222.2, 'USDT', keep_trailing_zeros=True) == '222.200 USDT'
+    assert round_coin_value(222.2, 'USDT') == '222.2 USDT'
     assert round_coin_value(222.12745, 'EUR') == '222.127 EUR'
     assert round_coin_value(0.1274512123, 'BTC') == '0.12745121 BTC'
     assert round_coin_value(0.1274512123, 'ETH') == '0.12745 ETH'
 
     assert round_coin_value(222.222222, 'USDT', False) == '222.222'
-    assert round_coin_value(222.2, 'USDT', False) == '222.200'
+    assert round_coin_value(222.2, 'USDT', False) == '222.2'
+    assert round_coin_value(222.00, 'USDT', False) == '222'
     assert round_coin_value(222.12745, 'EUR', False) == '222.127'
     assert round_coin_value(0.1274512123, 'BTC', False) == '0.12745121'
     assert round_coin_value(0.1274512123, 'ETH', False) == '0.12745'
+    assert round_coin_value(222.2, 'USDT', False, True) == '222.200'
 
 
 def test_shorten_date() -> None:
@@ -67,13 +71,19 @@ def test_file_load_json(mocker, testdatadir) -> None:
 
 @pytest.mark.parametrize("pair,expected_result", [
     ("ETH/BTC", 'ETH_BTC'),
+    ("ETH/USDT", 'ETH_USDT'),
+    ("ETH/USDT:USDT", 'ETH_USDT_USDT'),  # swap with USDT as settlement currency
+    ("ETH/USD:USD", 'ETH_USD_USD'),  # swap with USD as settlement currency
+    ("AAVE/USD:USD", 'AAVE_USD_USD'),  # swap with USDT as settlement currency
+    ("ETH/USDT:USDT-210625", 'ETH_USDT_USDT-210625'),  # expiring futures
     ("Fabric Token/ETH", 'Fabric_Token_ETH'),
     ("ETHH20", 'ETHH20'),
     (".XBTBON2H", '_XBTBON2H'),
     ("ETHUSD.d", 'ETHUSD_d'),
-    ("ADA-0327", 'ADA_0327'),
-    ("BTC-USD-200110", 'BTC_USD_200110'),
-    ("F-AKRO/USDT", 'F_AKRO_USDT'),
+    ("ADA-0327", 'ADA-0327'),
+    ("BTC-USD-200110", 'BTC-USD-200110'),
+    ("BTC-PERP:USDT", 'BTC-PERP_USDT'),
+    ("F-AKRO/USDT", 'F-AKRO_USDT'),
     ("LC+/ETH", 'LC__ETH'),
     ("CMT@18/ETH", 'CMT_18_ETH'),
     ("LBTC:1022/SAI", 'LBTC_1022_SAI'),
@@ -181,16 +191,31 @@ def test_render_template_fallback(mocker):
     assert 'if self.dp' in val
 
 
-def test_parse_db_uri_for_logging() -> None:
-    postgresql_conn_uri = "postgresql+psycopg2://scott123:scott123@host/dbname"
-    mariadb_conn_uri = "mariadb+mariadbconnector://app_user:Password123!@127.0.0.1:3306/company"
-    mysql_conn_uri = "mysql+pymysql://user:pass@some_mariadb/dbname?charset=utf8mb4"
-    sqlite_conn_uri = "sqlite:////freqtrade/user_data/tradesv3.sqlite"
-    censored_pwd = "*****"
+@pytest.mark.parametrize('conn_url,expected', [
+    ("postgresql+psycopg2://scott123:scott123@host:1245/dbname",
+     "postgresql+psycopg2://scott123:*****@host:1245/dbname"),
+    ("postgresql+psycopg2://scott123:scott123@host.name.com/dbname",
+     "postgresql+psycopg2://scott123:*****@host.name.com/dbname"),
+    ("mariadb+mariadbconnector://app_user:Password123!@127.0.0.1:3306/company",
+     "mariadb+mariadbconnector://app_user:*****@127.0.0.1:3306/company"),
+    ("mysql+pymysql://user:pass@some_mariadb/dbname?charset=utf8mb4",
+     "mysql+pymysql://user:*****@some_mariadb/dbname?charset=utf8mb4"),
+    ("sqlite:////freqtrade/user_data/tradesv3.sqlite",
+     "sqlite:////freqtrade/user_data/tradesv3.sqlite"),
+])
+def test_parse_db_uri_for_logging(conn_url, expected) -> None:
 
-    def get_pwd(x): return x.split(':')[2].split('@')[0]
+    assert parse_db_uri_for_logging(conn_url) == expected
 
-    assert get_pwd(parse_db_uri_for_logging(postgresql_conn_uri)) == censored_pwd
-    assert get_pwd(parse_db_uri_for_logging(mariadb_conn_uri)) == censored_pwd
-    assert get_pwd(parse_db_uri_for_logging(mysql_conn_uri)) == censored_pwd
-    assert sqlite_conn_uri == parse_db_uri_for_logging(sqlite_conn_uri)
+
+def test_deep_merge_dicts():
+    a = {'first': {'rows': {'pass': 'dog', 'number': '1', 'test': None}}}
+    b = {'first': {'rows': {'fail': 'cat', 'number': '5', 'test': 'asdf'}}}
+    res = {'first': {'rows': {'pass': 'dog', 'fail': 'cat', 'number': '5', 'test': 'asdf'}}}
+    res2 = {'first': {'rows': {'pass': 'dog', 'fail': 'cat', 'number': '1', 'test': None}}}
+    assert deep_merge_dicts(b, deepcopy(a)) == res
+
+    assert deep_merge_dicts(a, deepcopy(b)) == res2
+
+    res2['first']['rows']['test'] = 'asdf'
+    assert deep_merge_dicts(a, deepcopy(b), allow_null_overrides=False) == res2
diff --git a/tests/test_periodiccache.py b/tests/test_periodiccache.py
index f874f9041..b2bd8ba2b 100644
--- a/tests/test_periodiccache.py
+++ b/tests/test_periodiccache.py
@@ -26,7 +26,9 @@ def test_ttl_cache():
         assert 'a' in cache1h
 
         t.move_to("2021-09-01 05:59:59 +00:00")
+        assert 'a' not in cache
         assert 'a' in cache1h
 
         t.move_to("2021-09-01 06:00:00 +00:00")
+        assert 'a' not in cache
         assert 'a' not in cache1h
diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index d036b045e..801e0e35f 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -8,12 +8,17 @@ from unittest.mock import MagicMock
 
 import arrow
 import pytest
-from sqlalchemy import create_engine, inspect, text
+from sqlalchemy import create_engine, text
 
 from freqtrade import constants
+from freqtrade.enums import TradingMode
 from freqtrade.exceptions import DependencyException, OperationalException
 from freqtrade.persistence import LocalTrade, Order, Trade, clean_dry_run_db, init_db
-from tests.conftest import create_mock_trades, log_has, log_has_re
+from freqtrade.persistence.migrations import get_last_sequence_ids, set_sequence_ids
+from tests.conftest import create_mock_trades, create_mock_trades_with_leverage, log_has, log_has_re
+
+
+spot, margin, futures = TradingMode.SPOT, TradingMode.MARGIN, TradingMode.FUTURES
 
 
 def test_init_create_session(default_conf):
@@ -32,13 +37,17 @@ def test_init_custom_db_url(default_conf, tmpdir):
 
     init_db(default_conf['db_url'], default_conf['dry_run'])
     assert Path(filename).is_file()
+    r = Trade._session.execute(text("PRAGMA journal_mode"))
+    assert r.first() == ('wal',)
 
 
-def test_init_invalid_db_url(default_conf):
+def test_init_invalid_db_url():
     # Update path to a value other than default, but still in-memory
-    default_conf.update({'db_url': 'unknown:///some.url'})
     with pytest.raises(OperationalException, match=r'.*no valid database URL*'):
-        init_db(default_conf['db_url'], default_conf['dry_run'])
+        init_db('unknown:///some.url', True)
+
+    with pytest.raises(OperationalException, match=r'Bad db-url.*For in-memory database, pl.*'):
+        init_db('sqlite:///', True)
 
 
 def test_init_prod_db(default_conf, mocker):
@@ -64,30 +73,290 @@ def test_init_dryrun_db(default_conf, tmpdir):
     assert Path(filename).is_file()
 
 
+@pytest.mark.parametrize('is_short', [False, True])
 @pytest.mark.usefixtures("init_persistence")
-def test_update_limit_order(limit_buy_order_usdt, limit_sell_order_usdt, fee, caplog):
+def test_enter_exit_side(fee, is_short):
+    entry_side, exit_side = ("sell", "buy") if is_short else ("buy", "sell")
+    trade = Trade(
+        id=2,
+        pair='ADA/USDT',
+        stake_amount=0.001,
+        open_rate=0.01,
+        amount=5,
+        is_open=True,
+        open_date=arrow.utcnow().datetime,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        exchange='binance',
+        is_short=is_short,
+        leverage=2.0,
+        trading_mode=margin
+    )
+    assert trade.entry_side == entry_side
+    assert trade.exit_side == exit_side
+    assert trade.trade_direction == 'short' if is_short else 'long'
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_set_stop_loss_isolated_liq(fee):
+    trade = Trade(
+        id=2,
+        pair='ADA/USDT',
+        stake_amount=60.0,
+        open_rate=2.0,
+        amount=30.0,
+        is_open=True,
+        open_date=arrow.utcnow().datetime,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        exchange='binance',
+        is_short=False,
+        leverage=2.0,
+        trading_mode=margin
+    )
+    trade.set_isolated_liq(0.09)
+    assert trade.liquidation_price == 0.09
+    assert trade.stop_loss is None
+    assert trade.initial_stop_loss is None
+
+    trade._set_stop_loss(0.1, (1.0 / 9.0))
+    assert trade.liquidation_price == 0.09
+    assert trade.stop_loss == 0.1
+    assert trade.initial_stop_loss == 0.1
+
+    trade.set_isolated_liq(0.08)
+    assert trade.liquidation_price == 0.08
+    assert trade.stop_loss == 0.1
+    assert trade.initial_stop_loss == 0.1
+
+    trade.set_isolated_liq(0.11)
+    trade._set_stop_loss(0.1, 0)
+    assert trade.liquidation_price == 0.11
+    assert trade.stop_loss == 0.11
+    assert trade.initial_stop_loss == 0.1
+
+    # lower stop doesn't move stoploss
+    trade._set_stop_loss(0.1, 0)
+    assert trade.liquidation_price == 0.11
+    assert trade.stop_loss == 0.11
+    assert trade.initial_stop_loss == 0.1
+
+    trade.stop_loss = None
+    trade.liquidation_price = None
+    trade.initial_stop_loss = None
+
+    trade._set_stop_loss(0.07, 0)
+    assert trade.liquidation_price is None
+    assert trade.stop_loss == 0.07
+    assert trade.initial_stop_loss == 0.07
+
+    trade.is_short = True
+    trade.recalc_open_trade_value()
+    trade.stop_loss = None
+    trade.initial_stop_loss = None
+
+    trade.set_isolated_liq(0.09)
+    assert trade.liquidation_price == 0.09
+    assert trade.stop_loss is None
+    assert trade.initial_stop_loss is None
+
+    trade._set_stop_loss(0.08, (1.0 / 9.0))
+    assert trade.liquidation_price == 0.09
+    assert trade.stop_loss == 0.08
+    assert trade.initial_stop_loss == 0.08
+
+    trade.set_isolated_liq(0.1)
+    assert trade.liquidation_price == 0.1
+    assert trade.stop_loss == 0.08
+    assert trade.initial_stop_loss == 0.08
+
+    trade.set_isolated_liq(0.07)
+    trade._set_stop_loss(0.1, (1.0 / 8.0))
+    assert trade.liquidation_price == 0.07
+    assert trade.stop_loss == 0.07
+    assert trade.initial_stop_loss == 0.08
+
+    # Stop doesn't move stop higher
+    trade._set_stop_loss(0.1, (1.0 / 9.0))
+    assert trade.liquidation_price == 0.07
+    assert trade.stop_loss == 0.07
+    assert trade.initial_stop_loss == 0.08
+
+
+@pytest.mark.parametrize('exchange,is_short,lev,minutes,rate,interest,trading_mode', [
+    ("binance", False, 3, 10, 0.0005, round(0.0008333333333333334, 8), margin),
+    ("binance", True, 3, 10, 0.0005, 0.000625, margin),
+    ("binance", False, 3, 295, 0.0005, round(0.004166666666666667, 8), margin),
+    ("binance", True, 3, 295, 0.0005, round(0.0031249999999999997, 8), margin),
+    ("binance", False, 3, 295, 0.00025, round(0.0020833333333333333, 8), margin),
+    ("binance", True, 3, 295, 0.00025, round(0.0015624999999999999, 8), margin),
+    ("binance", False, 5, 295, 0.0005, 0.005, margin),
+    ("binance", True, 5, 295, 0.0005, round(0.0031249999999999997, 8), margin),
+    ("binance", False, 1, 295, 0.0005, 0.0, spot),
+    ("binance", True, 1, 295, 0.0005, 0.003125, margin),
+
+    ("binance", False, 3, 10, 0.0005, 0.0, futures),
+    ("binance", True, 3, 295, 0.0005, 0.0, futures),
+    ("binance", False, 5, 295, 0.0005, 0.0, futures),
+    ("binance", True, 5, 295, 0.0005, 0.0, futures),
+    ("binance", False, 1, 295, 0.0005, 0.0, futures),
+    ("binance", True, 1, 295, 0.0005, 0.0, futures),
+
+    ("kraken", False, 3, 10, 0.0005, 0.040, margin),
+    ("kraken", True, 3, 10, 0.0005, 0.030, margin),
+    ("kraken", False, 3, 295, 0.0005, 0.06, margin),
+    ("kraken", True, 3, 295, 0.0005, 0.045, margin),
+    ("kraken", False, 3, 295, 0.00025, 0.03, margin),
+    ("kraken", True, 3, 295, 0.00025, 0.0225, margin),
+    ("kraken", False, 5, 295, 0.0005, round(0.07200000000000001, 8), margin),
+    ("kraken", True, 5, 295, 0.0005, 0.045, margin),
+    ("kraken", False, 1, 295, 0.0005, 0.0, spot),
+    ("kraken", True, 1, 295, 0.0005, 0.045, margin),
+
+])
+@pytest.mark.usefixtures("init_persistence")
+def test_interest(fee, exchange, is_short, lev, minutes, rate, interest,
+                  trading_mode):
     """
-        On this test we will buy and sell a crypto currency.
-        fee: 0.25% quote
+        10min, 5hr limit trade on Binance/Kraken at 3x,5x leverage
+        fee: 0.25 % quote
+        interest_rate: 0.05 % per 4 hrs
         open_rate: 2.00 quote
         close_rate: 2.20 quote
         amount: = 30.0 crypto
         stake_amount
-            60.0  quote
+            3x, -3x: 20.0  quote
+            5x, -5x: 12.0  quote
         borrowed
-             0 quote
-        open_value: (amount * open_rate) + (amount * open_rate * fee)
-             30 * 2 + 30 * 2 * 0.0025 = 60.15 quote
-        close_value:
-            (amount * close_rate) - (amount * close_rate * fee) - interest
-            (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) = 65.835
-        total_profit:
-            close_value - open_value
-            65.835 - 60.15             = 5.685
-        total_profit_ratio:
-            ((close_value/open_value) - 1) * leverage
-            ((65.835 / 60.15) - 1)  * 1 = 0.0945137157107232
+          10min
+             3x: 40 quote
+            -3x: 30 crypto
+             5x: 48 quote
+            -5x: 30 crypto
+             1x: 0
+            -1x: 30 crypto
+        hours: 1/6 (10 minutes)
+        time-periods:
+            10min
+                kraken: (1 + 1) 4hr_periods = 2 4hr_periods
+                binance: 1/24 24hr_periods
+            4.95hr
+                kraken: ceil(1 + 4.95/4) 4hr_periods = 3 4hr_periods
+                binance: ceil(4.95)/24 24hr_periods = 5/24 24hr_periods
+        interest: borrowed * interest_rate * time-periods
+          10min
+            binance     3x: 40 * 0.0005 * 1/24 = 0.0008333333333333334 quote
+            kraken      3x: 40 * 0.0005 * 2    = 0.040 quote
+            binace     -3x: 30 * 0.0005 * 1/24 = 0.000625 crypto
+            kraken     -3x: 30 * 0.0005 * 2    = 0.030 crypto
+          5hr
+            binance     3x: 40 * 0.0005 * 5/24 = 0.004166666666666667 quote
+            kraken      3x: 40 * 0.0005 * 3    = 0.06 quote
+            binace     -3x: 30 * 0.0005 * 5/24 = 0.0031249999999999997 crypto
+            kraken     -3x: 30 * 0.0005 * 3    = 0.045 crypto
+          0.00025 interest
+            binance     3x: 40 * 0.00025 * 5/24 = 0.0020833333333333333 quote
+            kraken      3x: 40 * 0.00025 * 3    = 0.03 quote
+            binace     -3x: 30 * 0.00025 * 5/24 = 0.0015624999999999999 crypto
+            kraken     -3x: 30 * 0.00025 * 3    = 0.0225 crypto
+          5x leverage, 0.0005 interest, 5hr
+            binance     5x: 48 * 0.0005 * 5/24 = 0.005 quote
+            kraken      5x: 48 * 0.0005 * 3    = 0.07200000000000001 quote
+            binace     -5x: 30 * 0.0005 * 5/24 = 0.0031249999999999997 crypto
+            kraken     -5x: 30 * 0.0005 * 3    = 0.045 crypto
+          1x leverage, 0.0005 interest, 5hr
+            binance,kraken 1x: 0.0 quote
+            binace        -1x: 30 * 0.0005 * 5/24 = 0.003125 crypto
+            kraken        -1x: 30 * 0.0005 * 3    = 0.045 crypto
+    """
 
+    trade = Trade(
+        pair='ADA/USDT',
+        stake_amount=20.0,
+        amount=30.0,
+        open_rate=2.0,
+        open_date=datetime.utcnow() - timedelta(minutes=minutes),
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        exchange=exchange,
+        leverage=lev,
+        interest_rate=rate,
+        is_short=is_short,
+        trading_mode=trading_mode
+    )
+
+    assert round(float(trade.calculate_interest()), 8) == interest
+
+
+@pytest.mark.parametrize('is_short,lev,borrowed,trading_mode', [
+    (False, 1.0, 0.0, spot),
+    (True, 1.0, 30.0, margin),
+    (False, 3.0, 40.0, margin),
+    (True, 3.0, 30.0, margin),
+])
+@pytest.mark.usefixtures("init_persistence")
+def test_borrowed(limit_buy_order_usdt, limit_sell_order_usdt, fee,
+                  caplog, is_short, lev, borrowed, trading_mode):
+    """
+        10 minute limit trade on Binance/Kraken at 1x, 3x leverage
+        fee: 0.25% quote
+        interest_rate: 0.05% per 4 hrs
+        open_rate: 2.00 quote
+        close_rate: 2.20 quote
+        amount: = 30.0 crypto
+        stake_amount
+            1x,-1x: 60.0  quote
+            3x,-3x: 20.0  quote
+        borrowed
+             1x:  0 quote
+             3x: 40 quote
+            -1x: 30 crypto
+            -3x: 30 crypto
+        hours: 1/6 (10 minutes)
+        time-periods:
+            kraken: (1 + 1) 4hr_periods = 2 4hr_periods
+            binance: 1/24 24hr_periods
+        interest: borrowed * interest_rate * time-periods
+            1x            :  /
+            binance     3x: 40 * 0.0005 * 1/24 = 0.0008333333333333334 quote
+            kraken      3x: 40 * 0.0005 * 2 = 0.040 quote
+            binace -1x,-3x: 30 * 0.0005 * 1/24 = 0.000625 crypto
+            kraken -1x,-3x: 30 * 0.0005 * 2 = 0.030 crypto
+        open_value: (amount * open_rate) ± (amount * open_rate * fee)
+             1x, 3x: 30 * 2 + 30 * 2 * 0.0025 = 60.15 quote
+            -1x,-3x: 30 * 2 - 30 * 2 * 0.0025 = 59.850 quote
+        amount_closed:
+            1x, 3x         : amount
+            -1x, -3x       : amount + interest
+            binance -1x,-3x: 30 + 0.000625 = 30.000625 crypto
+            kraken  -1x,-3x: 30 + 0.03 = 30.03 crypto
+        close_value:
+             1x, 3x: (amount_closed * close_rate) - (amount_closed * close_rate * fee) - interest
+            -1x,-3x: (amount_closed * close_rate) + (amount_closed * close_rate * fee)
+            binance,kraken 1x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025)         = 65.835
+            binance        3x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) - 0.00083333 = 65.83416667
+            kraken         3x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) - 0.040 = 65.795
+            binance   -1x,-3x: (30.000625 * 2.20) + (30.000625 * 2.20 * 0.0025) = 66.16637843750001
+            kraken    -1x,-3x: (30.03 * 2.20) + (30.03 * 2.20 * 0.0025)         = 66.231165
+        total_profit:
+            1x, 3x : close_value - open_value
+            -1x,-3x: open_value  - close_value
+            binance,kraken 1x: 65.835 - 60.15             = 5.685
+            binance        3x: 65.83416667 - 60.15        = 5.684166670000003
+            kraken         3x: 65.795 - 60.15             = 5.645
+            binance   -1x,-3x: 59.850 - 66.16637843750001 = -6.316378437500013
+            kraken    -1x,-3x: 59.850 - 66.231165          = -6.381165
+        total_profit_ratio:
+            1x, 3x : ((close_value/open_value) - 1) * leverage
+            -1x,-3x: (1 - (close_value/open_value)) * leverage
+            binance  1x: ((65.835 / 60.15) - 1)  * 1 = 0.0945137157107232
+            binance  3x: ((65.83416667 / 60.15) - 1)  * 3 = 0.2834995845386534
+            kraken   1x: ((65.835 / 60.15) - 1)  * 1 = 0.0945137157107232
+            kraken   3x: ((65.795 / 60.15) - 1)  * 3 = 0.2815461346633419
+            binance -1x: (1-(66.1663784375 / 59.85)) * 1 = -0.1055368159983292
+            binance -3x: (1-(66.1663784375 / 59.85)) * 3 = -0.3166104479949876
+            kraken  -1x: (1-(66.2311650 / 59.85)) * 1    = -0.106619298245614
+            kraken  -3x: (1-(66.2311650 / 59.85)) * 3    = -0.319857894736842
     """
 
     trade = Trade(
@@ -101,30 +370,141 @@ def test_update_limit_order(limit_buy_order_usdt, limit_sell_order_usdt, fee, ca
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='binance',
+        is_short=is_short,
+        leverage=lev,
+        trading_mode=trading_mode
+    )
+    assert trade.borrowed == borrowed
+
+
+@pytest.mark.parametrize('is_short,open_rate,close_rate,lev,profit,trading_mode', [
+    (False, 2.0, 2.2, 1.0, 0.09451372, spot),
+    (True, 2.2, 2.0, 3.0, 0.25894253, margin),
+])
+@pytest.mark.usefixtures("init_persistence")
+def test_update_limit_order(fee, caplog, limit_buy_order_usdt, limit_sell_order_usdt, time_machine,
+                            is_short, open_rate, close_rate, lev, profit, trading_mode):
+    """
+        10 minute limit trade on Binance/Kraken at 1x, 3x leverage
+        fee: 0.25% quote
+        interest_rate: 0.05% per 4 hrs
+        open_rate: 2.00 quote
+        close_rate: 2.20 quote
+        amount: = 30.0 crypto
+        stake_amount
+            1x,-1x: 60.0  quote
+            3x,-3x: 20.0  quote
+        borrowed
+             1x:  0 quote
+             3x: 40 quote
+            -1x: 30 crypto
+            -3x: 30 crypto
+        hours: 1/6 (10 minutes)
+        time-periods:
+            kraken: (1 + 1) 4hr_periods = 2 4hr_periods
+            binance: 1/24 24hr_periods
+        interest: borrowed * interest_rate * time-periods
+            1x            :  /
+            binance     3x: 40 * 0.0005 * 1/24 = 0.0008333333333333334 quote
+            kraken      3x: 40 * 0.0005 * 2 = 0.040 quote
+            binace -1x,-3x: 30 * 0.0005 * 1/24 = 0.000625 crypto
+            kraken -1x,-3x: 30 * 0.0005 * 2 = 0.030 crypto
+        open_value: (amount * open_rate) ± (amount * open_rate * fee)
+             1x, 3x: 30 * 2 + 30 * 2 * 0.0025 = 60.15 quote
+            -1x,-3x: 30 * 2 - 30 * 2 * 0.0025 = 59.850 quote
+        amount_closed:
+            1x, 3x         : amount
+            -1x, -3x       : amount + interest
+            binance -1x,-3x: 30 + 0.000625 = 30.000625 crypto
+            kraken  -1x,-3x: 30 + 0.03 = 30.03 crypto
+        close_value:
+             1x, 3x: (amount_closed * close_rate) - (amount_closed * close_rate * fee) - interest
+            -1x,-3x: (amount_closed * close_rate) + (amount_closed * close_rate * fee)
+            binance,kraken 1x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025)         = 65.835
+            binance        3x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) - 0.00083333 = 65.83416667
+            kraken         3x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) - 0.040 = 65.795
+            binance   -1x,-3x: (30.000625 * 2.20) + (30.000625 * 2.20 * 0.0025) = 66.16637843750001
+            kraken    -1x,-3x: (30.03 * 2.20) + (30.03 * 2.20 * 0.0025)         = 66.231165
+        total_profit:
+            1x, 3x : close_value - open_value
+            -1x,-3x: open_value  - close_value
+            binance,kraken 1x: 65.835 - 60.15             = 5.685
+            binance        3x: 65.83416667 - 60.15        = 5.684166670000003
+            kraken         3x: 65.795 - 60.15             = 5.645
+            binance   -1x,-3x: 59.850 - 66.16637843750001 = -6.316378437500013
+            kraken    -1x,-3x: 59.850 - 66.231165          = -6.381165
+        total_profit_ratio:
+            1x, 3x : ((close_value/open_value) - 1) * leverage
+            -1x,-3x: (1 - (close_value/open_value)) * leverage
+            binance  1x: ((65.835 / 60.15) - 1)  * 1 = 0.0945137157107232
+            binance  3x: ((65.83416667 / 60.15) - 1)  * 3 = 0.2834995845386534
+            kraken   1x: ((65.835 / 60.15) - 1)  * 1 = 0.0945137157107232
+            kraken   3x: ((65.795 / 60.15) - 1)  * 3 = 0.2815461346633419
+            binance -1x: (1-(66.1663784375 / 59.85)) * 1 = -0.1055368159983292
+            binance -3x: (1-(66.1663784375 / 59.85)) * 3 = -0.3166104479949876
+            kraken  -1x: (1-(66.2311650 / 59.85)) * 1    = -0.106619298245614
+            kraken  -3x: (1-(66.2311650 / 59.85)) * 3    = -0.319857894736842
+        open_rate: 2.2, close_rate: 2.0, -3x, binance, short
+            open_value: 30 * 2.2 - 30 * 2.2 * 0.0025 = 65.835 quote
+            amount_closed: 30 + 0.000625 = 30.000625 crypto
+            close_value: (30.000625 * 2.0) + (30.000625 * 2.0 * 0.0025) = 60.151253125
+            total_profit: 65.835 - 60.151253125 = 5.683746874999997
+            total_profit_ratio: (1-(60.151253125/65.835)) * 3 = 0.2589996297562085
+
+    """
+    time_machine.move_to("2022-03-31 20:45:00 +00:00")
+
+    enter_order = limit_sell_order_usdt if is_short else limit_buy_order_usdt
+    exit_order = limit_buy_order_usdt if is_short else limit_sell_order_usdt
+    entry_side, exit_side = ("sell", "buy") if is_short else ("buy", "sell")
+
+    trade = Trade(
+        id=2,
+        pair='ADA/USDT',
+        stake_amount=60.0,
+        open_rate=open_rate,
+        amount=30.0,
+        is_open=True,
+        open_date=arrow.utcnow().datetime,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        exchange='binance',
+        is_short=is_short,
+        interest_rate=0.0005,
+        leverage=lev,
+        trading_mode=trading_mode
     )
     assert trade.open_order_id is None
     assert trade.close_profit is None
     assert trade.close_date is None
 
     trade.open_order_id = 'something'
-    trade.update(limit_buy_order_usdt)
+    oobj = Order.parse_from_ccxt_object(enter_order, 'ADA/USDT', entry_side)
+    trade.update_trade(oobj)
     assert trade.open_order_id is None
-    assert trade.open_rate == 2.00
+    assert trade.open_rate == open_rate
     assert trade.close_profit is None
     assert trade.close_date is None
-    assert log_has_re(r"LIMIT_BUY has been fulfilled for Trade\(id=2, "
-                      r"pair=ADA/USDT, amount=30.00000000, open_rate=2.00000000, open_since=.*\).",
+    assert log_has_re(f"LIMIT_{entry_side.upper()} has been fulfilled for "
+                      r"Trade\(id=2, pair=ADA/USDT, amount=30.00000000, "
+                      f"is_short={is_short}, leverage={lev}, open_rate={open_rate}0000000, "
+                      r"open_since=.*\).",
                       caplog)
 
     caplog.clear()
     trade.open_order_id = 'something'
-    trade.update(limit_sell_order_usdt)
+    time_machine.move_to("2022-03-31 21:45:05 +00:00")
+    oobj = Order.parse_from_ccxt_object(exit_order, 'ADA/USDT', exit_side)
+    trade.update_trade(oobj)
+
     assert trade.open_order_id is None
-    assert trade.close_rate == 2.20
-    assert trade.close_profit == round(0.0945137157107232, 8)
+    assert trade.close_rate == close_rate
+    assert trade.close_profit == profit
     assert trade.close_date is not None
-    assert log_has_re(r"LIMIT_SELL has been fulfilled for Trade\(id=2, "
-                      r"pair=ADA/USDT, amount=30.00000000, open_rate=2.00000000, open_since=.*\).",
+    assert log_has_re(f"LIMIT_{exit_side.upper()} has been fulfilled for "
+                      r"Trade\(id=2, pair=ADA/USDT, amount=30.00000000, "
+                      f"is_short={is_short}, leverage={lev}, open_rate={open_rate}0000000, "
+                      r"open_since=.*\).",
                       caplog)
     caplog.clear()
 
@@ -142,54 +522,92 @@ def test_update_market_order(market_buy_order_usdt, market_sell_order_usdt, fee,
         fee_close=fee.return_value,
         open_date=arrow.utcnow().datetime,
         exchange='binance',
+        trading_mode=margin,
+        leverage=1.0,
     )
 
     trade.open_order_id = 'something'
-    trade.update(market_buy_order_usdt)
+    oobj = Order.parse_from_ccxt_object(market_buy_order_usdt, 'ADA/USDT', 'buy')
+    trade.update_trade(oobj)
     assert trade.open_order_id is None
     assert trade.open_rate == 2.0
     assert trade.close_profit is None
     assert trade.close_date is None
     assert log_has_re(r"MARKET_BUY has been fulfilled for Trade\(id=1, "
-                      r"pair=ADA/USDT, amount=30.00000000, open_rate=2.00000000, open_since=.*\).",
+                      r"pair=ADA/USDT, amount=30.00000000, is_short=False, leverage=1.0, "
+                      r"open_rate=2.00000000, open_since=.*\).",
                       caplog)
 
     caplog.clear()
     trade.is_open = True
     trade.open_order_id = 'something'
-    trade.update(market_sell_order_usdt)
+    oobj = Order.parse_from_ccxt_object(market_sell_order_usdt, 'ADA/USDT', 'sell')
+    trade.update_trade(oobj)
     assert trade.open_order_id is None
     assert trade.close_rate == 2.2
     assert trade.close_profit == round(0.0945137157107232, 8)
     assert trade.close_date is not None
     assert log_has_re(r"MARKET_SELL has been fulfilled for Trade\(id=1, "
-                      r"pair=ADA/USDT, amount=30.00000000, open_rate=2.00000000, open_since=.*\).",
+                      r"pair=ADA/USDT, amount=30.00000000, is_short=False, leverage=1.0, "
+                      r"open_rate=2.00000000, open_since=.*\).",
                       caplog)
 
 
+@pytest.mark.parametrize(
+    'exchange,is_short,lev,open_value,close_value,profit,profit_ratio,trading_mode,funding_fees', [
+        ("binance", False, 1, 60.15, 65.835, 5.685, 0.09451371, spot, 0.0),
+        ("binance", True, 1, 59.850, 66.1663784375, -6.3163784375, -0.1055368, margin, 0.0),
+        ("binance", False, 3, 60.15, 65.83416667, 5.68416667, 0.28349958, margin, 0.0),
+        ("binance", True, 3, 59.85, 66.1663784375, -6.3163784375, -0.31661044, margin, 0.0),
+
+        ("kraken", False, 1, 60.15, 65.835, 5.685, 0.09451371, spot, 0.0),
+        ("kraken", True, 1, 59.850, 66.231165, -6.381165, -0.1066192, margin, 0.0),
+        ("kraken", False, 3, 60.15, 65.795, 5.645, 0.28154613, margin, 0.0),
+        ("kraken", True, 3, 59.850, 66.231165, -6.381165, -0.3198578, margin, 0.0),
+
+        ("binance", False, 1, 60.15, 65.835,  5.685, 0.09451371, futures, 0.0),
+        ("binance", False, 1, 60.15, 66.835,  6.685, 0.11113881, futures, 1.0),
+        ("binance", True, 1, 59.85,  66.165, -6.315, -0.10551378, futures, 0.0),
+        ("binance", True, 1, 59.85,  67.165, -7.315, -0.12222222, futures, -1.0),
+        ("binance", False, 3, 60.15, 64.835,  4.685, 0.23366583, futures, -1.0),
+        ("binance", True, 3, 59.85,  65.165, -5.315, -0.26641604, futures, 1.0),
+    ])
 @pytest.mark.usefixtures("init_persistence")
-def test_calc_open_close_trade_price(limit_buy_order_usdt, limit_sell_order_usdt, fee):
-    trade = Trade(
+def test_calc_open_close_trade_price(
+    limit_buy_order_usdt, limit_sell_order_usdt, fee, exchange, is_short, lev,
+    open_value, close_value, profit, profit_ratio, trading_mode, funding_fees
+):
+    trade: Trade = Trade(
         pair='ADA/USDT',
         stake_amount=60.0,
         open_rate=2.0,
         amount=30.0,
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
+        interest_rate=0.0005,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        exchange='binance',
+        exchange=exchange,
+        is_short=is_short,
+        leverage=lev,
+        trading_mode=trading_mode,
+        funding_fees=funding_fees
     )
 
-    trade.open_order_id = 'something'
-    trade.update(limit_buy_order_usdt)
-    assert trade._calc_open_trade_value() == 60.15
-    trade.update(limit_sell_order_usdt)
-    assert isclose(trade.calc_close_trade_value(), 65.835)
+    trade.open_order_id = f'something-{is_short}-{lev}-{exchange}'
 
-    # Profit in USDT
-    assert trade.calc_profit() == 5.685
+    oobj = Order.parse_from_ccxt_object(limit_buy_order_usdt, 'ADA/USDT', 'buy')
+    trade.update_trade(oobj)
 
-    # Profit in percent
-    assert trade.calc_profit_ratio() == round(0.0945137157107232, 8)
+    oobj = Order.parse_from_ccxt_object(limit_sell_order_usdt, 'ADA/USDT', 'sell')
+    trade.update_trade(oobj)
+
+    trade.open_rate = 2.0
+    trade.close_rate = 2.2
+    trade.recalc_open_trade_value()
+    assert isclose(trade._calc_open_trade_value(), open_value)
+    assert isclose(trade.calc_close_trade_value(), close_value)
+    assert isclose(trade.calc_profit(), round(profit, 8))
+    assert pytest.approx(trade.calc_profit_ratio()) == profit_ratio
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -202,8 +620,10 @@ def test_trade_close(limit_buy_order_usdt, limit_sell_order_usdt, fee):
         is_open=True,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
-        open_date=arrow.Arrow(2020, 2, 1, 15, 5, 1).datetime,
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
+        interest_rate=0.0005,
         exchange='binance',
+        trading_mode=margin
     )
     assert trade.close_profit is None
     assert trade.close_date is None
@@ -232,10 +652,13 @@ def test_calc_close_trade_price_exception(limit_buy_order_usdt, fee):
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='binance',
+        trading_mode=margin,
+        leverage=1.0,
     )
 
     trade.open_order_id = 'something'
-    trade.update(limit_buy_order_usdt)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order_usdt, 'ADA/USDT', 'buy')
+    trade.update_trade(oobj)
     assert trade.calc_close_trade_value() == 0.0
 
 
@@ -249,6 +672,7 @@ def test_update_open_order(limit_buy_order_usdt):
         fee_open=0.1,
         fee_close=0.1,
         exchange='binance',
+        trading_mode=margin
     )
 
     assert trade.open_order_id is None
@@ -256,7 +680,8 @@ def test_update_open_order(limit_buy_order_usdt):
     assert trade.close_date is None
 
     limit_buy_order_usdt['status'] = 'open'
-    trade.update(limit_buy_order_usdt)
+    oobj = Order.parse_from_ccxt_object(limit_buy_order_usdt, 'ADA/USDT', 'buy')
+    trade.update_trade(oobj)
 
     assert trade.open_order_id is None
     assert trade.close_profit is None
@@ -273,75 +698,211 @@ def test_update_invalid_order(limit_buy_order_usdt):
         fee_open=0.1,
         fee_close=0.1,
         exchange='binance',
+        trading_mode=margin
     )
     limit_buy_order_usdt['type'] = 'invalid'
+    oobj = Order.parse_from_ccxt_object(limit_buy_order_usdt, 'ADA/USDT', 'meep')
     with pytest.raises(ValueError, match=r'Unknown order type'):
-        trade.update(limit_buy_order_usdt)
+        trade.update_trade(oobj)
 
 
+@pytest.mark.parametrize('exchange', ['binance', 'kraken'])
+@pytest.mark.parametrize('trading_mode', [spot, margin, futures])
+@pytest.mark.parametrize('lev', [1, 3])
+@pytest.mark.parametrize('is_short,fee_rate,result', [
+    (False, 0.003, 60.18),
+    (False, 0.0025, 60.15),
+    (False, 0.003, 60.18),
+    (False, 0.0025, 60.15),
+    (True, 0.003, 59.82),
+    (True, 0.0025, 59.85),
+    (True, 0.003, 59.82),
+    (True, 0.0025, 59.85)
+])
 @pytest.mark.usefixtures("init_persistence")
-def test_calc_open_trade_value(limit_buy_order_usdt, fee):
-    """
-        fee: 0.25 %, 0.3% quote
-        open_rate: 2.00 quote
-        amount: = 30.0 crypto
-        stake_amount
-            60.0  quote
-        open_value: (amount * open_rate) + (amount * open_rate * fee)
-        0.25% fee
-            30 * 2 + 30 * 2 * 0.0025 = 60.15 quote
-        0.3% fee
-            30 * 2 + 30 * 2 * 0.003  = 60.18 quote
-    """
+def test_calc_open_trade_value(
+    limit_buy_order_usdt,
+    exchange,
+    lev,
+    is_short,
+    fee_rate,
+    result,
+    trading_mode
+):
+    # 10 minute limit trade on Binance/Kraken at 1x, 3x leverage
+    # fee: 0.25 %, 0.3% quote
+    # open_rate: 2.00 quote
+    # amount: = 30.0 crypto
+    # stake_amount
+    #     1x, -1x: 60.0  quote
+    #     3x, -3x: 20.0  quote
+    # open_value: (amount * open_rate) ± (amount * open_rate * fee)
+    # 0.25% fee
+    #      1x, 3x: 30 * 2 + 30 * 2 * 0.0025 = 60.15 quote
+    #     -1x,-3x: 30 * 2 - 30 * 2 * 0.0025 = 59.85 quote
+    # 0.3% fee
+    #      1x, 3x: 30 * 2 + 30 * 2 * 0.003  = 60.18 quote
+    #     -1x,-3x: 30 * 2 - 30 * 2 * 0.003  = 59.82 quote
     trade = Trade(
         pair='ADA/USDT',
         stake_amount=60.0,
         amount=30.0,
         open_rate=2.0,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        exchange='binance',
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
+        fee_open=fee_rate,
+        fee_close=fee_rate,
+        exchange=exchange,
+        leverage=lev,
+        is_short=is_short,
+        trading_mode=trading_mode
     )
     trade.open_order_id = 'open_trade'
-    trade.update(limit_buy_order_usdt)  # Buy @ 2.0
+    oobj = Order.parse_from_ccxt_object(
+        limit_buy_order_usdt, 'ADA/USDT', 'sell' if is_short else 'buy')
+    trade.update_trade(oobj)  # Buy @ 2.0
 
     # Get the open rate price with the standard fee rate
-    assert trade._calc_open_trade_value() == 60.15
-    trade.fee_open = 0.003
-    # Get the open rate price with a custom fee rate
-    assert trade._calc_open_trade_value() == 60.18
+    assert trade._calc_open_trade_value() == result
 
 
+@pytest.mark.parametrize(
+    'exchange,is_short,lev,open_rate,close_rate,fee_rate,result,trading_mode,funding_fees', [
+        ('binance', False, 1, 2.0, 2.5, 0.0025, 74.8125, spot, 0),
+        ('binance', False, 1, 2.0, 2.5, 0.003, 74.775, spot, 0),
+        ('binance', False, 1, 2.0, 2.2, 0.005, 65.67, margin, 0),
+        ('binance', False, 3, 2.0, 2.5, 0.0025, 74.81166667, margin, 0),
+        ('binance', False, 3, 2.0, 2.5, 0.003, 74.77416667, margin, 0),
+        ('binance', True, 3, 2.2, 2.5, 0.0025, 75.18906641, margin, 0),
+        ('binance', True, 3, 2.2, 2.5, 0.003, 75.22656719, margin, 0),
+        ('binance', True, 1, 2.2, 2.5, 0.0025, 75.18906641, margin, 0),
+        ('binance', True, 1, 2.2, 2.5, 0.003, 75.22656719, margin, 0),
+
+        # Kraken
+        ('kraken', False, 3, 2.0, 2.5, 0.0025, 74.7725, margin, 0),
+        ('kraken', False, 3, 2.0, 2.5, 0.003, 74.735, margin, 0),
+        ('kraken', True, 3, 2.2, 2.5, 0.0025, 75.2626875, margin, 0),
+        ('kraken', True, 3, 2.2, 2.5, 0.003, 75.300225, margin, 0),
+        ('kraken', True, 1, 2.2, 2.5, 0.0025, 75.2626875, margin, 0),
+        ('kraken', True, 1, 2.2, 2.5, 0.003, 75.300225, margin, 0),
+
+        ('binance', False, 1, 2.0, 2.5, 0.0025, 75.8125, futures, 1),
+        ('binance', False, 3, 2.0, 2.5, 0.0025, 73.8125, futures, -1),
+        ('binance', True, 3, 2.0, 2.5, 0.0025,  74.1875, futures, 1),
+        ('binance', True, 1, 2.0, 2.5, 0.0025,  76.1875, futures, -1),
+
+    ])
 @pytest.mark.usefixtures("init_persistence")
-def test_calc_close_trade_price(limit_buy_order_usdt, limit_sell_order_usdt, fee):
+def test_calc_close_trade_price(
+    open_rate, exchange, is_short,
+    lev, close_rate, fee_rate, result, trading_mode, funding_fees
+):
     trade = Trade(
         pair='ADA/USDT',
         stake_amount=60.0,
         amount=30.0,
-        open_rate=2.0,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        exchange='binance',
+        open_rate=open_rate,
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
+        fee_open=fee_rate,
+        fee_close=fee_rate,
+        exchange=exchange,
+        interest_rate=0.0005,
+        is_short=is_short,
+        leverage=lev,
+        trading_mode=trading_mode,
+        funding_fees=funding_fees
     )
     trade.open_order_id = 'close_trade'
-    trade.update(limit_buy_order_usdt)  # Buy @ 2.0
-
-    # Get the close rate price with a custom close rate and a regular fee rate
-    assert trade.calc_close_trade_value(rate=2.5) == 74.8125
-    # Get the close rate price with a custom close rate and a custom fee rate
-    assert trade.calc_close_trade_value(rate=2.5, fee=0.003) == 74.775
-    # Test when we apply a Sell order, and ask price with a custom fee rate
-    trade.update(limit_sell_order_usdt)
-    assert trade.calc_close_trade_value(fee=0.005) == 65.67
+    assert round(trade.calc_close_trade_value(rate=close_rate, fee=fee_rate), 8) == result
 
 
+@pytest.mark.parametrize(
+    'exchange,is_short,lev,close_rate,fee_close,profit,profit_ratio,trading_mode,funding_fees', [
+        ('binance', False, 1, 2.1, 0.0025, 2.6925, 0.044763092, spot, 0),
+        ('binance', False, 3, 2.1, 0.0025, 2.69166667, 0.134247714, margin, 0),
+        ('binance', True, 1, 2.1, 0.0025, -3.3088157, -0.055285142, margin, 0),
+        ('binance', True, 3, 2.1, 0.0025, -3.3088157, -0.16585542, margin, 0),
+
+        ('binance', False, 1, 1.9, 0.0025, -3.2925, -0.054738154, margin, 0),
+        ('binance', False, 3, 1.9, 0.0025, -3.29333333, -0.164256026, margin, 0),
+        ('binance', True, 1, 1.9, 0.0025, 2.70630953, 0.0452182043, margin, 0),
+        ('binance', True, 3, 1.9, 0.0025, 2.70630953, 0.135654613, margin, 0),
+
+        ('binance', False, 1, 2.2, 0.0025, 5.685, 0.09451371, margin, 0),
+        ('binance', False, 3, 2.2, 0.0025, 5.68416667, 0.28349958, margin, 0),
+        ('binance', True, 1, 2.2, 0.0025, -6.3163784, -0.10553681, margin, 0),
+        ('binance', True, 3, 2.2, 0.0025, -6.3163784, -0.31661044, margin, 0),
+
+        # Kraken
+        ('kraken', False, 1, 2.1, 0.0025, 2.6925, 0.044763092, spot, 0),
+        ('kraken', False, 3, 2.1, 0.0025, 2.6525, 0.132294264, margin, 0),
+        ('kraken', True, 1, 2.1, 0.0025, -3.3706575, -0.056318421, margin, 0),
+        ('kraken', True, 3, 2.1, 0.0025, -3.3706575, -0.168955263, margin, 0),
+
+        ('kraken', False, 1, 1.9, 0.0025, -3.2925, -0.054738154, margin, 0),
+        ('kraken', False, 3, 1.9, 0.0025, -3.3325, -0.166209476, margin, 0),
+        ('kraken', True, 1, 1.9, 0.0025, 2.6503575, 0.044283333, margin, 0),
+        ('kraken', True, 3, 1.9, 0.0025, 2.6503575, 0.132850000, margin, 0),
+
+        ('kraken', False, 1, 2.2, 0.0025, 5.685, 0.09451371, margin, 0),
+        ('kraken', False, 3, 2.2, 0.0025, 5.645, 0.28154613, margin, 0),
+        ('kraken', True, 1, 2.2, 0.0025, -6.381165, -0.1066192, margin, 0),
+        ('kraken', True, 3, 2.2, 0.0025, -6.381165, -0.3198578, margin, 0),
+
+        ('binance', False, 1, 2.1, 0.003, 2.66100000, 0.044239401, spot, 0),
+        ('binance', False, 1, 1.9, 0.003, -3.3209999, -0.055211970, spot, 0),
+        ('binance', False, 1, 2.2, 0.003, 5.6520000, 0.093965087, spot, 0),
+
+        # # FUTURES, funding_fee=1
+        ('binance', False, 1, 2.1, 0.0025, 3.6925, 0.06138819, futures, 1),
+        ('binance', False, 3, 2.1, 0.0025, 3.6925, 0.18416458, futures, 1),
+        ('binance', True, 1, 2.1, 0.0025, -2.3074999, -0.03855472, futures, 1),
+        ('binance', True, 3, 2.1, 0.0025, -2.3074999, -0.11566416, futures, 1),
+
+        ('binance', False, 1, 1.9, 0.0025, -2.2925, -0.03811305, futures, 1),
+        ('binance', False, 3, 1.9, 0.0025, -2.2925, -0.11433915, futures, 1),
+        ('binance', True, 1, 1.9, 0.0025, 3.7075, 0.06194653, futures, 1),
+        ('binance', True, 3, 1.9, 0.0025, 3.7075, 0.18583959, futures, 1),
+
+        ('binance', False, 1, 2.2, 0.0025, 6.685, 0.11113881, futures, 1),
+        ('binance', False, 3, 2.2, 0.0025, 6.685, 0.33341645, futures, 1),
+        ('binance', True, 1, 2.2, 0.0025, -5.315, -0.08880534, futures, 1),
+        ('binance', True, 3, 2.2, 0.0025, -5.315, -0.26641604, futures, 1),
+
+        # FUTURES, funding_fee=-1
+        ('binance', False, 1, 2.1, 0.0025, 1.6925, 0.02813798, futures, -1),
+        ('binance', False, 3, 2.1, 0.0025, 1.6925, 0.08441396, futures, -1),
+        ('binance', True, 1, 2.1, 0.0025, -4.307499, -0.07197159, futures, -1),
+        ('binance', True, 3, 2.1, 0.0025, -4.307499, -0.21591478, futures, -1),
+
+        ('binance', False, 1, 1.9, 0.0025, -4.292499, -0.07136325, futures, -1),
+        ('binance', False, 3, 1.9, 0.0025, -4.292499, -0.21408977, futures, -1),
+        ('binance', True, 1, 1.9, 0.0025, 1.7075, 0.02852965, futures, -1),
+        ('binance', True, 3, 1.9, 0.0025, 1.7075, 0.08558897, futures, -1),
+
+        ('binance', False, 1, 2.2, 0.0025, 4.684999, 0.07788861, futures, -1),
+        ('binance', False, 3, 2.2, 0.0025, 4.684999, 0.23366583, futures, -1),
+        ('binance', True, 1, 2.2, 0.0025, -7.315, -0.12222222, futures, -1),
+        ('binance', True, 3, 2.2, 0.0025, -7.315, -0.36666666, futures, -1),
+    ])
 @pytest.mark.usefixtures("init_persistence")
-def test_calc_profit(limit_buy_order_usdt, limit_sell_order_usdt, fee):
+def test_calc_profit(
+    exchange,
+    is_short,
+    lev,
+    close_rate,
+    fee_close,
+    profit,
+    profit_ratio,
+    trading_mode,
+    funding_fees
+):
     """
+        10 minute limit trade on Binance/Kraken at 1x, 3x leverage
         arguments:
             fee:
                 0.25% quote
                 0.30% quote
+            interest_rate: 0.05% per 4 hrs
             open_rate: 2.0 quote
             close_rate:
                 1.9 quote
@@ -349,121 +910,222 @@ def test_calc_profit(limit_buy_order_usdt, limit_sell_order_usdt, fee):
                 2.2 quote
             amount: = 30.0 crypto
             stake_amount
-                60.0  quote
-        open_value: (amount * open_rate) + (amount * open_rate * fee)
+                1x,-1x: 60.0  quote
+                3x,-3x: 20.0  quote
+            hours: 1/6 (10 minutes)
+            funding_fees: 1
+        borrowed
+             1x:  0 quote
+             3x: 40 quote
+            -1x: 30 crypto
+            -3x: 30 crypto
+        time-periods:
+            kraken: (1 + 1) 4hr_periods = 2 4hr_periods
+            binance: 1/24 24hr_periods
+        interest: borrowed * interest_rate * time-periods
+            1x            :  /
+            binance     3x: 40 * 0.0005 * 1/24 = 0.0008333333333333334 quote
+            kraken      3x: 40 * 0.0005 * 2    = 0.040 quote
+            binace -1x,-3x: 30 * 0.0005 * 1/24 = 0.000625 crypto
+            kraken -1x,-3x: 30 * 0.0005 * 2    = 0.030 crypto
+        open_value: (amount * open_rate) ± (amount * open_rate * fee)
           0.0025 fee
-            30 * 2 + 30 * 2 * 0.0025 = 60.15 quote
-            30 * 2 - 30 * 2 * 0.0025 = 59.85 quote
+             1x, 3x: 30 * 2 + 30 * 2 * 0.0025 = 60.15 quote
+            -1x,-3x: 30 * 2 - 30 * 2 * 0.0025 = 59.85 quote
           0.003 fee: Is only applied to close rate in this test
+        amount_closed:
+            1x, 3x                         = amount
+            -1x, -3x                       = amount + interest
+            binance -1x,-3x: 30 + 0.000625 = 30.000625 crypto
+            kraken  -1x,-3x: 30 + 0.03     = 30.03 crypto
         close_value:
             equations:
-                (amount_closed * close_rate) - (amount_closed * close_rate * fee)
+                1x, 3x: (amount_closed * close_rate) - (amount_closed * close_rate * fee) - interest
+                -1x,-3x: (amount_closed * close_rate) + (amount_closed * close_rate * fee)
             2.1 quote
-                (30.00 * 2.1) - (30.00 * 2.1 * 0.0025)   = 62.8425
+                bin,krak  1x: (30.00 * 2.1) - (30.00 * 2.1 * 0.0025)                = 62.8425
+                bin       3x: (30.00 * 2.1) - (30.00 * 2.1 * 0.0025) - 0.0008333333 = 62.8416666667
+                krak      3x: (30.00 * 2.1) - (30.00 * 2.1 * 0.0025) - 0.040        = 62.8025
+                bin  -1x,-3x: (30.000625 * 2.1) + (30.000625 * 2.1 * 0.0025)        = 63.15881578125
+                krak -1x,-3x: (30.03 * 2.1) + (30.03 * 2.1 * 0.0025)                = 63.2206575
             1.9 quote
-                (30.00 * 1.9) - (30.00 * 1.9 * 0.0025)   = 56.8575
+                bin,krak  1x: (30.00 * 1.9) - (30.00 * 1.9 * 0.0025)                = 56.8575
+                bin       3x: (30.00 * 1.9) - (30.00 * 1.9 * 0.0025) - 0.0008333333 = 56.85666667
+                krak      3x: (30.00 * 1.9) - (30.00 * 1.9 * 0.0025) - 0.040        = 56.8175
+                bin  -1x,-3x: (30.000625 * 1.9) + (30.000625 * 1.9 * 0.0025)        = 57.14369046875
+                krak -1x,-3x: (30.03 * 1.9) + (30.03 * 1.9 * 0.0025)                = 57.1996425
             2.2 quote
-                (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) = 65.835
+                bin,krak  1x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025)              = 65.835
+                bin       3x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) - 0.00083333 = 65.83416667
+                krak      3x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) - 0.040      = 65.795
+                bin  -1x,-3x: (30.000625 * 2.20) + (30.000625 * 2.20 * 0.0025)      = 66.1663784375
+                krak -1x,-3x: (30.03 * 2.20) + (30.03 * 2.20 * 0.0025)              = 66.231165
         total_profit:
             equations:
-                close_value - open_value
+                1x, 3x : close_value - open_value
+                -1x,-3x: open_value - close_value
             2.1 quote
-                62.8425 - 60.15 = 2.6925
+                binance,kraken 1x: 62.8425     - 60.15          = 2.6925
+                binance        3x: 62.84166667 - 60.15          = 2.69166667
+                kraken         3x: 62.8025     - 60.15          = 2.6525
+                binance   -1x,-3x: 59.850      - 63.15881578125 = -3.308815781249997
+                kraken    -1x,-3x: 59.850      - 63.2206575     = -3.3706575
             1.9 quote
-                56.8575 - 60.15 = -3.2925
+                binance,kraken 1x: 56.8575     - 60.15          = -3.2925
+                binance        3x: 56.85666667 - 60.15          = -3.29333333
+                kraken         3x: 56.8175     - 60.15          = -3.3325
+                binance   -1x,-3x: 59.850      - 57.14369046875 = 2.7063095312499996
+                kraken    -1x,-3x: 59.850      - 57.1996425     = 2.6503575
             2.2 quote
-                65.835  - 60.15 = 5.685
+                binance,kraken 1x: 65.835      - 60.15          = 5.685
+                binance        3x: 65.83416667 - 60.15          = 5.68416667
+                kraken         3x: 65.795      - 60.15          = 5.645
+                binance   -1x,-3x: 59.850      - 66.1663784375  = -6.316378437499999
+                kraken    -1x,-3x: 59.850      - 66.231165      = -6.381165
         total_profit_ratio:
             equations:
-                ((close_value/open_value) - 1) * leverage
+                1x, 3x : ((close_value/open_value) - 1) * leverage
+                -1x,-3x: (1 - (close_value/open_value)) * leverage
             2.1 quote
-                (62.8425 / 60.15) - 1 = 0.04476309226932673
+                binance,kraken 1x: (62.8425 / 60.15) - 1             = 0.04476309226932673
+                binance        3x: ((62.84166667 / 60.15) - 1)*3     = 0.13424771421446402
+                kraken         3x: ((62.8025 / 60.15) - 1)*3         = 0.13229426433915248
+                binance       -1x: 1 - (63.15881578125 / 59.850)     = -0.05528514254385963
+                binance       -3x: (1 - (63.15881578125 / 59.850))*3 = -0.1658554276315789
+                kraken        -1x: 1 - (63.2206575 / 59.850)         = -0.05631842105263152
+                kraken        -3x: (1 - (63.2206575 / 59.850))*3     = -0.16895526315789455
             1.9 quote
-                (56.8575 / 60.15) - 1 = -0.05473815461346632
+                binance,kraken 1x: (56.8575 / 60.15) - 1             = -0.05473815461346632
+                binance        3x: ((56.85666667 / 60.15) - 1)*3     = -0.16425602643391513
+                kraken         3x: ((56.8175 / 60.15) - 1)*3         = -0.16620947630922667
+                binance       -1x: 1 - (57.14369046875 / 59.850)     = 0.045218204365079395
+                binance       -3x: (1 - (57.14369046875 / 59.850))*3 = 0.13565461309523819
+                kraken        -1x: 1 - (57.1996425 / 59.850)         = 0.04428333333333334
+                kraken        -3x: (1 - (57.1996425 / 59.850))*3     = 0.13285000000000002
             2.2 quote
-                (65.835 / 60.15) - 1  = 0.0945137157107232
-        fee: 0.003
+                binance,kraken 1x: (65.835 / 60.15) - 1             = 0.0945137157107232
+                binance        3x: ((65.83416667 / 60.15) - 1)*3     = 0.2834995845386534
+                kraken         3x: ((65.795 / 60.15) - 1)*3         = 0.2815461346633419
+                binance       -1x: 1 - (66.1663784375 / 59.850)     = -0.1055368159983292
+                binance       -3x: (1 - (66.1663784375 / 59.850))*3 = -0.3166104479949876
+                kraken        -1x: 1 - (66.231165 / 59.850)         = -0.106619298245614
+                kraken        -3x: (1 - (66.231165 / 59.850))*3     = -0.319857894736842
+        fee: 0.003, 1x
             close_value:
                 2.1 quote: (30.00 * 2.1) - (30.00 * 2.1 * 0.003) = 62.811
                 1.9 quote: (30.00 * 1.9) - (30.00 * 1.9 * 0.003) = 56.829
                 2.2 quote: (30.00 * 2.2) - (30.00 * 2.2 * 0.003) = 65.802
             total_profit
-                fee: 0.003
+                fee: 0.003, 1x
                     2.1 quote: 62.811 - 60.15 = 2.6610000000000014
                     1.9 quote: 56.829 - 60.15 = -3.320999999999998
                     2.2 quote: 65.802 - 60.15 = 5.652000000000008
             total_profit_ratio
-                fee: 0.003
+                fee: 0.003, 1x
                     2.1 quote: (62.811 / 60.15) - 1 = 0.04423940149625927
                     1.9 quote: (56.829 / 60.15) - 1 = -0.05521197007481293
                     2.2 quote: (65.802 / 60.15) - 1 = 0.09396508728179565
+        futures (live):
+            funding_fee: 1
+                close_value:
+                    equations:
+                        1x,3x: (amount * close_rate) - (amount * close_rate * fee) + funding_fees
+                        -1x,-3x: (amount * close_rate) + (amount * close_rate * fee) - funding_fees
+                    2.1 quote
+                        1x,3x: (30.00 * 2.1) - (30.00 * 2.1 * 0.0025) + 1   = 63.8425
+                        -1x,-3x: (30.00 * 2.1) + (30.00 * 2.1 * 0.0025) - 1   = 62.1575
+                    1.9 quote
+                        1x,3x: (30.00 * 1.9) - (30.00 * 1.9 * 0.0025) + 1   = 57.8575
+                        -1x,-3x: (30.00 * 1.9) + (30.00 * 1.9 * 0.0025) - 1   = 56.1425
+                    2.2 quote:
+                        1x,3x: (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) + 1 = 66.835
+                        -1x,-3x: (30.00 * 2.20) + (30.00 * 2.20 * 0.0025) - 1 = 65.165
+                total_profit:
+                    2.1 quote
+                        1x,3x:   63.8425     - 60.15          = 3.6925
+                        -1x,-3x: 59.850      - 62.1575        = -2.3074999999999974
+                    1.9 quote
+                        1x,3x:   57.8575     - 60.15          = -2.2925
+                        -1x,-3x: 59.850      - 56.1425        = 3.707500000000003
+                    2.2 quote:
+                        1x,3x:   66.835      - 60.15          = 6.685
+                        -1x,-3x: 59.850      - 65.165         = -5.315000000000005
+                total_profit_ratio:
+                    2.1 quote
+                        1x: (63.8425 / 60.15) - 1             = 0.06138819617622615
+                        3x: ((63.8425 / 60.15) - 1)*3         = 0.18416458852867845
+                        -1x: 1 - (62.1575 / 59.850)           = -0.038554720133667564
+                        -3x: (1 - (62.1575 / 59.850))*3       = -0.11566416040100269
+                    1.9 quote
+                        1x: (57.8575 / 60.15) - 1             = -0.0381130507065669
+                        3x: ((57.8575 / 60.15) - 1)*3         = -0.1143391521197007
+                        -1x: 1 - (56.1425 / 59.850)           = 0.06194653299916464
+                        -3x: (1 - (56.1425 / 59.850))*3       = 0.18583959899749392
+                    2.2 quote
+                        1x: (66.835 / 60.15) - 1             = 0.11113881961762262
+                        3x: ((66.835 / 60.15) - 1)*3         = 0.33341645885286786
+                        -1x: 1 - (65.165 / 59.850)           = -0.08880534670008355
+                        -3x: (1 - (65.165 / 59.850))*3       = -0.26641604010025066
+            funding_fee: -1
+                close_value:
+                    equations:
+                        (amount * close_rate) - (amount * close_rate * fee) + funding_fees
+                        (amount * close_rate) - (amount * close_rate * fee) - funding_fees
+                    2.1 quote
+                        1x,3x:  (30.00 * 2.1) - (30.00 * 2.1 * 0.0025) + (-1)   = 61.8425
+                        -1x,-3x: (30.00 * 2.1) + (30.00 * 2.1 * 0.0025) - (-1)   = 64.1575
+                    1.9 quote
+                        1x,3x:  (30.00 * 1.9) - (30.00 * 1.9 * 0.0025) + (-1)   = 55.8575
+                        -1x,-3x: (30.00 * 1.9) + (30.00 * 1.9 * 0.0025) - (-1)   = 58.1425
+                    2.2 quote:
+                        1x,3x:  (30.00 * 2.20) - (30.00 * 2.20 * 0.0025) + (-1) = 64.835
+                        -1x,-3x: (30.00 * 2.20) + (30.00 * 2.20 * 0.0025) - (-1) = 67.165
+                total_profit:
+                    2.1 quote
+                        1x,3x:   61.8425     - 60.15          = 1.6925000000000026
+                        -1x,-3x: 59.850      - 64.1575        = -4.307499999999997
+                    1.9 quote
+                        1x,3x:   55.8575     - 60.15          = -4.292499999999997
+                        -1x,-3x: 59.850      - 58.1425        = 1.7075000000000031
+                    2.2 quote:
+                        1x,3x:   64.835      - 60.15          = 4.684999999999995
+                        -1x,-3x: 59.850      - 67.165         = -7.315000000000005
+                total_profit_ratio:
+                    2.1 quote
+                        1x: (61.8425 / 60.15) - 1             = 0.028137988362427313
+                        3x: ((61.8425 / 60.15) - 1)*3         = 0.08441396508728194
+                        -1x: 1 - (64.1575 / 59.850)           = -0.07197159565580624
+                        -3x: (1 - (64.1575 / 59.850))*3       = -0.21591478696741873
+                    1.9 quote
+                        1x: (55.8575 / 60.15) - 1             = -0.07136325852036574
+                        3x: ((55.8575 / 60.15) - 1)*3         = -0.2140897755610972
+                        -1x: 1 - (58.1425 / 59.850)           = 0.02852965747702596
+                        -3x: (1 - (58.1425 / 59.850))*3       = 0.08558897243107788
+                    2.2 quote
+                        1x: (64.835 / 60.15) - 1              = 0.07788861180382378
+                        3x: ((64.835 / 60.15) - 1)*3          = 0.23366583541147135
+                        -1x: 1 - (67.165 / 59.850)            = -0.12222222222222223
+                        -3x: (1 - (67.165 / 59.850))*3        = -0.3666666666666667
     """
     trade = Trade(
         pair='ADA/USDT',
         stake_amount=60.0,
         amount=30.0,
         open_rate=2.0,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        exchange='binance',
+        open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
+        interest_rate=0.0005,
+        exchange=exchange,
+        is_short=is_short,
+        leverage=lev,
+        fee_open=0.0025,
+        fee_close=fee_close,
+        trading_mode=trading_mode,
+        funding_fees=funding_fees
     )
     trade.open_order_id = 'something'
-    trade.update(limit_buy_order_usdt)  # Buy @ 2.0
 
-    # Custom closing rate and regular fee rate
-    # Higher than open rate - 2.1 quote
-    assert trade.calc_profit(rate=2.1) == 2.6925
-    # Lower than open rate - 1.9 quote
-    assert trade.calc_profit(rate=1.9) == round(-3.292499999999997, 8)
-
-    # fee 0.003
-    # Higher than open rate - 2.1 quote
-    assert trade.calc_profit(rate=2.1, fee=0.003) == 2.661
-    # Lower than open rate - 1.9 quote
-    assert trade.calc_profit(rate=1.9, fee=0.003) == round(-3.320999999999998, 8)
-
-    # Test when we apply a Sell order. Sell higher than open rate @ 2.2
-    trade.update(limit_sell_order_usdt)
-    assert trade.calc_profit() == round(5.684999999999995, 8)
-
-    # Test with a custom fee rate on the close trade
-    assert trade.calc_profit(fee=0.003) == round(5.652000000000008, 8)
-
-
-@pytest.mark.usefixtures("init_persistence")
-def test_calc_profit_ratio(limit_buy_order_usdt, limit_sell_order_usdt, fee):
-    trade = Trade(
-        pair='ADA/USDT',
-        stake_amount=60.0,
-        amount=30.0,
-        open_rate=2.0,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        exchange='binance'
-    )
-    trade.open_order_id = 'something'
-    trade.update(limit_buy_order_usdt)  # Buy @ 2.0
-
-    # Higher than open rate - 2.1 quote
-    assert trade.calc_profit_ratio(rate=2.1) == round(0.04476309226932673, 8)
-    # Lower than open rate - 1.9 quote
-    assert trade.calc_profit_ratio(rate=1.9) == round(-0.05473815461346632, 8)
-
-    # fee 0.003
-    # Higher than open rate - 2.1 quote
-    assert trade.calc_profit_ratio(rate=2.1, fee=0.003) == round(0.04423940149625927, 8)
-    # Lower than open rate - 1.9 quote
-    assert trade.calc_profit_ratio(rate=1.9, fee=0.003) == round(-0.05521197007481293, 8)
-
-    # Test when we apply a Sell order. Sell higher than open rate @ 2.2
-    trade.update(limit_sell_order_usdt)
-    assert trade.calc_profit_ratio() == round(0.0945137157107232, 8)
-
-    # Test with a custom fee rate on the close trade
-    assert trade.calc_profit_ratio(fee=0.003) == round(0.09396508728179565, 8)
-
-    trade.open_trade_value = 0.0
-    assert trade.calc_profit_ratio(fee=0.003) == 0.0
+    assert pytest.approx(trade.calc_profit(rate=close_rate)) == round(profit, 8)
+    assert pytest.approx(trade.calc_profit_ratio(rate=close_rate)) == round(profit_ratio, 8)
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -547,6 +1209,27 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
                                 PRIMARY KEY (id),
                                 CHECK (is_open IN (0, 1))
                                 );"""
+    create_table_order = """CREATE TABLE orders (
+                                id INTEGER NOT NULL,
+                                ft_trade_id INTEGER,
+                                ft_order_side VARCHAR(25) NOT NULL,
+                                ft_pair VARCHAR(25) NOT NULL,
+                                ft_is_open BOOLEAN NOT NULL,
+                                order_id VARCHAR(255) NOT NULL,
+                                status VARCHAR(255),
+                                symbol VARCHAR(25),
+                                order_type VARCHAR(50),
+                                side VARCHAR(25),
+                                price FLOAT,
+                                amount FLOAT,
+                                filled FLOAT,
+                                remaining FLOAT,
+                                cost FLOAT,
+                                order_date DATETIME,
+                                order_filled_date DATETIME,
+                                order_update_date DATETIME,
+                                PRIMARY KEY (id)
+                            );"""
     insert_table_old = """INSERT INTO trades (exchange, pair, is_open, fee,
                           open_rate, stake_amount, amount, open_date,
                           stop_loss, initial_stop_loss, max_rate, ticker_interval,
@@ -560,15 +1243,66 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
                                      stake=default_conf.get("stake_amount"),
                                      amount=amount
                                      )
+    insert_orders = f"""
+        insert into orders (
+            ft_trade_id,
+            ft_order_side,
+            ft_pair,
+            ft_is_open,
+            order_id,
+            status,
+            symbol,
+            order_type,
+            side,
+            price,
+            amount,
+            filled,
+            remaining,
+            cost)
+        values (
+            1,
+            'buy',
+            'ETC/BTC',
+            0,
+            'buy_order',
+            'closed',
+            'ETC/BTC',
+            'limit',
+            'buy',
+            0.00258580,
+            {amount},
+            {amount},
+            0,
+            {amount * 0.00258580}
+        ),
+        (
+            1,
+            'stoploss',
+            'ETC/BTC',
+            0,
+            'stop_order_id222',
+            'closed',
+            'ETC/BTC',
+            'limit',
+            'sell',
+            0.00258580,
+            {amount},
+            {amount},
+            0,
+            {amount * 0.00258580}
+        )
+    """
     engine = create_engine('sqlite://')
     mocker.patch('freqtrade.persistence.models.create_engine', lambda *args, **kwargs: engine)
 
     # Create table using the old format
     with engine.begin() as connection:
         connection.execute(text(create_table_old))
+        connection.execute(text(create_table_order))
         connection.execute(text("create index ix_trades_is_open on trades(is_open)"))
         connection.execute(text("create index ix_trades_pair on trades(pair)"))
         connection.execute(text(insert_table_old))
+        connection.execute(text(insert_orders))
 
         # fake previous backup
         connection.execute(text("create table trades_bak as select * from trades"))
@@ -593,78 +1327,19 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
     assert trade.min_rate is None
     assert trade.stop_loss == 0.0
     assert trade.initial_stop_loss == 0.0
-    assert trade.sell_reason is None
+    assert trade.exit_reason is None
     assert trade.strategy is None
     assert trade.timeframe == '5m'
     assert trade.stoploss_order_id == 'stop_order_id222'
     assert trade.stoploss_last_update is None
     assert log_has("trying trades_bak1", caplog)
     assert log_has("trying trades_bak2", caplog)
-    assert log_has("Running database migration for trades - backup: trades_bak2", caplog)
+    assert log_has("Running database migration for trades - backup: trades_bak2, orders_bak0",
+                   caplog)
     assert trade.open_trade_value == trade._calc_open_trade_value()
     assert trade.close_profit_abs is None
 
-    assert log_has("Moving open orders to Orders table.", caplog)
-    orders = Order.query.all()
-    assert len(orders) == 2
-    assert orders[0].order_id == 'buy_order'
-    assert orders[0].ft_order_side == 'buy'
-
-    assert orders[1].order_id == 'stop_order_id222'
-    assert orders[1].ft_order_side == 'stoploss'
-
-    caplog.clear()
-    # Drop latest column
-    with engine.begin() as connection:
-        connection.execute(text("alter table orders rename to orders_bak"))
-    inspector = inspect(engine)
-
-    with engine.begin() as connection:
-        for index in inspector.get_indexes('orders_bak'):
-            connection.execute(text(f"drop index {index['name']}"))
-        # Recreate table
-        connection.execute(text("""
-            CREATE TABLE orders (
-                id INTEGER NOT NULL,
-                ft_trade_id INTEGER,
-                ft_order_side VARCHAR NOT NULL,
-                ft_pair VARCHAR NOT NULL,
-                ft_is_open BOOLEAN NOT NULL,
-                order_id VARCHAR NOT NULL,
-                status VARCHAR,
-                symbol VARCHAR,
-                order_type VARCHAR,
-                side VARCHAR,
-                price FLOAT,
-                amount FLOAT,
-                filled FLOAT,
-                remaining FLOAT,
-                cost FLOAT,
-                order_date DATETIME,
-                order_filled_date DATETIME,
-                order_update_date DATETIME,
-                PRIMARY KEY (id),
-                CONSTRAINT _order_pair_order_id UNIQUE (ft_pair, order_id),
-                FOREIGN KEY(ft_trade_id) REFERENCES trades (id)
-            )
-            """))
-
-        connection.execute(text("""
-        insert into orders ( id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status,
-            symbol, order_type, side, price, amount, filled, remaining, cost, order_date,
-            order_filled_date, order_update_date)
-            select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status,
-            symbol, order_type, side, price, amount, filled, remaining, cost, order_date,
-            order_filled_date, order_update_date
-            from orders_bak
-        """))
-
-    # Run init to test migration
-    init_db(default_conf['db_url'], default_conf['dry_run'])
-
-    assert log_has("trying orders_bak1", caplog)
-
-    orders = Order.query.all()
+    orders = trade.orders
     assert len(orders) == 2
     assert orders[0].order_id == 'buy_order'
     assert orders[0].ft_order_side == 'buy'
@@ -673,7 +1348,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
     assert orders[1].ft_order_side == 'stoploss'
 
 
-def test_migrate_mid_state(mocker, default_conf, fee, caplog):
+def test_migrate_too_old(mocker, default_conf, fee, caplog):
     """
     Test Database migration (starting with new pairformat)
     """
@@ -697,6 +1372,7 @@ def test_migrate_mid_state(mocker, default_conf, fee, caplog):
                                 PRIMARY KEY (id),
                                 CHECK (is_open IN (0, 1))
                                 );"""
+
     insert_table_old = """INSERT INTO trades (exchange, pair, is_open, fee_open, fee_close,
                           open_rate, stake_amount, amount, open_date)
                           VALUES ('binance', 'ETC/BTC', 1, {fee}, {fee},
@@ -715,25 +1391,40 @@ def test_migrate_mid_state(mocker, default_conf, fee, caplog):
         connection.execute(text(insert_table_old))
 
     # Run init to test migration
-    init_db(default_conf['db_url'], default_conf['dry_run'])
+    with pytest.raises(OperationalException, match=r'Your database seems to be very old'):
+        init_db(default_conf['db_url'], default_conf['dry_run'])
 
-    assert len(Trade.query.filter(Trade.id == 1).all()) == 1
-    trade = Trade.query.filter(Trade.id == 1).first()
-    assert trade.fee_open == fee.return_value
-    assert trade.fee_close == fee.return_value
-    assert trade.open_rate_requested is None
-    assert trade.close_rate_requested is None
-    assert trade.is_open == 1
-    assert trade.amount == amount
-    assert trade.stake_amount == default_conf.get("stake_amount")
-    assert trade.pair == "ETC/BTC"
-    assert trade.exchange == "binance"
-    assert trade.max_rate == 0.0
-    assert trade.stop_loss == 0.0
-    assert trade.initial_stop_loss == 0.0
-    assert trade.open_trade_value == trade._calc_open_trade_value()
-    assert log_has("trying trades_bak0", caplog)
-    assert log_has("Running database migration for trades - backup: trades_bak0", caplog)
+
+def test_migrate_get_last_sequence_ids():
+    engine = MagicMock()
+    engine.begin = MagicMock()
+    engine.name = 'postgresql'
+    get_last_sequence_ids(engine, 'trades_bak', 'orders_bak')
+
+    assert engine.begin.call_count == 2
+    engine.reset_mock()
+    engine.begin.reset_mock()
+
+    engine.name = 'somethingelse'
+    get_last_sequence_ids(engine, 'trades_bak', 'orders_bak')
+
+    assert engine.begin.call_count == 0
+
+
+def test_migrate_set_sequence_ids():
+    engine = MagicMock()
+    engine.begin = MagicMock()
+    engine.name = 'postgresql'
+    set_sequence_ids(engine, 22, 55)
+
+    assert engine.begin.call_count == 1
+    engine.reset_mock()
+    engine.begin.reset_mock()
+
+    engine.name = 'somethingelse'
+    set_sequence_ids(engine, 22, 55)
+
+    assert engine.begin.call_count == 0
 
 
 def test_adjust_stop_loss(fee):
@@ -788,6 +1479,59 @@ def test_adjust_stop_loss(fee):
     assert trade.stop_loss_pct == -0.1
 
 
+def test_adjust_stop_loss_short(fee):
+    trade = Trade(
+        pair='ADA/USDT',
+        stake_amount=0.001,
+        amount=5,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        exchange='binance',
+        open_rate=1,
+        max_rate=1,
+        is_short=True,
+    )
+    trade.adjust_stop_loss(trade.open_rate, 0.05, True)
+    assert trade.stop_loss == 1.05
+    assert trade.stop_loss_pct == -0.05
+    assert trade.initial_stop_loss == 1.05
+    assert trade.initial_stop_loss_pct == -0.05
+    # Get percent of profit with a lower rate
+    trade.adjust_stop_loss(1.04, 0.05)
+    assert trade.stop_loss == 1.05
+    assert trade.stop_loss_pct == -0.05
+    assert trade.initial_stop_loss == 1.05
+    assert trade.initial_stop_loss_pct == -0.05
+    # Get percent of profit with a custom rate (Higher than open rate)
+    trade.adjust_stop_loss(0.7, 0.1)
+    # If the price goes down to 0.7, with a trailing stop of 0.1,
+    # the new stoploss at 0.1 above 0.7 would be 0.7*0.1 higher
+    assert round(trade.stop_loss, 8) == 0.77
+    assert trade.stop_loss_pct == -0.1
+    assert trade.initial_stop_loss == 1.05
+    assert trade.initial_stop_loss_pct == -0.05
+    # current rate lower again ... should not change
+    trade.adjust_stop_loss(0.8, -0.1)
+    assert round(trade.stop_loss, 8) == 0.77
+    assert trade.initial_stop_loss == 1.05
+    assert trade.initial_stop_loss_pct == -0.05
+    # current rate higher... should raise stoploss
+    trade.adjust_stop_loss(0.6, -0.1)
+    assert round(trade.stop_loss, 8) == 0.66
+    assert trade.initial_stop_loss == 1.05
+    assert trade.initial_stop_loss_pct == -0.05
+    #  Initial is true but stop_loss set - so doesn't do anything
+    trade.adjust_stop_loss(0.3, -0.1, True)
+    assert round(trade.stop_loss, 8) == 0.66
+    assert trade.initial_stop_loss == 1.05
+    assert trade.initial_stop_loss_pct == -0.05
+    assert trade.stop_loss_pct == -0.1
+    trade.set_isolated_liq(0.63)
+    trade.adjust_stop_loss(0.59, -0.1)
+    assert trade.stop_loss == 0.63
+    assert trade.liquidation_price == 0.63
+
+
 def test_adjust_min_max_rates(fee):
     trade = Trade(
         pair='ADA/USDT',
@@ -826,22 +1570,35 @@ def test_adjust_min_max_rates(fee):
 
 @pytest.mark.usefixtures("init_persistence")
 @pytest.mark.parametrize('use_db', [True, False])
-def test_get_open(fee, use_db):
+@pytest.mark.parametrize('is_short', [True, False])
+def test_get_open(fee, is_short, use_db):
     Trade.use_db = use_db
     Trade.reset_trades()
 
-    create_mock_trades(fee, use_db)
+    create_mock_trades(fee, is_short, use_db)
     assert len(Trade.get_open_trades()) == 4
 
     Trade.use_db = True
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_to_json(default_conf, fee):
+@pytest.mark.parametrize('use_db', [True, False])
+def test_get_open_lev(fee, use_db):
+    Trade.use_db = use_db
+    Trade.reset_trades()
+
+    create_mock_trades_with_leverage(fee, use_db)
+    assert len(Trade.get_open_trades()) == 5
+
+    Trade.use_db = True
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_to_json(fee):
 
     # Simulate dry_run entries
     trade = Trade(
-        pair='ETH/BTC',
+        pair='ADA/USDT',
         stake_amount=0.001,
         amount=123.0,
         amount_requested=123.0,
@@ -850,14 +1607,16 @@ def test_to_json(default_conf, fee):
         open_date=arrow.utcnow().shift(hours=-2).datetime,
         open_rate=0.123,
         exchange='binance',
-        buy_tag=None,
+        enter_tag=None,
         open_order_id='dry_run_buy_12345'
     )
     result = trade.to_json()
     assert isinstance(result, dict)
 
     assert result == {'trade_id': None,
-                      'pair': 'ETH/BTC',
+                      'pair': 'ADA/USDT',
+                      'base_currency': 'ADA',
+                      'quote_currency': 'USDT',
                       'is_open': None,
                       'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"),
                       'open_timestamp': int(trade.open_date.timestamp() * 1000),
@@ -887,7 +1646,8 @@ def test_to_json(default_conf, fee):
                       'profit_pct': None,
                       'profit_abs': None,
                       'sell_reason': None,
-                      'sell_order_status': None,
+                      'exit_reason': None,
+                      'exit_order_status': None,
                       'stop_loss_abs': None,
                       'stop_loss_ratio': None,
                       'stop_loss_pct': None,
@@ -901,8 +1661,16 @@ def test_to_json(default_conf, fee):
                       'max_rate': None,
                       'strategy': None,
                       'buy_tag': None,
+                      'enter_tag': None,
                       'timeframe': None,
                       'exchange': 'binance',
+                      'leverage': None,
+                      'interest_rate': None,
+                      'liquidation_price': None,
+                      'is_short': None,
+                      'trading_mode': None,
+                      'funding_fees': None,
+                      'orders': [],
                       }
 
     # Simulate dry_run entries
@@ -917,7 +1685,7 @@ def test_to_json(default_conf, fee):
         close_date=arrow.utcnow().shift(hours=-1).datetime,
         open_rate=0.123,
         close_rate=0.125,
-        buy_tag='buys_signal_001',
+        enter_tag='buys_signal_001',
         exchange='binance',
     )
     result = trade.to_json()
@@ -925,6 +1693,8 @@ def test_to_json(default_conf, fee):
 
     assert result == {'trade_id': None,
                       'pair': 'XRP/BTC',
+                      'base_currency': 'XRP',
+                      'quote_currency': 'BTC',
                       'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"),
                       'open_timestamp': int(trade.open_date.timestamp() * 1000),
                       'close_date': trade.close_date.strftime("%Y-%m-%d %H:%M:%S"),
@@ -965,11 +1735,20 @@ def test_to_json(default_conf, fee):
                       'open_rate_requested': None,
                       'open_trade_value': 12.33075,
                       'sell_reason': None,
-                      'sell_order_status': None,
+                      'exit_reason': None,
+                      'exit_order_status': None,
                       'strategy': None,
                       'buy_tag': 'buys_signal_001',
+                      'enter_tag': 'buys_signal_001',
                       'timeframe': None,
                       'exchange': 'binance',
+                      'leverage': None,
+                      'interest_rate': None,
+                      'liquidation_price': None,
+                      'is_short': None,
+                      'trading_mode': None,
+                      'funding_fees': None,
+                      'orders': [],
                       }
 
 
@@ -1033,6 +1812,126 @@ def test_stoploss_reinitialization(default_conf, fee):
     assert trade_adj.initial_stop_loss_pct == -0.04
 
 
+def test_stoploss_reinitialization_leverage(default_conf, fee):
+    init_db(default_conf['db_url'])
+    trade = Trade(
+        pair='ADA/USDT',
+        stake_amount=30.0,
+        fee_open=fee.return_value,
+        open_date=arrow.utcnow().shift(hours=-2).datetime,
+        amount=30.0,
+        fee_close=fee.return_value,
+        exchange='binance',
+        open_rate=1,
+        max_rate=1,
+        leverage=5.0,
+    )
+
+    trade.adjust_stop_loss(trade.open_rate, 0.1, True)
+    assert trade.stop_loss == 0.98
+    assert trade.stop_loss_pct == -0.1
+    assert trade.initial_stop_loss == 0.98
+    assert trade.initial_stop_loss_pct == -0.1
+    Trade.query.session.add(trade)
+
+    # Lower stoploss
+    Trade.stoploss_reinitialization(0.15)
+
+    trades = Trade.get_open_trades()
+    assert len(trades) == 1
+    trade_adj = trades[0]
+    assert trade_adj.stop_loss == 0.97
+    assert trade_adj.stop_loss_pct == -0.15
+    assert trade_adj.initial_stop_loss == 0.97
+    assert trade_adj.initial_stop_loss_pct == -0.15
+
+    # Raise stoploss
+    Trade.stoploss_reinitialization(0.05)
+
+    trades = Trade.get_open_trades()
+    assert len(trades) == 1
+    trade_adj = trades[0]
+    assert trade_adj.stop_loss == 0.99
+    assert trade_adj.stop_loss_pct == -0.05
+    assert trade_adj.initial_stop_loss == 0.99
+    assert trade_adj.initial_stop_loss_pct == -0.05
+
+    # Trailing stoploss (move stoplos up a bit)
+    trade.adjust_stop_loss(1.02, 0.05)
+    assert trade_adj.stop_loss == 1.0098
+    assert trade_adj.initial_stop_loss == 0.99
+
+    Trade.stoploss_reinitialization(0.05)
+
+    trades = Trade.get_open_trades()
+    assert len(trades) == 1
+    trade_adj = trades[0]
+    # Stoploss should not change in this case.
+    assert trade_adj.stop_loss == 1.0098
+    assert trade_adj.stop_loss_pct == -0.05
+    assert trade_adj.initial_stop_loss == 0.99
+    assert trade_adj.initial_stop_loss_pct == -0.05
+
+
+def test_stoploss_reinitialization_short(default_conf, fee):
+    init_db(default_conf['db_url'])
+    trade = Trade(
+        pair='ADA/USDT',
+        stake_amount=0.001,
+        fee_open=fee.return_value,
+        open_date=arrow.utcnow().shift(hours=-2).datetime,
+        amount=10,
+        fee_close=fee.return_value,
+        exchange='binance',
+        open_rate=1,
+        max_rate=1,
+        is_short=True,
+        leverage=5.0,
+    )
+    trade.adjust_stop_loss(trade.open_rate, -0.1, True)
+    assert trade.stop_loss == 1.02
+    assert trade.stop_loss_pct == -0.1
+    assert trade.initial_stop_loss == 1.02
+    assert trade.initial_stop_loss_pct == -0.1
+    Trade.query.session.add(trade)
+    # Lower stoploss
+    Trade.stoploss_reinitialization(-0.15)
+    trades = Trade.get_open_trades()
+    assert len(trades) == 1
+    trade_adj = trades[0]
+    assert trade_adj.stop_loss == 1.03
+    assert trade_adj.stop_loss_pct == -0.15
+    assert trade_adj.initial_stop_loss == 1.03
+    assert trade_adj.initial_stop_loss_pct == -0.15
+    # Raise stoploss
+    Trade.stoploss_reinitialization(-0.05)
+    trades = Trade.get_open_trades()
+    assert len(trades) == 1
+    trade_adj = trades[0]
+    assert trade_adj.stop_loss == 1.01
+    assert trade_adj.stop_loss_pct == -0.05
+    assert trade_adj.initial_stop_loss == 1.01
+    assert trade_adj.initial_stop_loss_pct == -0.05
+    # Trailing stoploss
+    trade.adjust_stop_loss(0.98, -0.05)
+    assert trade_adj.stop_loss == 0.9898
+    assert trade_adj.initial_stop_loss == 1.01
+    Trade.stoploss_reinitialization(-0.05)
+    trades = Trade.get_open_trades()
+    assert len(trades) == 1
+    trade_adj = trades[0]
+    # Stoploss should not change in this case.
+    assert trade_adj.stop_loss == 0.9898
+    assert trade_adj.stop_loss_pct == -0.05
+    assert trade_adj.initial_stop_loss == 1.01
+    assert trade_adj.initial_stop_loss_pct == -0.05
+    # Stoploss can't go above liquidation price
+    trade_adj.set_isolated_liq(0.985)
+    trade.adjust_stop_loss(0.9799, -0.05)
+    assert trade_adj.stop_loss == 0.985
+    assert trade_adj.stop_loss == 0.985
+
+
 def test_update_fee(fee):
     trade = Trade(
         pair='ADA/USDT',
@@ -1103,14 +2002,15 @@ def test_fee_updated(fee):
 
 
 @pytest.mark.usefixtures("init_persistence")
+@pytest.mark.parametrize('is_short', [True, False])
 @pytest.mark.parametrize('use_db', [True, False])
-def test_total_open_trades_stakes(fee, use_db):
+def test_total_open_trades_stakes(fee, is_short, use_db):
 
     Trade.use_db = use_db
     Trade.reset_trades()
     res = Trade.total_open_trades_stakes()
     assert res == 0
-    create_mock_trades(fee, use_db)
+    create_mock_trades(fee, is_short, use_db)
     res = Trade.total_open_trades_stakes()
     assert res == 0.004
 
@@ -1118,26 +2018,32 @@ def test_total_open_trades_stakes(fee, use_db):
 
 
 @pytest.mark.usefixtures("init_persistence")
+@pytest.mark.parametrize('is_short,result', [
+    (True, -0.006739127),
+    (False, 0.000739127),
+    (None, -0.005429127),
+])
 @pytest.mark.parametrize('use_db', [True, False])
-def test_get_total_closed_profit(fee, use_db):
+def test_get_total_closed_profit(fee, use_db, is_short, result):
 
     Trade.use_db = use_db
     Trade.reset_trades()
     res = Trade.get_total_closed_profit()
     assert res == 0
-    create_mock_trades(fee, use_db)
+    create_mock_trades(fee, is_short, use_db)
     res = Trade.get_total_closed_profit()
-    assert res == 0.000739127
+    assert pytest.approx(res) == result
 
     Trade.use_db = True
 
 
 @pytest.mark.usefixtures("init_persistence")
+@pytest.mark.parametrize('is_short', [True, False])
 @pytest.mark.parametrize('use_db', [True, False])
-def test_get_trades_proxy(fee, use_db):
+def test_get_trades_proxy(fee, use_db, is_short):
     Trade.use_db = use_db
     Trade.reset_trades()
-    create_mock_trades(fee, use_db)
+    create_mock_trades(fee, is_short, use_db)
     trades = Trade.get_trades_proxy()
     assert len(trades) == 6
 
@@ -1166,9 +2072,10 @@ def test_get_trades_backtest():
 
 
 @pytest.mark.usefixtures("init_persistence")
+# @pytest.mark.parametrize('is_short', [True, False])
 def test_get_overall_performance(fee):
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, False)
     res = Trade.get_overall_performance()
 
     assert len(res) == 2
@@ -1178,31 +2085,58 @@ def test_get_overall_performance(fee):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_get_best_pair(fee):
+@pytest.mark.parametrize('is_short,pair,profit', [
+    (True, 'ETC/BTC', -0.005),
+    (False, 'XRP/BTC', 0.01),
+    (None, 'XRP/BTC', 0.01),
+])
+def test_get_best_pair(fee, is_short, pair, profit):
 
     res = Trade.get_best_pair()
     assert res is None
 
-    create_mock_trades(fee)
+    create_mock_trades(fee, is_short)
     res = Trade.get_best_pair()
     assert len(res) == 2
-    assert res[0] == 'XRP/BTC'
-    assert res[1] == 0.01
+    assert res[0] == pair
+    assert res[1] == profit
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_get_best_pair_lev(fee):
+
+    res = Trade.get_best_pair()
+    assert res is None
+
+    create_mock_trades_with_leverage(fee)
+    res = Trade.get_best_pair()
+    assert len(res) == 2
+    assert res[0] == 'DOGE/BTC'
+    assert res[1] == 0.1713156134055116
+
+
+@pytest.mark.usefixtures("init_persistence")
+@pytest.mark.parametrize('is_short', [True, False])
+def test_get_exit_order_count(fee, is_short):
+
+    create_mock_trades(fee, is_short=is_short)
+    trade = Trade.get_trades([Trade.pair == 'ETC/BTC']).first()
+    assert trade.get_exit_order_count() == 1
 
 
 @pytest.mark.usefixtures("init_persistence")
 def test_update_order_from_ccxt(caplog):
     # Most basic order return (only has orderid)
-    o = Order.parse_from_ccxt_object({'id': '1234'}, 'ETH/BTC', 'buy')
+    o = Order.parse_from_ccxt_object({'id': '1234'}, 'ADA/USDT', 'buy')
     assert isinstance(o, Order)
-    assert o.ft_pair == 'ETH/BTC'
+    assert o.ft_pair == 'ADA/USDT'
     assert o.ft_order_side == 'buy'
     assert o.order_id == '1234'
     assert o.ft_is_open
     ccxt_order = {
         'id': '1234',
         'side': 'buy',
-        'symbol': 'ETH/BTC',
+        'symbol': 'ADA/USDT',
         'type': 'limit',
         'price': 1234.5,
         'amount':  20.0,
@@ -1211,9 +2145,9 @@ def test_update_order_from_ccxt(caplog):
         'status': 'open',
         'timestamp': 1599394315123
     }
-    o = Order.parse_from_ccxt_object(ccxt_order, 'ETH/BTC', 'buy')
+    o = Order.parse_from_ccxt_object(ccxt_order, 'ADA/USDT', 'buy')
     assert isinstance(o, Order)
-    assert o.ft_pair == 'ETH/BTC'
+    assert o.ft_pair == 'ADA/USDT'
     assert o.ft_order_side == 'buy'
     assert o.order_id == '1234'
     assert o.order_type == 'limit'
@@ -1252,48 +2186,52 @@ def test_update_order_from_ccxt(caplog):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_select_order(fee):
-    create_mock_trades(fee)
+@pytest.mark.parametrize('is_short', [True, False])
+def test_select_order(fee, is_short):
+    create_mock_trades(fee, is_short)
 
     trades = Trade.get_trades().all()
 
     # Open buy order, no sell order
-    order = trades[0].select_order('buy', True)
+    order = trades[0].select_order(trades[0].entry_side, True)
     assert order is None
-    order = trades[0].select_order('buy', False)
+    order = trades[0].select_order(trades[0].entry_side, False)
     assert order is not None
-    order = trades[0].select_order('sell', None)
+    order = trades[0].select_order(trades[0].exit_side, None)
     assert order is None
 
     # closed buy order, and open sell order
-    order = trades[1].select_order('buy', True)
+    order = trades[1].select_order(trades[1].entry_side, True)
     assert order is None
-    order = trades[1].select_order('buy', False)
+    order = trades[1].select_order(trades[1].entry_side, False)
     assert order is not None
-    order = trades[1].select_order('buy', None)
+    order = trades[1].select_order(trades[1].entry_side, None)
     assert order is not None
-    order = trades[1].select_order('sell', True)
+    order = trades[1].select_order(trades[1].exit_side, True)
     assert order is None
-    order = trades[1].select_order('sell', False)
+    order = trades[1].select_order(trades[1].exit_side, False)
     assert order is not None
 
     # Has open buy order
-    order = trades[3].select_order('buy', True)
+    order = trades[3].select_order(trades[3].entry_side, True)
     assert order is not None
-    order = trades[3].select_order('buy', False)
+    order = trades[3].select_order(trades[3].entry_side, False)
     assert order is None
 
     # Open sell order
-    order = trades[4].select_order('buy', True)
+    order = trades[4].select_order(trades[4].entry_side, True)
     assert order is None
-    order = trades[4].select_order('buy', False)
+    order = trades[4].select_order(trades[4].entry_side, False)
     assert order is not None
 
-    order = trades[4].select_order('sell', True)
+    trades[4].orders[1].ft_order_side = trades[4].exit_side
+    order = trades[4].select_order(trades[4].exit_side, True)
+    assert order is not None
+
+    trades[4].orders[1].ft_order_side = 'stoploss'
+    order = trades[4].select_order('stoploss', None)
     assert order is not None
     assert order.ft_order_side == 'stoploss'
-    order = trades[4].select_order('sell', False)
-    assert order is None
 
 
 def test_Trade_object_idem():
@@ -1313,10 +2251,14 @@ def test_Trade_object_idem():
         'get_overall_performance',
         'get_total_closed_profit',
         'total_open_trades_stakes',
-        'get_sold_trades_without_assigned_fees',
+        'get_closed_trades_without_assigned_fees',
         'get_open_trades_without_assigned_fees',
         'get_open_order_trades',
         'get_trades',
+        'get_exit_reason_performance',
+        'get_enter_tag_performance',
+        'get_mix_tag_performance',
+
     )
 
     # Parent (LocalTrade) should have the same attributes
@@ -1331,3 +2273,401 @@ def test_Trade_object_idem():
                 and item not in ('trades', 'trades_open', 'total_profit')
                 and type(getattr(LocalTrade, item)) not in (property, FunctionType)):
             assert item in trade
+
+
+def test_recalc_trade_from_orders(fee):
+
+    o1_amount = 100
+    o1_rate = 1
+    o1_cost = o1_amount * o1_rate
+    o1_fee_cost = o1_cost * fee.return_value
+    o1_trade_val = o1_cost + o1_fee_cost
+
+    trade = Trade(
+        pair='ADA/USDT',
+        stake_amount=o1_cost,
+        open_date=arrow.utcnow().shift(hours=-2).datetime,
+        amount=o1_amount,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        exchange='binance',
+        open_rate=o1_rate,
+        max_rate=o1_rate,
+        leverage=1,
+    )
+
+    assert fee.return_value == 0.0025
+    assert trade._calc_open_trade_value() == o1_trade_val
+    assert trade.amount == o1_amount
+    assert trade.stake_amount == o1_cost
+    assert trade.open_rate == o1_rate
+    assert trade.open_trade_value == o1_trade_val
+
+    # Calling without orders should not throw exceptions and change nothing
+    trade.recalc_trade_from_orders()
+    assert trade.amount == o1_amount
+    assert trade.stake_amount == o1_cost
+    assert trade.open_rate == o1_rate
+    assert trade.open_trade_value == o1_trade_val
+
+    trade.update_fee(o1_fee_cost, 'BNB', fee.return_value, 'buy')
+
+    assert len(trade.orders) == 0
+
+    # Check with 1 order
+    order1 = Order(
+        ft_order_side='buy',
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side="buy",
+        price=o1_rate,
+        average=o1_rate,
+        filled=o1_amount,
+        remaining=0,
+        cost=o1_amount,
+        order_date=trade.open_date,
+        order_filled_date=trade.open_date,
+    )
+    trade.orders.append(order1)
+    trade.recalc_trade_from_orders()
+
+    # Calling recalc with single initial order should not change anything
+    assert trade.amount == o1_amount
+    assert trade.stake_amount == o1_amount
+    assert trade.open_rate == o1_rate
+    assert trade.fee_open_cost == o1_fee_cost
+    assert trade.open_trade_value == o1_trade_val
+
+    # One additional adjustment / DCA order
+    o2_amount = 125
+    o2_rate = 0.9
+    o2_cost = o2_amount * o2_rate
+    o2_fee_cost = o2_cost * fee.return_value
+    o2_trade_val = o2_cost + o2_fee_cost
+
+    order2 = Order(
+        ft_order_side='buy',
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side="buy",
+        price=o2_rate,
+        average=o2_rate,
+        filled=o2_amount,
+        remaining=0,
+        cost=o2_cost,
+        order_date=arrow.utcnow().shift(hours=-1).datetime,
+        order_filled_date=arrow.utcnow().shift(hours=-1).datetime,
+    )
+    trade.orders.append(order2)
+    trade.recalc_trade_from_orders()
+
+    # Validate that the trade now has new averaged open price and total values
+    avg_price = (o1_cost + o2_cost) / (o1_amount + o2_amount)
+    assert trade.amount == o1_amount + o2_amount
+    assert trade.stake_amount == o1_amount + o2_cost
+    assert trade.open_rate == avg_price
+    assert trade.fee_open_cost == o1_fee_cost + o2_fee_cost
+    assert trade.open_trade_value == o1_trade_val + o2_trade_val
+
+    # Let's try with multiple additional orders
+    o3_amount = 150
+    o3_rate = 0.85
+    o3_cost = o3_amount * o3_rate
+    o3_fee_cost = o3_cost * fee.return_value
+    o3_trade_val = o3_cost + o3_fee_cost
+
+    order3 = Order(
+        ft_order_side='buy',
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side="buy",
+        price=o3_rate,
+        average=o3_rate,
+        filled=o3_amount,
+        remaining=0,
+        cost=o3_cost,
+        order_date=arrow.utcnow().shift(hours=-1).datetime,
+        order_filled_date=arrow.utcnow().shift(hours=-1).datetime,
+    )
+    trade.orders.append(order3)
+    trade.recalc_trade_from_orders()
+
+    # Validate that the sum is still correct and open rate is averaged
+    avg_price = (o1_cost + o2_cost + o3_cost) / (o1_amount + o2_amount + o3_amount)
+    assert trade.amount == o1_amount + o2_amount + o3_amount
+    assert trade.stake_amount == o1_cost + o2_cost + o3_cost
+    assert trade.open_rate == avg_price
+    assert pytest.approx(trade.fee_open_cost) == o1_fee_cost + o2_fee_cost + o3_fee_cost
+    assert pytest.approx(trade.open_trade_value) == o1_trade_val + o2_trade_val + o3_trade_val
+
+    # Just to make sure sell orders are ignored, let's calculate one more time.
+    sell1 = Order(
+        ft_order_side='sell',
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side="sell",
+        price=avg_price + 0.95,
+        average=avg_price + 0.95,
+        filled=o1_amount + o2_amount + o3_amount,
+        remaining=0,
+        cost=o1_cost + o2_cost + o3_cost,
+        order_date=trade.open_date,
+        order_filled_date=trade.open_date,
+    )
+    trade.orders.append(sell1)
+    trade.recalc_trade_from_orders()
+
+    assert trade.amount == o1_amount + o2_amount + o3_amount
+    assert trade.stake_amount == o1_cost + o2_cost + o3_cost
+    assert trade.open_rate == avg_price
+    assert pytest.approx(trade.fee_open_cost) == o1_fee_cost + o2_fee_cost + o3_fee_cost
+    assert pytest.approx(trade.open_trade_value) == o1_trade_val + o2_trade_val + o3_trade_val
+
+
+@pytest.mark.parametrize('is_short', [True, False])
+def test_recalc_trade_from_orders_ignores_bad_orders(fee, is_short):
+
+    o1_amount = 100
+    o1_rate = 1
+    o1_cost = o1_amount * o1_rate
+    o1_fee_cost = o1_cost * fee.return_value
+    o1_trade_val = o1_cost - o1_fee_cost if is_short else o1_cost + o1_fee_cost
+    entry_side = "sell" if is_short else "buy"
+    exit_side = "buy" if is_short else "sell"
+
+    trade = Trade(
+        pair='ADA/USDT',
+        stake_amount=o1_cost,
+        open_date=arrow.utcnow().shift(hours=-2).datetime,
+        amount=o1_amount,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        exchange='binance',
+        open_rate=o1_rate,
+        max_rate=o1_rate,
+        is_short=is_short,
+        leverage=1.0,
+    )
+    trade.update_fee(o1_fee_cost, 'BNB', fee.return_value, entry_side)
+    # Check with 1 order
+    order1 = Order(
+        ft_order_side=entry_side,
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side=entry_side,
+        price=o1_rate,
+        average=o1_rate,
+        filled=o1_amount,
+        remaining=0,
+        cost=o1_amount,
+        order_date=trade.open_date,
+        order_filled_date=trade.open_date,
+    )
+    trade.orders.append(order1)
+    trade.recalc_trade_from_orders()
+
+    # Calling recalc with single initial order should not change anything
+    assert trade.amount == o1_amount
+    assert trade.stake_amount == o1_amount
+    assert trade.open_rate == o1_rate
+    assert trade.fee_open_cost == o1_fee_cost
+    assert trade.open_trade_value == o1_trade_val
+    assert trade.nr_of_successful_entries == 1
+
+    order2 = Order(
+        ft_order_side=entry_side,
+        ft_pair=trade.pair,
+        ft_is_open=True,
+        status="open",
+        symbol=trade.pair,
+        order_type="market",
+        side=entry_side,
+        price=o1_rate,
+        average=o1_rate,
+        filled=o1_amount,
+        remaining=0,
+        cost=o1_cost,
+        order_date=arrow.utcnow().shift(hours=-1).datetime,
+        order_filled_date=arrow.utcnow().shift(hours=-1).datetime,
+    )
+    trade.orders.append(order2)
+    trade.recalc_trade_from_orders()
+
+    # Validate that the trade values have not been changed
+    assert trade.amount == o1_amount
+    assert trade.stake_amount == o1_amount
+    assert trade.open_rate == o1_rate
+    assert trade.fee_open_cost == o1_fee_cost
+    assert trade.open_trade_value == o1_trade_val
+    assert trade.nr_of_successful_entries == 1
+
+    # Let's try with some other orders
+    order3 = Order(
+        ft_order_side=entry_side,
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="cancelled",
+        symbol=trade.pair,
+        order_type="market",
+        side=entry_side,
+        price=1,
+        average=2,
+        filled=0,
+        remaining=4,
+        cost=5,
+        order_date=arrow.utcnow().shift(hours=-1).datetime,
+        order_filled_date=arrow.utcnow().shift(hours=-1).datetime,
+    )
+    trade.orders.append(order3)
+    trade.recalc_trade_from_orders()
+
+    # Validate that the order values still are ignoring orders 2 and 3
+    assert trade.amount == o1_amount
+    assert trade.stake_amount == o1_amount
+    assert trade.open_rate == o1_rate
+    assert trade.fee_open_cost == o1_fee_cost
+    assert trade.open_trade_value == o1_trade_val
+    assert trade.nr_of_successful_entries == 1
+
+    order4 = Order(
+        ft_order_side=entry_side,
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side=entry_side,
+        price=o1_rate,
+        average=o1_rate,
+        filled=o1_amount,
+        remaining=0,
+        cost=o1_cost,
+        order_date=arrow.utcnow().shift(hours=-1).datetime,
+        order_filled_date=arrow.utcnow().shift(hours=-1).datetime,
+    )
+    trade.orders.append(order4)
+    trade.recalc_trade_from_orders()
+
+    # Validate that the trade values have been changed
+    assert trade.amount == 2 * o1_amount
+    assert trade.stake_amount == 2 * o1_amount
+    assert trade.open_rate == o1_rate
+    assert trade.fee_open_cost == 2 * o1_fee_cost
+    assert trade.open_trade_value == 2 * o1_trade_val
+    assert trade.nr_of_successful_entries == 2
+
+    # Just to make sure exit orders are ignored, let's calculate one more time.
+    sell1 = Order(
+        ft_order_side=exit_side,
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side=exit_side,
+        price=4,
+        average=3,
+        filled=2,
+        remaining=1,
+        cost=5,
+        order_date=trade.open_date,
+        order_filled_date=trade.open_date,
+    )
+    trade.orders.append(sell1)
+    trade.recalc_trade_from_orders()
+
+    assert trade.amount == 2 * o1_amount
+    assert trade.stake_amount == 2 * o1_amount
+    assert trade.open_rate == o1_rate
+    assert trade.fee_open_cost == 2 * o1_fee_cost
+    assert trade.open_trade_value == 2 * o1_trade_val
+    assert trade.nr_of_successful_entries == 2
+
+    # Check with 1 order
+    order_noavg = Order(
+        ft_order_side=entry_side,
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side=entry_side,
+        price=o1_rate,
+        average=None,
+        filled=o1_amount,
+        remaining=0,
+        cost=o1_amount,
+        order_date=trade.open_date,
+        order_filled_date=trade.open_date,
+    )
+    trade.orders.append(order_noavg)
+    trade.recalc_trade_from_orders()
+
+    # Calling recalc with single initial order should not change anything
+    assert trade.amount == 3 * o1_amount
+    assert trade.stake_amount == 3 * o1_amount
+    assert trade.open_rate == o1_rate
+    assert trade.fee_open_cost == 3 * o1_fee_cost
+    assert trade.open_trade_value == 3 * o1_trade_val
+    assert trade.nr_of_successful_entries == 3
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_select_filled_orders(fee):
+    create_mock_trades(fee)
+
+    trades = Trade.get_trades().all()
+
+    # Closed buy order, no sell order
+    orders = trades[0].select_filled_orders('buy')
+    assert orders is not None
+    assert len(orders) == 1
+    order = orders[0]
+    assert order.amount > 0
+    assert order.filled > 0
+    assert order.side == 'buy'
+    assert order.ft_order_side == 'buy'
+    assert order.status == 'closed'
+    orders = trades[0].select_filled_orders('sell')
+    assert orders is not None
+    assert len(orders) == 0
+
+    # closed buy order, and closed sell order
+    orders = trades[1].select_filled_orders('buy')
+    assert orders is not None
+    assert len(orders) == 1
+
+    orders = trades[1].select_filled_orders('sell')
+    assert orders is not None
+    assert len(orders) == 1
+
+    # Has open buy order
+    orders = trades[3].select_filled_orders('buy')
+    assert orders is not None
+    assert len(orders) == 0
+    orders = trades[3].select_filled_orders('sell')
+    assert orders is not None
+    assert len(orders) == 0
+
+    # Open sell order
+    orders = trades[4].select_filled_orders('buy')
+    assert orders is not None
+    assert len(orders) == 1
+    orders = trades[4].select_filled_orders('sell')
+    assert orders is not None
+    assert len(orders) == 0
diff --git a/tests/test_plotting.py b/tests/test_plotting.py
index 51301a464..97f367608 100644
--- a/tests/test_plotting.py
+++ b/tests/test_plotting.py
@@ -1,4 +1,3 @@
-
 from copy import deepcopy
 from pathlib import Path
 from unittest.mock import MagicMock
@@ -46,7 +45,7 @@ def test_init_plotscript(default_conf, mocker, testdatadir):
     default_conf['trade_source'] = "file"
     default_conf['timeframe'] = "5m"
     default_conf["datadir"] = testdatadir
-    default_conf['exportfilename'] = testdatadir / "backtest-result_test.json"
+    default_conf['exportfilename'] = testdatadir / "backtest-result_new.json"
     supported_markets = ["TRX/BTC", "ADA/BTC"]
     ret = init_plotscript(default_conf, supported_markets)
     assert "ohlcv" in ret
@@ -158,7 +157,7 @@ def test_plot_trades(testdatadir, caplog):
     assert fig == fig1
     assert log_has("No trades found.", caplog)
     pair = "ADA/BTC"
-    filename = testdatadir / "backtest-result_test.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     trades = load_backtest_data(filename)
     trades = trades.loc[trades['pair'] == pair]
 
@@ -172,7 +171,7 @@ def test_plot_trades(testdatadir, caplog):
     assert len(trades) == len(trade_buy.x)
     assert trade_buy.marker.color == 'cyan'
     assert trade_buy.marker.symbol == 'circle-open'
-    assert trade_buy.text[0] == '4.0%, roi, 15 min'
+    assert trade_buy.text[0] == '3.99%, buy_tag, roi, 15 min'
 
     trade_sell = find_trace_in_fig_data(figure.data, 'Sell - Profit')
     assert isinstance(trade_sell, go.Scatter)
@@ -180,7 +179,7 @@ def test_plot_trades(testdatadir, caplog):
     assert len(trades.loc[trades['profit_ratio'] > 0]) == len(trade_sell.x)
     assert trade_sell.marker.color == 'green'
     assert trade_sell.marker.symbol == 'square-open'
-    assert trade_sell.text[0] == '4.0%, roi, 15 min'
+    assert trade_sell.text[0] == '3.99%, buy_tag, roi, 15 min'
 
     trade_sell_loss = find_trace_in_fig_data(figure.data, 'Sell - Loss')
     assert isinstance(trade_sell_loss, go.Scatter)
@@ -188,7 +187,7 @@ def test_plot_trades(testdatadir, caplog):
     assert len(trades.loc[trades['profit_ratio'] <= 0]) == len(trade_sell_loss.x)
     assert trade_sell_loss.marker.color == 'red'
     assert trade_sell_loss.marker.symbol == 'square-open'
-    assert trade_sell_loss.text[5] == '-10.4%, stop_loss, 720 min'
+    assert trade_sell_loss.text[5] == '-10.45%, stop_loss, 720 min'
 
 
 def test_generate_candlestick_graph_no_signals_no_trades(default_conf, mocker, testdatadir, caplog):
@@ -201,8 +200,10 @@ def test_generate_candlestick_graph_no_signals_no_trades(default_conf, mocker, t
     timerange = TimeRange(None, 'line', 0, -1000)
     data = history.load_pair_history(pair=pair, timeframe='1m',
                                      datadir=testdatadir, timerange=timerange)
-    data['buy'] = 0
-    data['sell'] = 0
+    data['enter_long'] = 0
+    data['exit_long'] = 0
+    data['enter_short'] = 0
+    data['exit_short'] = 0
 
     indicators1 = []
     indicators2 = []
@@ -223,8 +224,10 @@ def test_generate_candlestick_graph_no_signals_no_trades(default_conf, mocker, t
     assert row_mock.call_count == 2
     assert trades_mock.call_count == 1
 
-    assert log_has("No buy-signals found.", caplog)
-    assert log_has("No sell-signals found.", caplog)
+    assert log_has("No enter_long-signals found.", caplog)
+    assert log_has("No exit_long-signals found.", caplog)
+    assert log_has("No enter_short-signals found.", caplog)
+    assert log_has("No exit_short-signals found.", caplog)
 
 
 def test_generate_candlestick_graph_no_trades(default_conf, mocker, testdatadir):
@@ -250,7 +253,7 @@ def test_generate_candlestick_graph_no_trades(default_conf, mocker, testdatadir)
     assert fig.layout.title.text == pair
     figure = fig.layout.figure
 
-    assert len(figure.data) == 6
+    assert len(figure.data) == 8
     # Candlesticks are plotted first
     candles = find_trace_in_fig_data(figure.data, "Price")
     assert isinstance(candles, go.Candlestick)
@@ -258,15 +261,15 @@ def test_generate_candlestick_graph_no_trades(default_conf, mocker, testdatadir)
     volume = find_trace_in_fig_data(figure.data, "Volume")
     assert isinstance(volume, go.Bar)
 
-    buy = find_trace_in_fig_data(figure.data, "buy")
-    assert isinstance(buy, go.Scatter)
+    enter_long = find_trace_in_fig_data(figure.data, "enter_long")
+    assert isinstance(enter_long, go.Scatter)
     # All buy-signals should be plotted
-    assert int(data.buy.sum()) == len(buy.x)
+    assert int(data['enter_long'].sum()) == len(enter_long.x)
 
-    sell = find_trace_in_fig_data(figure.data, "sell")
-    assert isinstance(sell, go.Scatter)
+    exit_long = find_trace_in_fig_data(figure.data, "exit_long")
+    assert isinstance(exit_long, go.Scatter)
     # All buy-signals should be plotted
-    assert int(data.sell.sum()) == len(sell.x)
+    assert int(data['exit_long'].sum()) == len(exit_long.x)
 
     assert find_trace_in_fig_data(figure.data, "Bollinger Band")
 
@@ -295,7 +298,7 @@ def test_generate_plot_file(mocker, caplog):
 
 
 def test_add_profit(testdatadir):
-    filename = testdatadir / "backtest-result_test.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     bt_data = load_backtest_data(filename)
     timerange = TimeRange.parse_timerange("20180110-20180112")
 
@@ -315,7 +318,7 @@ def test_add_profit(testdatadir):
 
 
 def test_generate_profit_graph(testdatadir):
-    filename = testdatadir / "backtest-result_test.json"
+    filename = testdatadir / "backtest_results/backtest-result_new.json"
     trades = load_backtest_data(filename)
     timerange = TimeRange.parse_timerange("20180110-20180112")
     pairs = ["TRX/BTC", "XLM/BTC"]
@@ -337,15 +340,20 @@ def test_generate_profit_graph(testdatadir):
     assert fig.layout.yaxis3.title.text == "Profit BTC"
 
     figure = fig.layout.figure
-    assert len(figure.data) == 5
+    assert len(figure.data) == 7
 
     avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
     assert isinstance(avgclose, go.Scatter)
 
     profit = find_trace_in_fig_data(figure.data, "Profit")
     assert isinstance(profit, go.Scatter)
-    profit = find_trace_in_fig_data(figure.data, "Max drawdown 10.45%")
-    assert isinstance(profit, go.Scatter)
+    drawdown = find_trace_in_fig_data(figure.data, "Max drawdown 35.69%")
+    assert isinstance(drawdown, go.Scatter)
+    parallel = find_trace_in_fig_data(figure.data, "Parallel trades")
+    assert isinstance(parallel, go.Scatter)
+
+    underwater = find_trace_in_fig_data(figure.data, "Underwater Plot")
+    assert isinstance(underwater, go.Scatter)
 
     for pair in pairs:
         profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
@@ -377,7 +385,7 @@ def test_load_and_plot_trades(default_conf, mocker, caplog, testdatadir):
 
     default_conf['trade_source'] = 'file'
     default_conf["datadir"] = testdatadir
-    default_conf['exportfilename'] = testdatadir / "backtest-result_test.json"
+    default_conf['exportfilename'] = testdatadir / "backtest-result_new.json"
     default_conf['indicators1'] = ["sma5", "ema10"]
     default_conf['indicators2'] = ["macd"]
     default_conf['pairs'] = ["ETH/BTC", "LTC/BTC"]
@@ -448,7 +456,7 @@ def test_plot_profit(default_conf, mocker, testdatadir):
                        match=r"No trades found, cannot generate Profit-plot.*"):
         plot_profit(default_conf)
 
-    default_conf['exportfilename'] = testdatadir / "backtest-result_test.json"
+    default_conf['exportfilename'] = testdatadir / "backtest_results/backtest-result_new.json"
 
     plot_profit(default_conf)
 
diff --git a/tests/test_wallets.py b/tests/test_wallets.py
index 53e3b758e..73a34bbae 100644
--- a/tests/test_wallets.py
+++ b/tests/test_wallets.py
@@ -6,7 +6,7 @@ import pytest
 
 from freqtrade.constants import UNLIMITED_STAKE_AMOUNT
 from freqtrade.exceptions import DependencyException
-from tests.conftest import get_patched_freqtradebot, patch_wallet
+from tests.conftest import create_mock_trades, get_patched_freqtradebot, patch_wallet
 
 
 def test_sync_wallet_at_boot(mocker, default_conf):
@@ -180,22 +180,32 @@ def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_r
     assert result == 0
 
 
-@pytest.mark.parametrize('stake_amount,min_stake_amount,max_stake_amount,expected', [
-    (22, 11, 50, 22),
-    (100, 11, 500, 100),
-    (1000, 11, 500, 500),  # Above max-stake
-    (20, 15, 10, 0),  # Minimum stake > max-stake
-    (1, 11, 100, 11),  # Below min stake
-    (1, 15, 10, 0),  # Below min stake and min_stake > max_stake
+@pytest.mark.parametrize('stake_amount,min_stake,stake_available,max_stake,expected', [
+    (22, 11, 50, 10000, 22),
+    (100, 11, 500, 10000, 100),
+    (1000, 11, 500, 10000, 500),  # Above stake_available
+    (700, 11, 1000, 400, 400),  # Above max_stake, below stake available
+    (20, 15, 10, 10000, 0),  # Minimum stake > stake_available
+    (9, 11, 100, 10000, 11),  # Below min stake
+    (1, 15, 10, 10000, 0),  # Below min stake and min_stake > stake_available
+    (20, 50, 100, 10000, 0),  # Below min stake and stake * 1.3 > min_stake
+    (1000, None, 1000, 10000, 1000),  # No min-stake-amount could be determined
 
 ])
-def test__validate_stake_amount(mocker, default_conf,
-                                stake_amount, min_stake_amount, max_stake_amount, expected):
+def test_validate_stake_amount(
+    mocker,
+    default_conf,
+    stake_amount,
+    min_stake,
+    stake_available,
+    max_stake,
+    expected,
+):
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
 
     mocker.patch("freqtrade.wallets.Wallets.get_available_stake_amount",
-                 return_value=max_stake_amount)
-    res = freqtrade.wallets._validate_stake_amount('XRP/USDT', stake_amount, min_stake_amount)
+                 return_value=stake_available)
+    res = freqtrade.wallets.validate_stake_amount('XRP/USDT', stake_amount, min_stake, max_stake)
     assert res == expected
 
 
@@ -224,3 +234,131 @@ def test_get_starting_balance(mocker, default_conf, available_capital, closed_pr
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
 
     assert freqtrade.wallets.get_starting_balance() == expected
+
+
+def test_sync_wallet_futures_live(mocker, default_conf):
+    default_conf['dry_run'] = False
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    mock_result = [
+        {
+            "symbol": "ETH/USDT:USDT",
+            "timestamp": None,
+            "datetime": None,
+            "initialMargin": 0.0,
+            "initialMarginPercentage": None,
+            "maintenanceMargin": 0.0,
+            "maintenanceMarginPercentage": 0.005,
+            "entryPrice": 0.0,
+            "notional": 100.0,
+            "leverage": 5.0,
+            "unrealizedPnl": 0.0,
+            "contracts": 100.0,
+            "contractSize": 1,
+            "marginRatio": None,
+            "liquidationPrice": 0.0,
+            "markPrice": 2896.41,
+            "collateral": 20,
+            "marginType": "isolated",
+            "side": 'short',
+            "percentage": None
+        },
+        {
+            "symbol": "ADA/USDT:USDT",
+            "timestamp": None,
+            "datetime": None,
+            "initialMargin": 0.0,
+            "initialMarginPercentage": None,
+            "maintenanceMargin": 0.0,
+            "maintenanceMarginPercentage": 0.005,
+            "entryPrice": 0.0,
+            "notional": 100.0,
+            "leverage": 5.0,
+            "unrealizedPnl": 0.0,
+            "contracts": 100.0,
+            "contractSize": 1,
+            "marginRatio": None,
+            "liquidationPrice": 0.0,
+            "markPrice": 0.91,
+            "collateral": 20,
+            "marginType": "isolated",
+            "side": 'short',
+            "percentage": None
+        },
+        {
+            # Closed position
+            "symbol": "SOL/BUSD:BUSD",
+            "timestamp": None,
+            "datetime": None,
+            "initialMargin": 0.0,
+            "initialMarginPercentage": None,
+            "maintenanceMargin": 0.0,
+            "maintenanceMarginPercentage": 0.005,
+            "entryPrice": 0.0,
+            "notional": 0.0,
+            "leverage": 5.0,
+            "unrealizedPnl": 0.0,
+            "contracts": 0.0,
+            "contractSize": 1,
+            "marginRatio": None,
+            "liquidationPrice": 0.0,
+            "markPrice": 15.41,
+            "collateral": 0.0,
+            "marginType": "isolated",
+            "side": 'short',
+            "percentage": None
+        }
+    ]
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value={
+            "USDT": {
+                "free": 900,
+                "used": 100,
+                "total": 1000
+            },
+        }),
+        fetch_positions=MagicMock(return_value=mock_result)
+    )
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    assert len(freqtrade.wallets._wallets) == 1
+    assert len(freqtrade.wallets._positions) == 2
+
+    assert 'USDT' in freqtrade.wallets._wallets
+    assert 'ETH/USDT:USDT' in freqtrade.wallets._positions
+    assert freqtrade.wallets._last_wallet_refresh > 0
+
+    # Remove ETH/USDT:USDT position
+    del mock_result[0]
+    freqtrade.wallets.update()
+    assert len(freqtrade.wallets._positions) == 1
+    assert 'ETH/USDT:USDT' not in freqtrade.wallets._positions
+
+
+def test_sync_wallet_futures_dry(mocker, default_conf, fee):
+    default_conf['dry_run'] = True
+    default_conf['trading_mode'] = 'futures'
+    default_conf['margin_mode'] = 'isolated'
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    assert len(freqtrade.wallets._wallets) == 1
+    assert len(freqtrade.wallets._positions) == 0
+
+    create_mock_trades(fee, is_short=None)
+
+    freqtrade.wallets.update()
+
+    assert len(freqtrade.wallets._wallets) == 1
+    assert len(freqtrade.wallets._positions) == 4
+    positions = freqtrade.wallets.get_all_positions()
+    positions['ETH/BTC'].side == 'short'
+    positions['ETC/BTC'].side == 'long'
+    positions['XRP/BTC'].side == 'long'
+    positions['LTC/BTC'].side == 'short'
+
+    assert freqtrade.wallets.get_starting_balance() == default_conf['dry_run_wallet']
+    total = freqtrade.wallets.get_total('BTC')
+    free = freqtrade.wallets.get_free('BTC')
+    used = freqtrade.wallets.get_used('BTC')
+    assert free + used == total
diff --git a/tests/test_worker.py b/tests/test_worker.py
index c3773d296..ddca9525b 100644
--- a/tests/test_worker.py
+++ b/tests/test_worker.py
@@ -43,7 +43,7 @@ def test_worker_stopped(mocker, default_conf, caplog) -> None:
     worker.freqtrade.state = State.STOPPED
     state = worker._worker(old_state=State.RUNNING)
     assert state is State.STOPPED
-    assert log_has('Changing state to: STOPPED', caplog)
+    assert log_has('Changing state from RUNNING to: STOPPED', caplog)
     assert mock_throttle.call_count == 1
 
 
diff --git a/tests/testdata/backtest-result_multistrat.json b/tests/testdata/backtest-result_multistrat.json
deleted file mode 100644
index 553783dfa..000000000
--- a/tests/testdata/backtest-result_multistrat.json
+++ /dev/null
@@ -1 +0,0 @@
-{"strategy": {"StrategyTestV2": {"trades": [{"pair": "TRX/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:15:00+00:00", "close_date": "2018-01-10 07:20:00+00:00", "trade_duration": 5, "open_rate": 9.64e-05, "close_rate": 0.00010074887218045112, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1037.344398340249, "profit_abs": 0.00399999999999999}, {"pair": "ADA/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:15:00+00:00", "close_date": "2018-01-10 07:30:00+00:00", "trade_duration": 15, "open_rate": 4.756e-05, "close_rate": 4.9705563909774425e-05, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2102.6072329688814, "profit_abs": 0.00399999999999999}, {"pair": "XLM/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:25:00+00:00", "close_date": "2018-01-10 07:35:00+00:00", "trade_duration": 10, "open_rate": 3.339e-05, "close_rate": 3.489631578947368e-05, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2994.908655286014, "profit_abs": 0.0040000000000000036}, {"pair": "TRX/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:25:00+00:00", "close_date": "2018-01-10 07:40:00+00:00", "trade_duration": 15, "open_rate": 9.696e-05, "close_rate": 0.00010133413533834584, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1031.3531353135315, "profit_abs": 0.00399999999999999}, {"pair": "ETH/BTC", "profit_percent": -0.0, "open_date": "2018-01-10 07:35:00+00:00", "close_date": "2018-01-10 08:35:00+00:00", "trade_duration": 60, "open_rate": 0.0943, "close_rate": 0.09477268170426063, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1.0604453870625663, "profit_abs": 0.0}, {"pair": "XMR/BTC", "profit_percent": 0.00997506, "open_date": "2018-01-10 07:40:00+00:00", "close_date": "2018-01-10 08:10:00+00:00", "trade_duration": 30, "open_rate": 0.02719607, "close_rate": 0.02760503345864661, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 3.677001860930642, "profit_abs": 0.0010000000000000009}, {"pair": "ZEC/BTC", "profit_percent": 0.0, "open_date": "2018-01-10 08:15:00+00:00", "close_date": "2018-01-10 09:55:00+00:00", "trade_duration": 100, "open_rate": 0.04634952, "close_rate": 0.046581848421052625, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2.1575196463739, "profit_abs": 0.0}, {"pair": "NXT/BTC", "profit_percent": -0.0, "open_date": "2018-01-10 14:45:00+00:00", "close_date": "2018-01-10 15:50:00+00:00", "trade_duration": 65, "open_rate": 3.066e-05, "close_rate": 3.081368421052631e-05, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 3261.5786040443577, "profit_abs": -1.3877787807814457e-17}, {"pair": "LTC/BTC", "profit_percent": 0.0, "open_date": "2018-01-10 16:35:00+00:00", "close_date": "2018-01-10 17:15:00+00:00", "trade_duration": 40, "open_rate": 0.0168999, "close_rate": 0.016984611278195488, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 5.917194776300452, "profit_abs": 1.3877787807814457e-17}, {"pair": "ETH/BTC", "profit_percent": -0.0, "open_date": "2018-01-10 16:40:00+00:00", "close_date": "2018-01-10 17:20:00+00:00", "trade_duration": 40, "open_rate": 0.09132568, "close_rate": 0.0917834528320802, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1.0949822656672252, "profit_abs": 0.0}, {"pair": "ETH/BTC", "profit_percent": -0.0, "open_date": "2018-01-10 18:50:00+00:00", "close_date": "2018-01-10 19:45:00+00:00", "trade_duration": 55, "open_rate": 0.08898003, "close_rate": 0.08942604518796991, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1.1238476768326557, "profit_abs": -1.3877787807814457e-17}, {"pair": "ETH/BTC", "profit_percent": 0.0, "open_date": "2018-01-10 22:15:00+00:00", "close_date": "2018-01-10 23:00:00+00:00", "trade_duration": 45, "open_rate": 0.08560008, "close_rate": 0.08602915308270676, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1.1682232072680307, "profit_abs": 0.0}, {"pair": "ETC/BTC", "profit_percent": 0.00997506, "open_date": "2018-01-10 22:50:00+00:00", "close_date": "2018-01-10 23:20:00+00:00", "trade_duration": 30, "open_rate": 0.00249083, "close_rate": 0.0025282860902255634, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 40.147260150231055, "profit_abs": 0.000999999999999987}, {"pair": "NXT/BTC", "profit_percent": -0.0, "open_date": "2018-01-10 23:15:00+00:00", "close_date": "2018-01-11 00:15:00+00:00", "trade_duration": 60, "open_rate": 3.022e-05, "close_rate": 3.037147869674185e-05, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 3309.0668431502318, "profit_abs": -1.3877787807814457e-17}, {"pair": "ETC/BTC", "profit_percent": 0.01995012, "open_date": "2018-01-10 23:40:00+00:00", "close_date": "2018-01-11 00:05:00+00:00", "trade_duration": 25, "open_rate": 0.002437, "close_rate": 0.0024980776942355883, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 41.03405826836274, "profit_abs": 0.001999999999999974}, {"pair": "ZEC/BTC", "profit_percent": 0.00997506, "open_date": "2018-01-11 00:00:00+00:00", "close_date": "2018-01-11 00:35:00+00:00", "trade_duration": 35, "open_rate": 0.04771803, "close_rate": 0.04843559436090225, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2.0956439316543456, "profit_abs": 0.0010000000000000009}, {"pair": "XLM/BTC", "profit_percent": -0.10448878, "open_date": "2018-01-11 03:40:00+00:00", "close_date": "2018-01-11 04:25:00+00:00", "trade_duration": 45, "open_rate": 3.651e-05, "close_rate": 3.2859000000000005e-05, "open_at_end": false, "sell_reason": "stop_loss", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2738.9756231169545, "profit_abs": -0.01047499999999997}, {"pair": "ETH/BTC", "profit_percent": 0.00997506, "open_date": "2018-01-11 03:55:00+00:00", "close_date": "2018-01-11 04:25:00+00:00", "trade_duration": 30, "open_rate": 0.08824105, "close_rate": 0.08956798308270676, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1.1332594070446804, "profit_abs": 0.0010000000000000009}, {"pair": "ETC/BTC", "profit_percent": -0.0, "open_date": "2018-01-11 04:00:00+00:00", "close_date": "2018-01-11 04:50:00+00:00", "trade_duration": 50, "open_rate": 0.00243, "close_rate": 0.002442180451127819, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 41.1522633744856, "profit_abs": -1.3877787807814457e-17}, {"pair": "ZEC/BTC", "profit_percent": 0.01995012, "open_date": "2018-01-11 04:30:00+00:00", "close_date": "2018-01-11 04:55:00+00:00", "trade_duration": 25, "open_rate": 0.04545064, "close_rate": 0.046589753784461146, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2.200189040242338, "profit_abs": 0.001999999999999988}, {"pair": "XLM/BTC", "profit_percent": 0.01995012, "open_date": "2018-01-11 04:30:00+00:00", "close_date": "2018-01-11 04:50:00+00:00", "trade_duration": 20, "open_rate": 3.372e-05, "close_rate": 3.456511278195488e-05, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2965.599051008304, "profit_abs": 0.001999999999999988}, {"pair": "XMR/BTC", "profit_percent": 0.01995012, "open_date": "2018-01-11 04:55:00+00:00", "close_date": "2018-01-11 05:15:00+00:00", "trade_duration": 20, "open_rate": 0.02644, "close_rate": 0.02710265664160401, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 3.7821482602118004, "profit_abs": 0.001999999999999988}, {"pair": "ETH/BTC", "profit_percent": -0.0, "open_date": "2018-01-11 11:20:00+00:00", "close_date": "2018-01-11 12:00:00+00:00", "trade_duration": 40, "open_rate": 0.08812, "close_rate": 0.08856170426065162, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1.1348161597821154, "profit_abs": 0.0}, {"pair": "XMR/BTC", "profit_percent": -0.0, "open_date": "2018-01-11 11:35:00+00:00", "close_date": "2018-01-11 12:15:00+00:00", "trade_duration": 40, "open_rate": 0.02683577, "close_rate": 0.026970285137844607, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 3.7263696923919087, "profit_abs": 0.0}, {"pair": "ADA/BTC", "profit_percent": 0.01995012, "open_date": "2018-01-11 14:00:00+00:00", "close_date": "2018-01-11 14:25:00+00:00", "trade_duration": 25, "open_rate": 4.919e-05, "close_rate": 5.04228320802005e-05, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2032.9335230737956, "profit_abs": 0.0020000000000000018}, {"pair": "ETH/BTC", "profit_percent": -0.0, "open_date": "2018-01-11 19:25:00+00:00", "close_date": "2018-01-11 20:35:00+00:00", "trade_duration": 70, "open_rate": 0.08784896, "close_rate": 0.08828930566416039, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1.1383174029607181, "profit_abs": -1.3877787807814457e-17}, {"pair": "ADA/BTC", "profit_percent": -0.0, "open_date": "2018-01-11 22:35:00+00:00", "close_date": "2018-01-11 23:30:00+00:00", "trade_duration": 55, "open_rate": 5.105e-05, "close_rate": 5.130588972431077e-05, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 1958.8638589618022, "profit_abs": -1.3877787807814457e-17}, {"pair": "XLM/BTC", "profit_percent": 0.00997506, "open_date": "2018-01-11 22:55:00+00:00", "close_date": 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{"pair": "ZEC/BTC", "profit_percent": -0.0, "open_date": "2018-01-11 23:55:00+00:00", "close_date": "2018-01-12 01:15:00+00:00", "trade_duration": 80, "open_rate": 0.048, "close_rate": 0.04824060150375939, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2.0833333333333335, "profit_abs": -1.3877787807814457e-17}, {"pair": "XLM/BTC", "profit_percent": 0.01995012, "open_date": "2018-01-12 21:15:00+00:00", "close_date": "2018-01-12 21:40:00+00:00", "trade_duration": 25, "open_rate": 4.692e-05, "close_rate": 4.809593984962405e-05, "open_at_end": false, "sell_reason": "roi", "fee_open": 0.0025, "fee_close": 0.0025, "amount": 2131.287297527707, "profit_abs": 0.001999999999999974}, {"pair": "ETC/BTC", "profit_percent": -0.0, "open_date": "2018-01-13 00:55:00+00:00", "close_date": "2018-01-13 06:20:00+00:00", "trade_duration": 325, "open_rate": 0.00256966, "close_rate": 0.0025825405012531327, "open_at_end": false, "sell_reason": "roi", "fee_open": 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diff --git a/tests/testdata/backtest-result_new.json b/tests/testdata/backtest-result_new.json
deleted file mode 100644
index 84f3806ea..000000000
--- a/tests/testdata/backtest-result_new.json
+++ /dev/null
@@ -1 +0,0 @@
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diff --git a/tests/testdata/backtest-result_test.json b/tests/testdata/backtest-result_test.json
deleted file mode 100644
index dce22acaf..000000000
--- a/tests/testdata/backtest-result_test.json
+++ /dev/null
@@ -1 +0,0 @@
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diff --git a/tests/testdata/.last_result.json b/tests/testdata/backtest_results/.last_result.json
similarity index 100%
rename from tests/testdata/.last_result.json
rename to tests/testdata/backtest_results/.last_result.json
diff --git a/tests/testdata/backtest_results/backtest-result_multistrat.json b/tests/testdata/backtest_results/backtest-result_multistrat.json
new file mode 100644
index 000000000..786795d67
--- /dev/null
+++ b/tests/testdata/backtest_results/backtest-result_multistrat.json
@@ -0,0 +1 @@
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diff --git a/tests/testdata/backtest_results/backtest-result_multistrat.meta.json b/tests/testdata/backtest_results/backtest-result_multistrat.meta.json
new file mode 100644
index 000000000..906edcece
--- /dev/null
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diff --git a/tests/testdata/backtest_results/backtest-result_new.json b/tests/testdata/backtest_results/backtest-result_new.json
new file mode 100644
index 000000000..03fdb455a
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diff --git a/tests/testdata/backtest_results/backtest-result_new.meta.json b/tests/testdata/backtest_results/backtest-result_new.meta.json
new file mode 100644
index 000000000..57ecdb19d
--- /dev/null
+++ b/tests/testdata/backtest_results/backtest-result_new.meta.json
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+{
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+}
diff --git a/tests/testdata/futures/UNITTEST_USDT-1h-mark.json b/tests/testdata/futures/UNITTEST_USDT-1h-mark.json
new file mode 100644
index 000000000..312f616fb
--- /dev/null
+++ b/tests/testdata/futures/UNITTEST_USDT-1h-mark.json
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diff --git a/tests/testdata/futures/UNITTEST_USDT_USDT-1h-mark.h5 b/tests/testdata/futures/UNITTEST_USDT_USDT-1h-mark.h5
new file mode 100644
index 000000000..e6b128dc1
Binary files /dev/null and b/tests/testdata/futures/UNITTEST_USDT_USDT-1h-mark.h5 differ
diff --git a/tests/testdata/futures/XRP_USDT-1h-futures.json b/tests/testdata/futures/XRP_USDT-1h-futures.json
new file mode 100644
index 000000000..58944e717
--- /dev/null
+++ b/tests/testdata/futures/XRP_USDT-1h-futures.json
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diff --git a/tests/testdata/futures/XRP_USDT-1h-futures.json.gz b/tests/testdata/futures/XRP_USDT-1h-futures.json.gz
new file mode 100644
index 000000000..f2a223b03
Binary files /dev/null and b/tests/testdata/futures/XRP_USDT-1h-futures.json.gz differ
diff --git a/tests/testdata/futures/XRP_USDT-1h-mark.json b/tests/testdata/futures/XRP_USDT-1h-mark.json
new file mode 100644
index 000000000..26703b945
--- /dev/null
+++ b/tests/testdata/futures/XRP_USDT-1h-mark.json
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diff --git a/tests/testdata/futures/XRP_USDT-8h-funding_rate.json b/tests/testdata/futures/XRP_USDT-8h-funding_rate.json
new file mode 100644
index 000000000..494da4efc
--- /dev/null
+++ b/tests/testdata/futures/XRP_USDT-8h-funding_rate.json
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/tests/testdata/futures/XRP_USDT-8h-mark.json b/tests/testdata/futures/XRP_USDT-8h-mark.json
new file mode 100644
index 000000000..63dad259b
--- /dev/null
+++ b/tests/testdata/futures/XRP_USDT-8h-mark.json
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/tests/testdata/strategy_SampleStrategy.fthypt b/tests/testdata/strategy_SampleStrategy.fthypt
index 6dc2b9ab1..6a64a9c4f 100644
--- a/tests/testdata/strategy_SampleStrategy.fthypt
+++ b/tests/testdata/strategy_SampleStrategy.fthypt
@@ -1,5 +1,5 @@
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Avg profit   0.02%. Median profit   0.00%. Total profit  0.00011576 BTC (   0.00\u03A3%). Avg duration 3:03:00 min.","total_profit":1.1576000000000034e-07,"current_epoch":5,"is_initial_point":true,"is_best":false}
diff --git a/tests/testdata/testconfigs/recursive.json b/tests/testdata/testconfigs/recursive.json
new file mode 100644
index 000000000..33ab12008
--- /dev/null
+++ b/tests/testdata/testconfigs/recursive.json
@@ -0,0 +1,6 @@
+{
+    // This file fails as it's loading itself over and over
+    "add_config_files": [
+        "./recursive.json"
+    ]
+}
diff --git a/tests/testdata/testconfigs/test_base_config.json b/tests/testdata/testconfigs/test_base_config.json
new file mode 100644
index 000000000..d15c5890b
--- /dev/null
+++ b/tests/testdata/testconfigs/test_base_config.json
@@ -0,0 +1,12 @@
+{
+    "stake_currency": "",
+    "dry_run": true,
+    "exchange": {
+        "name": "",
+        "key": "",
+        "secret": "",
+        "pair_whitelist": [],
+        "ccxt_async_config": {
+        }
+    }
+}
diff --git a/tests/testdata/testconfigs/test_pricing2_conf.json b/tests/testdata/testconfigs/test_pricing2_conf.json
new file mode 100644
index 000000000..094783a60
--- /dev/null
+++ b/tests/testdata/testconfigs/test_pricing2_conf.json
@@ -0,0 +1,18 @@
+{
+    "entry_pricing": {
+        "price_side": "same",
+        "use_order_book": true,
+        "order_book_top": 1,
+        "price_last_balance": 0.0,
+        "check_depth_of_market": {
+            "enabled": false,
+            "bids_to_ask_delta": 1
+        }
+    },
+    "exit_pricing":{
+        "price_side": "other",
+        "use_order_book": true,
+        "order_book_top": 1,
+        "price_last_balance": 0.0
+    }
+}
diff --git a/tests/testdata/testconfigs/test_pricing_conf.json b/tests/testdata/testconfigs/test_pricing_conf.json
new file mode 100644
index 000000000..59516d65e
--- /dev/null
+++ b/tests/testdata/testconfigs/test_pricing_conf.json
@@ -0,0 +1,21 @@
+{
+    "entry_pricing": {
+        "price_side": "same",
+        "use_order_book": true,
+        "order_book_top": 1,
+        "price_last_balance": 0.0,
+        "check_depth_of_market": {
+            "enabled": false,
+            "bids_to_ask_delta": 1
+        }
+    },
+    "exit_pricing":{
+        "price_side": "same",
+        "use_order_book": true,
+        "order_book_top": 1,
+        "price_last_balance": 0.0
+    },
+    "add_config_files": [
+        "./test_pricing2_conf.json"
+    ]
+}
diff --git a/tests/testdata/testconfigs/testconfig.json b/tests/testdata/testconfigs/testconfig.json
new file mode 100644
index 000000000..87ed6daef
--- /dev/null
+++ b/tests/testdata/testconfigs/testconfig.json
@@ -0,0 +1,6 @@
+{
+    "add_config_files": [
+        "test_base_config.json",
+        "test_pricing_conf.json"
+    ]
+}