"description":"The timeframe to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). \nUsually specified in the strategy and missing in the configuration.",
"type":"string"
},
"proxy_coin":{
"description":"Proxy coin - must be used for specific futures modes (e.g. BNFCR)",
"type":"string"
},
"stake_currency":{
"description":"Currency used for staking.",
"type":"string"
@@ -102,8 +106,17 @@
},
"dry_run_wallet":{
"description":"Initial wallet balance for dry run mode.",
"type":"number",
"default":1000
"type":[
"number",
"object"
],
"default":1000,
"patternProperties":{
"^[a-zA-Z0-9]+$":{
"type":"number"
}
},
"additionalProperties":false
},
"cancel_open_orders_on_exit":{
"description":"Cancel open orders when exiting.",
@@ -244,7 +257,8 @@
"enum":[
"day",
"week",
"month"
"month",
"year"
]
}
},
@@ -528,6 +542,10 @@
"description":"Edge configuration.",
"$ref":"#/definitions/edge"
},
"log_config":{
"description":"Logging configuration.",
"$ref":"#/definitions/logging"
},
"freqai":{
"description":"FreqAI configuration.",
"$ref":"#/definitions/freqai"
@@ -592,9 +610,21 @@
"type":"string"
},
"chat_id":{
"description":"Telegram chat ID",
"description":"Telegram chat or group ID",
"type":"string"
},
"topic_id":{
"description":"Telegram topic ID - only applicable for group chats",
"type":"string"
},
"authorized_users":{
"description":"Authorized users for the bot.",
"type":"array",
"items":{
"type":"string"
},
"uniqueItems":true
},
"allow_custom_messages":{
"description":"Allow sending custom messages from the Strategy.",
"type":"boolean",
@@ -682,12 +712,18 @@
},
"exit_fill":{
"description":"Telegram setting for exit fill signals.",
"type":"string",
"enum":[
"on",
"off",
"silent"
"type":[
"string",
"object"
],
"additionalProperties":{
"type":"string",
"enum":[
"on",
"off",
"silent"
]
},
"default":"on"
},
"exit_cancel":{
@@ -956,7 +992,7 @@
"type":"string"
}
},
"x":{
"verbosity":{
"description":"Logging verbosity level.",
"type":"string",
"enum":[
@@ -1032,7 +1068,6 @@
"enum":[
"json",
"jsongz",
"hdf5",
"feather",
"parquet"
],
@@ -1044,7 +1079,6 @@
"enum":[
"json",
"jsongz",
"hdf5",
"feather",
"parquet"
],
@@ -1251,6 +1285,30 @@
"allowed_risk"
]
},
"logging":{
"type":"object",
"properties":{
"version":{
"type":"number",
"const":1
},
"formatters":{
"type":"object"
},
"handlers":{
"type":"object"
},
"root":{
"type":"object"
}
},
"required":[
"version",
"formatters",
"handlers",
"root"
]
},
"external_message_consumer":{
"description":"Configuration for external message consumer.",
"type":"object",
@@ -1345,10 +1403,10 @@
"type":"boolean",
"default":false
},
"keras":{
"description":"Use Keras for model training.",
"type":"boolean",
"default":false
"identifier":{
"description":"A unique ID for the current model. Must be changed when modifying features.",
"type":"string",
"default":"example"
},
"write_metrics_to_disk":{
"description":"Write metrics to disk?",
@@ -1378,16 +1436,49 @@
"type":"number",
"default":7
},
"identifier":{
"description":"A unique ID for the current model. Must be changed when modifying features.",
"type":"string",
"default":"example"
"live_retrain_hours":{
"description":"Frequency of retraining during dry/live runs.",
"type":"number",
"default":0
},
"expiration_hours":{
"description":"Avoid making predictions if a model is more than `expiration_hours` old. Defaults to 0 (no expiration).",
"type":"number",
"default":0
},
"save_backtest_models":{
"description":"Save models to disk when running backtesting.",
"type":"boolean",
"default":false
},
"fit_live_predictions_candles":{
"description":"Number of historical candles to use for computing target (label) statistics from prediction data, instead of from the training dataset.",
"type":"integer"
},
"data_kitchen_thread_count":{
"description":"Designate the number of threads you want to use for data processing (outlier methods, normalization, etc.).",
"type":"integer"
},
"activate_tensorboard":{
"description":"Indicate whether or not to activate tensorboard",
"type":"boolean",
"default":true
},
"wait_for_training_iteration_on_reload":{
"description":"Wait for the next training iteration to complete after /reload or ctrl+c.",
"type":"boolean",
"default":true
},
"continual_learning":{
"description":"Use the final state of the most recently trained model as starting point for the new model, allowing for incremental learning.",
"type":"boolean",
"default":false
},
"keras":{
"description":"Use Keras for model training.",
"type":"boolean",
"default":false
},
"feature_parameters":{
"description":"The parameters used to engineer the feature set",
@@ -37,8 +37,9 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
min_date: datetime,
max_date: datetime,
config: Config,
processed: Dict[str, DataFrame],
backtest_stats: Dict[str, Any],
processed: dict[str, DataFrame],
backtest_stats: dict[str, Any],
starting_balance: float,
**kwargs,
) -> float:
"""
@@ -70,6 +71,7 @@ Currently, the arguments are:
* `config`: Config object used (Note: Not all strategy-related parameters will be updated here if they are part of a hyperopt space).
* `processed`: Dict of Dataframes with the pair as keys containing the data used for backtesting.
* `backtest_stats`: Backtesting statistics using the same format as the backtesting file "strategy" substructure. Available fields can be seen in `generate_strategy_stats()` in `optimize_reports.py`.
* `starting_balance`: Starting balance used for backtesting.
This function needs to return a floating point number (`float`). Smaller numbers will be interpreted as better results. The parameters and balancing for this is up to you.
@@ -103,7 +105,7 @@ class MyAwesomeStrategy(IStrategy):
@@ -4,6 +4,7 @@ This guide walks you through utilizing public trade data for advanced orderflow
!!! Warning "Experimental Feature"
The orderflow feature is currently in beta and may be subject to changes in future releases. Please report any issues or feedback on the [Freqtrade GitHub repository](https://github.com/freqtrade/freqtrade/issues).
It's also currently not been tested with freqAI - and combining these two features is considered out of scope at this point.
!!! Warning "Performance"
Orderflow requires raw trades data. This data is rather large, and can cause a slow initial startup, when freqtrade needs to download the trades data for the last X candles. Additionally, enabling this feature will cause increased memory usage. Please ensure to have sufficient resources available.
@@ -69,8 +70,8 @@ dataframe["delta"] # Difference between ask and bid volume.
dataframe["min_delta"] # Minimum delta within the candle
dataframe["max_delta"] # Maximum delta within the candle
dataframe["total_trades"] # Total number of trades
dataframe["stacked_imbalances_bid"] # Price level of stacked bid imbalance
dataframe["stacked_imbalances_ask"] # Price level of stacked ask imbalance
dataframe["stacked_imbalances_bid"] # List of price levels of stacked bid imbalance range beginnings
dataframe["stacked_imbalances_ask"] # List of price levels of stacked ask imbalance range beginnings
```
You can access these columns in your strategy code for further analysis. Here's an example:
Freqtrade uses the default logging module provided by python.
Python allows for extensive [logging configuration](https://docs.python.org/3/library/logging.config.html#logging.config.dictConfig) in this regards - way more than what can be covered here.
Default logging (Colored terminal output) is setup by default if no `log_config` is provided.
Using `--logfile logfile.log` will enable the RotatingFileHandler.
If you're not content with the log format - or with the default settings provided for the RotatingFileHandler, you can customize logging to your liking.
The default configuration looks roughly like the below - with the file handler being provided - but not enabled.
Highlighted lines in the above code-block define the Rich handler and belong together.
The formatter "standard" and "file" will belong to the FileHandler.
Each handler must use one of the defined formatters (by name) - and it's class must be available and a valid logging class.
To actually use a handler - it must be in the "handlers" section inside the "root" segment.
If this section is left out, freqtrade will provide no output (in the non-configured handler, anyway).
!!! Tip "Explicit log configuration"
We recommend to extract the logging configuration from your main configuration, and provide it to your bot via [multiple configuration files](configuration.md#multiple-configuration-files) functionality. This will avoid unnecessary code duplication.
---
On many Linux systems the bot can be configured to send its log messages to `syslog` or `journald` system services. Logging to a remote `syslog` server is also available on Windows. The special values for the `--logfile` command line option can be used for this.
### Logging to syslog
To send Freqtrade log messages to a local or remote `syslog` service use the `--logfile` command line option with the value in the following format:
To send Freqtrade log messages to a local or remote `syslog` service use the `"log_config"` setup option to configure logging.
* `--logfile syslog:<syslog_address>` -- send log messages to `syslog` service using the `<syslog_address>` as the syslog address.
// Use one of the other options above as address instead?
"address": "/dev/log"
}
},
"root": {
"handlers": [
// other handlers
"syslog",
]
}
The syslog address can be either a Unix domain socket (socket filename) or a UDP socket specification, consisting of IP address and UDP port, separated by the `:` character.
}
}
```
So, the following are the examples of possible usages:
[Additional log-handlers](#advanced-logging) may need to be configured to for example also have log output in the console.
* `--logfile syslog:/dev/log` -- log to syslog (rsyslog) using the `/dev/log` socket, suitable for most systems.
* `--logfile syslog` -- same as above, the shortcut for `/dev/log`.
* `--logfile syslog:/var/run/syslog` -- log to syslog (rsyslog) using the `/var/run/syslog` socket. Use this on MacOS.
* `--logfile syslog:localhost:514` -- log to local syslog using UDP socket, if it listens on port 514.
* `--logfile syslog:<ip>:514` -- log to remote syslog at IP address and port 514. This may be used on Windows for remote logging to an external syslog server.
#### Syslog usage
Log messages are send to `syslog` with the `user` facility. So you can see them with the following commands:
* `tail -f /var/log/user`, or
* `tail -f /var/log/user`, or
* install a comprehensive graphical viewer (for instance, 'Log File Viewer' for Ubuntu).
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.
On many systems `syslog` (`rsyslog`) fetches data from `journald` (and vice versa), so both syslog or 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
@@ -228,13 +309,69 @@ For `syslog` (`rsyslog`), the reduction mode can be switched on. This will reduc
$RepeatedMsgReduction on
```
#### Syslog addressing
The syslog address can be either a Unix domain socket (socket filename) or a UDP socket specification, consisting of IP address and UDP port, separated by the `:` character.
So, the following are the examples of possible addresses:
* `"address": "/dev/log"` -- log to syslog (rsyslog) using the `/dev/log` socket, suitable for most systems.
* `"address": "/var/run/syslog"` -- log to syslog (rsyslog) using the `/var/run/syslog` socket. Use this on MacOS.
* `"address": "localhost:514"` -- log to local syslog using UDP socket, if it listens on port 514.
* `"address": "<ip>:514"` -- log to remote syslog at IP address and port 514. This may be used on Windows for remote logging to an external syslog server.
??? Info "Deprecated - configure syslog via command line"
`--logfile syslog:<syslog_address>` -- send log messages to `syslog` service using the `<syslog_address>` as the syslog address.
The syslog address can be either a Unix domain socket (socket filename) or a UDP socket specification, consisting of IP address and UDP port, separated by the `:` character.
So, the following are the examples of possible usages:
* `--logfile syslog:/dev/log` -- log to syslog (rsyslog) using the `/dev/log` socket, suitable for most systems.
* `--logfile syslog` -- same as above, the shortcut for `/dev/log`.
* `--logfile syslog:/var/run/syslog` -- log to syslog (rsyslog) using the `/var/run/syslog` socket. Use this on MacOS.
* `--logfile syslog:localhost:514` -- log to local syslog using UDP socket, if it listens on port 514.
* `--logfile syslog:<ip>:514` -- log to remote syslog at IP address and port 514. This may be used on Windows for remote logging to an external syslog server.
### Logging to journald
This needs the `cysystemd` python package installed as dependency (`pip install cysystemd`), which is not available on Windows. Hence, the whole journald logging functionality is not available for a bot running on Windows.
To send Freqtrade log messages to `journald` system service use the `--logfile` command line option with the value in the following format:
To send Freqtrade log messages to `journald` system service, add the following configuration snippet to your configuration.
* `--logfile journald` -- send log messages to `journald`.
[Additional log-handlers](#advanced-logging) may need to be configured to for example also have log output in the console.
Log messages are send to `journald` with the `user` facility. So you can see them with the following commands:
@@ -244,3 +381,51 @@ Log messages are send to `journald` with the `user` facility. So you can see the
There are many other options in the `journalctl` utility to filter the messages, see manual pages for this utility.
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.
??? Info "Deprecated - configure journald via command line"
To send Freqtrade log messages to `journald` system service use the `--logfile` command line option with the value in the following format:
`--logfile journald` -- send log messages to `journald`.
### Log format as JSON
You can also configure the default output stream to use JSON format instead.
The "fmt_dict" attribute defines the keys for the json output - as well as the [python logging LogRecord attributes](https://docs.python.org/3/library/logging.html#logrecord-attributes).
The below configuration will change the default output to JSON. The same formatter could however also be used in combination with the `RotatingFileHandler`.
We recommend to keep one format in human readable form.
@@ -305,6 +209,7 @@ A backtesting result will look like that:
| Sortino | 1.88 |
| Sharpe | 2.97 |
| Calmar | 6.29 |
| SQN | 2.45 |
| Profit factor | 1.11 |
| Expectancy (Ratio) | -0.15 (-0.05) |
| Avg. stake amount | 0.001 BTC |
@@ -411,6 +316,7 @@ It contains some useful key metrics about performance of your strategy on backte
| Sortino | 1.88 |
| Sharpe | 2.97 |
| Calmar | 6.29 |
| SQN | 2.45 |
| Profit factor | 1.11 |
| Expectancy (Ratio) | -0.15 (-0.05) |
| Avg. stake amount | 0.001 BTC |
@@ -464,6 +370,7 @@ It contains some useful key metrics about performance of your strategy on backte
-`Sortino`: Annualized Sortino ratio.
-`Sharpe`: Annualized Sharpe ratio.
-`Calmar`: Annualized Calmar ratio.
-`SQN`: System Quality Number (SQN) - by Van Tharp.
-`Profit factor`: profit / loss.
-`Avg. stake amount`: Average stake amount, either `stake_amount` or the average when using dynamic stake amount.
-`Total trade volume`: Volume generated on the exchange to reach the above profit.
@@ -528,6 +435,20 @@ To save time, by default backtest will reuse a cached result from within the las
To further analyze your backtest results, freqtrade will export the trades to file by default.
You can then load the trades to perform further analysis as shown in the [data analysis](strategy_analysis_example.md#load-backtest-results-to-pandas-dataframe) backtesting section.
### Backtest output file
The output file freqtrade produces is a zip file containing the following files:
- The backtest report in json format
- the market change data in feather format
- a copy of the strategy file
- a copy of the strategy parameters (if a parameter file was used)
- a sanitized copy of the config file
This will ensure results are reproducible - under the assumption that the same data is available.
Only the strategy file and the config file are included in the zip file, eventual dependencies are not included.
## Assumptions made by backtesting
Since backtesting lacks some detailed information about what happens within a candle, it needs to take a few assumptions:
@@ -558,6 +479,7 @@ Since backtesting lacks some detailed information about what happens within a ca
- Stoploss
- ROI
- Trailing stoploss
- Position reversals (futures only) happen if an entry signal in the other direction than the closing trade triggers at the candle the existing trade closes.
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.
Also, keep in mind that past results don't guarantee future success.
@@ -572,7 +494,7 @@ These limits are usually listed in the exchange documentation as "trading rules"
Backtesting (as well as live and dry-run) does honor these limits, and will ensure that a stoploss can be placed below this value - so the value will be slightly higher than what the exchange specifies.
Freqtrade has however no information about historic limits.
This can lead to situations where trading-limits are inflated by using a historic price, resulting in minimum amounts > 50$.
This can lead to situations where trading-limits are inflated by using a historic price, resulting in minimum amounts > 50\$.
For example:
@@ -603,7 +525,12 @@ To utilize this, you can append `--timeframe-detail 5m` to your regular backtest
This will load 1h data as well as 5m data for the timeframe. The strategy will be analyzed with the 1h timeframe, and Entry orders will only be placed at the main timeframe, however Order fills and exit signals will be evaluated at the 5m candle, simulating intra-candle movements.
This will load 1h data (the main timeframe) as well as 5m data (detail timeframe) for the selected timerange.
The strategy will be analyzed with the 1h timeframe.
Candles where activity may take place (there's an active signal, the pair is in a trade) are evaluated at the 5m timeframe.
This will allow for a more accurate simulation of intra-candle movements - and can lead to different results, especially on higher timeframes.
Entries will generally still happen at the main candle's open, however freed trade slots may be freed earlier (if the exit signal is triggered on the 5m candle), which can then be used for a new trade of a different pair.
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).
@@ -615,6 +542,27 @@ Also, data must be available / downloaded already.
!!! Tip
You can use this function as the last part of strategy development, to ensure your strategy is not exploiting one of the [backtesting assumptions](#assumptions-made-by-backtesting). Strategies that perform similarly well with this mode have a good chance to perform well in dry/live modes too (although only forward-testing (dry-mode) can really confirm a strategy).
??? Sample "Extreme Difference Example"
Using `--timeframe-detail` on an extreme example (all below pairs have the 10:00 candle with an entry signal) may lead to the following backtesting Trade sequence with 1 max_open_trades:
The difference is significant, as without detail data, only the first `max_open_trades` signals per candle are evaluated, and the trade slots are only freed at the end of the candle, allowing for a new trade to be opened at the next candle.
## Backtesting multiple strategies
To compare multiple strategies, a list of Strategies can be provided to backtesting.
@@ -54,11 +54,13 @@ By default, the bot loop runs every few seconds (`internals.process_throttle_sec
* Check timeouts for open orders.
* Calls `check_entry_timeout()` strategy callback for open entry orders.
* Calls `check_exit_timeout()` strategy callback for open exit orders.
* Calls `adjust_entry_price()` strategy callback for open entry orders.
* Calls `adjust_order_price()` strategy callback for open orders.
* Calls `adjust_entry_price()` strategy callback for open entry orders. *only called when `adjust_order_price()` is not implemented*
* Calls `adjust_exit_price()` strategy callback for open exit orders. *only called when `adjust_order_price()` is not implemented*
* 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.
* Before an 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 entry signal trying to enter new positions.
@@ -80,7 +82,9 @@ This loop will be repeated again and again until the bot is stopped.
* Loops per candle simulating entry and exit points.
* Calls `bot_loop_start()` strategy callback.
* Check for Order timeouts, either via the `unfilledtimeout` configuration, or via `check_entry_timeout()` / `check_exit_timeout()` strategy callbacks.
* Calls `adjust_entry_price()` strategy callback for open entry orders.
* Calls `adjust_order_price()` strategy callback for open orders.
* Calls `adjust_entry_price()` strategy callback for open entry orders. *only called when `adjust_order_price()` is not implemented!*
* Calls `adjust_exit_price()` strategy callback for open exit orders. *only called when `adjust_order_price()` is not implemented!*
* 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).
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.
Environment variables are loaded after the initial configuration. As such, you cannot provide the path to the configuration through environment variables. Please use `--config path/to/config.json` for that.
This also applies to user_dir to some degree. while the user directory can be set through environment variables - the configuration will **not** be loaded from that location.
This also applies to `user_dir` to some degree. while the user directory can be set through environment variables - the configuration will **not** be loaded from that location.
### Multiple configuration files
@@ -146,10 +152,10 @@ Freqtrade can also load many options via command line (CLI) arguments (check out
The prevalence for all Options is as follows:
- CLI arguments override any other option
- [Environment Variables](#environment-variables)
- Configuration files are used in sequence (the last file wins) and override Strategy configurations.
- Strategy configurations are only used if they are not set via configuration or command-line arguments. These options are marked with [Strategy Override](#parameters-in-the-strategy) in the below table.
* CLI arguments override any other option
* [Environment Variables](#environment-variables)
* Configuration files are used in sequence (the last file wins) and override Strategy configurations.
* Strategy configurations are only used if they are not set via configuration or command-line arguments. These options are marked with [Strategy Override](#parameters-in-the-strategy) in the below table.
### Parameters table
@@ -168,7 +174,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `timeframe` | The timeframe to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). Usually missing in configuration, and specified in the strategy. [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
| `dry_run_wallet` | Define the starting amount in stake currency for the simulated wallet used by the bot running in Dry Run mode. [More information below](#dry-run-wallet)<br>*Defaults to `1000`.* <br> **Datatype:** Float or Dict
| `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 `true`.* <br> **Datatype:** Boolean
| `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
@@ -183,7 +189,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `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
| | **Unfilled timeout**
| `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.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. [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
| `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
@@ -225,6 +231,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `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
| `exchange.only_from_ccxt` | Prevent data-download from data.binance.vision. Leaving this as false can greatly speed up downloads, but may be problematic if the site is not available.<br>*Defaults to `false`*<br> **Datatype:** Boolean
| `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
| | **Plugins**
| `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation of all possible configuration options.
@@ -275,6 +282,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `dataformat_ohlcv` | Data format to use to store historical candle (OHLCV) data. <br> *Defaults to `feather`*. <br> **Datatype:** String
| `dataformat_trades` | Data format to use to store historical trades data. <br> *Defaults to `feather`*. <br> **Datatype:** String
| `reduce_df_footprint` | Recast all numeric columns to float32/int32, with the objective of reducing ram/disk usage (and decreasing train/inference timing in FreqAI). (Currently only affects FreqAI use-cases) <br> **Datatype:** Boolean. <br> Default: `False`.
| `log_config` | Dictionary containing the log config for python logging. [more info](advanced-setup.md#advanced-logging) <br> **Datatype:** dict. <br> Default: `FtRichHandler`
### Parameters in the strategy
@@ -295,10 +303,10 @@ Values set in the configuration file always overwrite values set in the strategy
* `order_time_in_force`
* `unfilledtimeout`
* `disable_dataframe_checks`
- `use_exit_signal`
* `use_exit_signal`
* `exit_profit_only`
- `exit_profit_offset`
- `ignore_roi_if_entry_signal`
* `exit_profit_offset`
* `ignore_roi_if_entry_signal`
* `ignore_buying_expired_candle_after`
* `position_adjustment_enable`
* `max_entry_position_adjustment`
@@ -311,18 +319,37 @@ There are several methods to configure how much of the stake currency the bot wi
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$, the minimum stake amount to buy this pair is `20 * 0.6 ~= 12`.
This exchange has also a limit on USD - where all orders must be > 10$ - which however does not apply in this case.
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$, instead, it'll make sure that there's enough space to place a stoploss below the pair (+ an offset, defined by `amount_reserve_percent`, which defaults to 5%).
To guarantee safe execution, freqtrade will not allow buying with a stake-amount of 10.1\$, instead, it'll make sure that there's enough space to place a stoploss below the pair (+ an offset, defined by `amount_reserve_percent`, which defaults to 5%).
With a reserve of 5%, the minimum stake amount would be ~12.6$ (`12 * (1 + 0.05)`). If we take into account a stoploss of 10% on top of that - we'd end up with a value of ~14$ (`12.6 / (1 - 0.1)`).
With a reserve of 5%, the minimum stake amount would be ~12.6\$ (`12 * (1 + 0.05)`). If we take into account a stoploss of 10% on top of that - we'd end up with a value of ~14\$ (`12.6 / (1 - 0.1)`).
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. 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.
#### Dry-run wallet
When running in dry-run mode, the bot will use a simulated wallet to execute trades. The starting balance of this wallet is defined by `dry_run_wallet` (defaults to 1000).
For more complex scenarios, you can also assign a dictionary to `dry_run_wallet` to define the starting balance for each currency.
```json
"dry_run_wallet": {
"BTC": 0.01,
"ETH": 2,
"USDT": 1000
}
```
Command line options (`--dry-run-wallet`) can be used to override the configuration value, but only for the float value, not for the dictionary. If you'd like to use the dictionary, please adjust the configuration file.
!!! Note
Balances not in stake-currency will not be used for trading, but are shown as part of the wallet balance.
On Cross-margin exchanges, the wallet balance may be used to calculate the available collateral for trading.
#### Tradable balance
By default, the bot assumes that the `complete amount - 1%` is at it's disposal, and when using [dynamic stake amount](#dynamic-stake-amount), it will split the complete balance into `max_open_trades` buckets per trade.
@@ -362,9 +389,9 @@ To overcome this, the option `amend_last_stake_amount` can be set to `True`, whi
In the example above this would mean:
- Trade1: 400 USDT
- Trade2: 400 USDT
- Trade3: 200 USDT
* Trade1: 400 USDT
* Trade2: 400 USDT
* Trade3: 200 USDT
!!! Note
This option only applies with [Static stake amount](#static-stake-amount) - since [Dynamic stake amount](#dynamic-stake-amount) divides the balances evenly.
@@ -11,86 +11,16 @@ Without provided configuration, `--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, 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.
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 missing timerange 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 the `--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.
--prepend Allow data prepending. (Data-appending is disabled)
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
--logfile FILE, --log-file 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, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
```
--8<-- "commands/download-data.md"
!!! 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.
`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.
* 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 change the exchange used to download the historical data from, either use `--exchange <exchange>` - or specify a different configuration file.
* 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.
* Given starting points are ignored if data is already available, downloading only missing data up to today.
* 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.
@@ -162,7 +93,6 @@ Freqtrade currently supports the following data-formats:
* `feather` - a dataformat based on Apache Arrow
* `json` - plain "text" json files
* `jsongz` - a gzip-zipped version of json files
* `hdf5` - a high performance datastore
* `parquet` - columnar datastore (OHLCV only)
By default, both OHLCV data and trades data are stored in the `feather` format.
@@ -172,8 +102,8 @@ To persist this change, you should also add the following snippet to your config
``` jsonc
// ...
"dataformat_ohlcv": "hdf5",
"dataformat_trades": "hdf5",
"dataformat_ohlcv": "feather",
"dataformat_trades": "feather",
// ...
```
@@ -211,7 +141,6 @@ time freqtrade list-data --show-timerange --data-format-ohlcv <dataformat>
| `feather` | 72Mb | 3.5s |
| `json` | 149Mb | 25.6s |
| `jsongz` | 39Mb | 27s |
| `hdf5` | 145Mb | 3.9s |
| `parquet` | 83Mb | 3.8s |
Size has been taken from the BTC/USDT 1m spot combination for the timerange specified above.
@@ -249,55 +178,7 @@ Mixing different stake-currencies is allowed for this file, since it's only used
@@ -81,4 +81,15 @@ version 2023.3 saw the removal of `populate_any_indicators` in favor of split me
## Removal of `protections` from configuration
Setting protections from the configuration via `"protections": [],` has been removed in 2024.10, after having raised deprecation warnings for over 3 years.
Setting protections from the configuration via `"protections": [],` has been removed in 2024.10, after having raised deprecation warnings for over 3 years.
## hdf5 data storage
Using hdf5 as data storage has been deprecated in 2024.12 and was removed in 2025.1. We recommend switching to the feather data format.
Please use the [`convert-data` subcommand](data-download.md#sub-command-convert-data) to convert your existing data to one of the supported formats before updating.
## Configuring advanced logging via config
Configuring syslog and journald via `--logfile systemd` and `--logfile journald` respectively has been deprecated in 2025.3.
Please use configuration based [log setup](advanced-setup.md#advanced-logging) instead.
@@ -162,7 +162,7 @@ Hopefully you also want to contribute this back upstream.
Whatever your motivations are - This should get you off the ground in trying to develop a new Pairlist Handler.
First of all, have a look at the [VolumePairList](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/pairlist/VolumePairList.py) Handler, and best copy this file with a name of your new Pairlist Handler.
First of all, have a look at the [VolumePairList](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/plugins/pairlist/VolumePairList.py) Handler, and best copy this file with a name of your new Pairlist Handler.
This is a simple Handler, which however serves as a good example on how to start developing.
@@ -226,7 +226,7 @@ In `VolumePairList`, this implements different methods of sorting, does early va
It will also take a long time, as freqtrade will need to download every single trade that happened on the exchange for the pair / timerange combination, therefore please be patient.
!!! Warning "rateLimit tuning"
Please pay attention that rateLimit configuration entry holds delay in milliseconds between requests, NOT requests\sec rate.
Please pay attention that rateLimit configuration entry holds delay in milliseconds between requests, NOT requests/sec rate.
So, in order to mitigate Kraken API "Rate limit exceeded" exception, this configuration should be increased, NOT decreased.
For Kucoin, it is suggested to add `"KCS/<STAKE>"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `KCS` on the account or unless you're willing to disable using `KCS` for fees.
Kucoin accounts may use `KCS` for fees, and if a trade happens to be on `KCS`, further trades may consume this position and make the initial `KCS` trade unsellable as the expected amount is not there anymore.
## HTX (formerly Huobi)
## HTX
!!! Tip "Stoploss on Exchange"
HTX 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
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:
@@ -236,6 +257,9 @@ OKX requires a passphrase for each api key, you will therefore need to add this
}
```
If you've registered with OKX on the host my.okx.com (OKX EAA)- you will need to use `"myokx"` as the exchange name.
Using the wrong exchange will result in the error "OKX Error 50119: API key doesn't exist" - as the 2 are separate entities.
!!! 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.
@@ -252,6 +276,14 @@ OKX requires a passphrase for each api key, you will therefore need to add this
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.
Gate API keys require the following permissions on top of the market type you want to trade:
* "Spot Trade" _or_ "Perpetual Futures" (Read and Write) (either select both, or the one matching the market you want to trade)
* "Wallet" (read only)
* "Account" (read only)
Without these permissions, the bot will not start correctly and show errors like "permission missing".
## Bybit
Futures trading on bybit is currently supported for USDT markets, and will use isolated futures mode.
@@ -261,6 +293,7 @@ On startup, freqtrade will set the position mode to "One-way Mode" for the whole
As bybit doesn't provide funding rate history, the dry-run calculation is used for live trades as well.
API Keys for live futures trading must have the following permissions:
* Read-write
* Contract - Orders
* Contract - Positions
@@ -295,6 +328,41 @@ It's therefore required to pass the UID as well.
!!! Warning "Necessary Verification"
Bitmart requires Verification Lvl2 to successfully trade on the spot market through the API - even though trading via UI works just fine with just Lvl1 verification.
## Hyperliquid
!!! Tip "Stoploss on Exchange"
Hyperliquid supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it.
Hyperliquid is a Decentralized Exchange (DEX). Decentralized exchanges work a bit different compared to normal exchanges. Instead of authenticating private API calls using an API key, private API calls need to be signed with the private key of your wallet (We recommend using an api Wallet for this, generated either on Hyperliquid or in your wallet of choice).
This needs to be configured like this:
```json
"exchange": {
"name": "hyperliquid",
"walletAddress": "your_eth_wallet_address",
"privateKey": "your_api_private_key",
// ...
}
```
* walletAddress in hex format: `0x<40 hex characters>` - Can be easily copied from your wallet - and should be your wallet address, not your API Wallet Address.
* privateKey in hex format: `0x<64 hex characters>` - Use the key the API Wallet shows on creation.
Hyperliquid handles deposits and withdrawals on the Arbitrum One chain, a Layer 2 scaling solution built on top of Ethereum. Hyperliquid uses USDC as quote / collateral. The process of depositing USDC on Hyperliquid requires a couple of steps, see [how to start trading](https://hyperliquid.gitbook.io/hyperliquid-docs/onboarding/how-to-start-trading) for details on what steps are needed.
!!! Note "Hyperliquid general usage Notes"
Hyperliquid does not support market orders, however ccxt will simulate market orders by placing limit orders with a maximum slippage of 5%.
Unfortunately, hyperliquid only offers 5000 historic candles, so backtesting will either need to build candles historically (by waiting and downloading the data incrementally over time) - or will be limited to the last 5000 candles.
!!! Info "Some general best practices (non exhaustive)"
* Beware of supply chain attacks, like pip package poisoning etcetera. Whenever you use your private key, make sure your environment is safe.
* Don't use your actual wallet private key for trading. Use the Hyperliquid [API generator](https://app.hyperliquid.xyz/API) to create a separate API wallet.
* Don't store your actual wallet private key on the server you use for freqtrade. Use the API wallet private key instead. This key won't allow withdrawals, only trading.
* Always keep your mnemonic phrase and private key private.
* Don't use the same mnemonic as the one you had to backup when initializing a hardware wallet, using the same mnemonic basically deletes the security of your hardware wallet.
* Create a different software wallet, only transfer the funds you want to trade with to that wallet, and use that wallet to trade on Hyperliquid.
* If you have funds you don't want to use for trading (after making a profit for example), transfer them back to your hardware wallet.
## 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.
@@ -304,7 +372,7 @@ Should you experience constant errors with Nonce (like `InvalidNonce`), it is be
* The Ocean (exchange id: `theocean`) exchange uses Web3 functionality and requires `web3` python package to be installed:
@@ -40,12 +40,18 @@ This could be caused by the following reasons:
* The installation did not complete successfully.
* Please check the [Installation documentation](installation.md).
### The bot starts, but in STOPPED mode
Make sure you set the `initial_state` config option to `"running"` in your config.json
### I have waited 5 minutes, why hasn't the bot made any trades yet?
* Depending on the buy strategy, the amount of whitelisted coins, the
situation of the market etc, it can take up to hours to find a good entry
* Depending on the entry strategy, the amount of whitelisted coins, the
situation of the market etc, it can take up to hours or days to find a good entry
position for a trade. Be patient!
* Backtesting will tell you roughly how many trades to expect - but that won't guarantee that they'll be distributed evenly across time - so you could have 20 trades on one day, and 0 for the rest of the week.
* It may be because of a configuration error. It's best to check the logs, they usually tell you if the bot is simply not getting buy signals (only heartbeat messages), or if there is something wrong (errors / exceptions in the log).
### I have made 12 trades already, why is my total profit negative?
@@ -100,6 +106,19 @@ You can use the `/stopentry` command in Telegram to prevent future trade entry,
Please look at the [advanced setup documentation Page](advanced-setup.md#running-multiple-instances-of-freqtrade).
### I'm getting "Impossible to load Strategy" when starting the bot
This error message is shown when the bot cannot load the strategy.
Usually, you can use `freqtrade list-strategies` to list all available strategies.
The output of this command will also include a status column, showing if the strategy can be loaded.
Please check the following:
* Are you using the correct strategy name? The strategy name is case-sensitive and must correspond to the Strategy class name (not the filename!).
* Is the strategy in the `user_data/strategies` directory, and has the file-ending `.py`?
* Does the bot show other warnings before this error? Maybe you're missing some dependencies for the strategy - which would be highlighted in the log.
* In case of docker - is the strategy directory mounted correctly (check the volumes part of the docker-compose file)?
### I'm getting "Missing data fillup" messages in the log
This message is just a warning that the latest candles had missing candles in them.
@@ -116,6 +135,10 @@ This message is a warning that the candles had a price jump of > 30%.
This might be a sign that the pair stopped trading, and some token exchange took place (e.g. COCOS in 2021 - where price jumped from 0.0000154 to 0.01621).
This message is often accompanied by ["Missing data fillup"](#im-getting-missing-data-fillup-messages-in-the-log) - as trading on such pairs is often stopped for some time.
### I want to reset the bot's database
To reset the bot's database, you can either delete the database (by default `tradesv3.sqlite` or `tradesv3.dryrun.sqlite`), or use a different database url via `--db-url` (e.g. `sqlite:///mynewdatabase.sqlite`).
### 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).
@@ -146,9 +169,9 @@ The same fix should be applied in the configuration file, if order types are def
### I'm trying to start the bot live, but get an API permission error
Errors like `Invalid API-key, IP, or permissions for action` mean exactly what they actually say.
Your API key is either invalid (copy/paste error? check for leading/trailing spaces in the config), expired, or the IP you're running the bot from is not enabled in the Exchange's API console.
Usually, the permission "Spot Trading" (or the equivalent in the exchange you use) will be necessary.
Errors like `Invalid API-key, IP, or permissions for action` mean exactly what they actually say.
Your API key is either invalid (copy/paste error? check for leading/trailing spaces in the config), expired, or the IP you're running the bot from is not enabled in the Exchange's API console.
Usually, the permission "Spot Trading" (or the equivalent in the exchange you use) will be necessary.
Futures will usually have to be enabled specifically.
* **Extensibility** - The generalized and robust architecture allows for incorporating any [machine learning library/method](freqai-configuration.md#using-different-prediction-models) available in Python. Eight examples are currently available, including classifiers, regressors, and a convolutional neural network
* **Smart outlier removal** - Remove outliers from training and prediction data sets using a variety of [outlier detection techniques](freqai-feature-engineering.md#outlier-detection)
* **Crash resilience** - Store trained models to disk to make reloading from a crash fast and easy, and [purge obsolete files](freqai-running.md#purging-old-model-data) for sustained dry/live runs
* **Automatic data normalization** - [Normalize the data](freqai-feature-engineering.md#feature-normalization) in a smart and statistically safe way
* **Automatic data normalization** - [Normalize the data](freqai-feature-engineering.md#building-the-data-pipeline) in a smart and statistically safe way
* **Automatic data download** - Compute timeranges for data downloads and update historic data (in live deployments)
* **Cleaning of incoming data** - Handle NaNs safely before training and model inferencing
* **Dimensionality reduction** - Reduce the size of the training data via [Principal Component Analysis](freqai-feature-engineering.md#data-dimensionality-reduction-with-principal-component-analysis)
If you are using docker, a dedicated tag with FreqAI dependencies is available as `:freqai`. As such - you can replace the image line in your docker compose file with `image: freqtradeorg/freqtrade:develop_freqai`. This image contains the regular FreqAI dependencies. Similar to native installs, Catboost will not be available on ARM based devices. If you would like to use PyTorch or Reinforcement learning, you should use the torch or RL tags, `image: freqtradeorg/freqtrade:develop_freqaitorch`, `image: freqtradeorg/freqtrade:develop_freqairl`.
If you are using docker, a dedicated tag with FreqAI dependencies is available as `:freqai`. As such - you can replace the image line in your docker compose file with `image: freqtradeorg/freqtrade:stable_freqai`. This image contains the regular FreqAI dependencies. Similar to native installs, Catboost will not be available on ARM based devices. If you would like to use PyTorch or Reinforcement learning, you should use the torch or RL tags, `image: freqtradeorg/freqtrade:stable_freqaitorch`, `image: freqtradeorg/freqtrade:stable_freqairl`.
!!! note "docker-compose-freqai.yml"
We do provide an explicit docker-compose file for this in `docker/docker-compose-freqai.yml` - which can be used via `docker compose -f docker/docker-compose-freqai.yml run ...` - or can be copied to replace the original docker file. This docker-compose file also contains a (disabled) section to enable GPU resources within docker containers. This obviously assumes the system has GPU resources available.
### FreqAI position in open-source machine learning landscape
Forecasting chaotic time-series based systems, such as equity/cryptocurrency markets, requires a broad set of tools geared toward testing a wide range of hypotheses. Fortunately, a recent maturation of robust machine learning libraries (e.g. `scikit-learn`) has opened up a wide range of research possibilities. Scientists from a diverse range of fields can now easily prototype their studies on an abundance of established machine learning algorithms. Similarly, these user-friendly libraries enable "citzen scientists" to use their basic Python skills for data exploration. However, leveraging these machine learning libraries on historical and live chaotic data sources can be logistically difficult and expensive. Additionally, robust data collection, storage, and handling presents a disparate challenge. [`FreqAI`](#freqai) aims to provide a generalized and extensible open-sourced framework geared toward live deployments of adaptive modeling for market forecasting. The `FreqAI` framework is effectively a sandbox for the rich world of open-source machine learning libraries. Inside the `FreqAI` sandbox, users find they can combine a wide variety of third-party libraries to test creative hypotheses on a free live 24/7 chaotic data source - cryptocurrency exchange data.
Forecasting chaotic time-series based systems, such as equity/cryptocurrency markets, requires a broad set of tools geared toward testing a wide range of hypotheses. Fortunately, a recent maturation of robust machine learning libraries (e.g. `scikit-learn`) has opened up a wide range of research possibilities. Scientists from a diverse range of fields can now easily prototype their studies on an abundance of established machine learning algorithms. Similarly, these user-friendly libraries enable "citizen scientists" to use their basic Python skills for data exploration. However, leveraging these machine learning libraries on historical and live chaotic data sources can be logistically difficult and expensive. Additionally, robust data collection, storage, and handling presents a disparate challenge. [`FreqAI`](#freqai) aims to provide a generalized and extensible open-sourced framework geared toward live deployments of adaptive modeling for market forecasting. The `FreqAI` framework is effectively a sandbox for the rich world of open-source machine learning libraries. Inside the `FreqAI` sandbox, users find they can combine a wide variety of third-party libraries to test creative hypotheses on a free live 24/7 chaotic data source - cryptocurrency exchange data.
Recursively search for a strategy in the strategies
folder.
--freqaimodel NAME Specify a custom freqaimodels.
--freqaimodel-path PATH
Specify additional lookup path for freqaimodels.
```
--8<-- "commands/hyperopt.md"
### Hyperopt checklist
@@ -867,18 +744,15 @@ You can use the `--print-all` command line option if you would like to see all r
## Position stacking and disabling max market positions
In some situations, you may need to run Hyperopt (and Backtesting) with the
`--eps`/`--enable-position-staking` and `--dmmp`/`--disable-max-market-positions` arguments.
In some situations, you may need to run Hyperopt (and Backtesting) with the`--eps`/`--enable-position-staking` argument, or you may need to set `max_open_trades` to a very high number to disable the limit on the number of open trades.
By default, hyperopt emulates the behavior of the Freqtrade Live Run/Dry Run, where only one
open trade is allowed for every traded pair. The total number of trades open for all pairs
open trade per pair is allowed. The total number of trades open for all pairs
is also limited by the `max_open_trades` setting. During Hyperopt/Backtesting this may lead to
some potential trades to be hidden (or masked) by previously open trades.
potential trades being hidden (or masked) by already open trades.
The `--eps`/`--enable-position-stacking` argument allows emulation of buying the same pair multiple times,
while `--dmmp`/`--disable-max-market-positions` disables applying `max_open_trades`
during Hyperopt/Backtesting (which is equal to setting `max_open_trades` to a very high
number).
The `--eps`/`--enable-position-stacking` argument allows emulation of buying the same pair multiple times.
Using `--max-open-trades` with a very high number will disable the limit on the number of opentrades.
!!! Note
Dry/live runs will **NOT** use position stacking - therefore it does make sense to also validate the strategy without this as it's closer to reality.
@@ -919,13 +793,39 @@ Your epochs should therefore be aligned to the possible values - or you should b
After you run Hyperopt for the desired amount of epochs, you can later list all results for analysis, select only best or profitable once, and show the details for any of the epochs previously evaluated. This can be done with the `hyperopt-list` and `hyperopt-show` sub-commands. The usage of these sub-commands is described in the [Utils](utils.md#list-hyperopt-results) chapter.
## Output debug messages from your strategy
If you want to output debug messages from your strategy, you can use the `logging` module. By default, Freqtrade will output all messages with a level of `INFO` or higher.
Messages printed via `print()` will not be shown in the hyperopt output unless parallelism is disabled (`-j 1`).
It is recommended to use the `logging` module instead.
## Validate backtesting results
Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.
To achieve same the results (number of trades, their durations, profit, etc.) as during Hyperopt, please use the same configuration and parameters (timerange, timeframe, ...) used for hyperopt`--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
To achieve same the results (number of trades, their durations, profit, etc.) as during Hyperopt, please use the same configuration and parameters (timerange, timeframe, ...) used for hyperopt for Backtesting.
### Why do my backtest results not match my hyperopt results?
Should results not match, check the following factors:
* You may have added parameters to hyperopt in `populate_indicators()` where they will be calculated only once **for all epochs**. If you are, for example, trying to optimise multiple SMA timeperiod values, the hyperoptable timeperiod parameter should be placed in `populate_entry_trend()` which is calculated every epoch. See [Optimizing an indicator parameter](https://www.freqtrade.io/en/stable/hyperopt/#optimizing-an-indicator-parameter).
@@ -44,9 +44,24 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged
By default, the `StaticPairList` method is used, which uses a statically defined pair whitelist from the configuration. The pairlist also supports wildcards (in regex-style) - so `.*/BTC` will include all pairs with BTC as a stake.
It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklist`.
It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklist`, which in the below example, will trade BTC/USDT and ETH/USDT - and will prevent BNB/USDT trading.
Both `pair_*list` parameters support regex - so values like `.*/USDT` would enable trading all pairs that are not in the blacklist.
```json
"exchange": {
"name": "...",
// ...
"pair_whitelist": [
"BTC/USDT",
"ETH/USDT",
// ...
],
"pair_blacklist": [
"BNB/USDT",
// ...
]
},
"pairlists": [
{"method": "StaticPairList"}
],
@@ -352,7 +367,7 @@ The optional `bearer_token` will be included in the requests Authorization Heade
#### MarketCapPairList
`MarketCapPairList` employs sorting/filtering of pairs by their marketcap rank based of CoinGecko. It will only recognize coins up to the coin placed at rank 250. The returned pairlist will be sorted based of their marketcap ranks.
`MarketCapPairList` employs sorting/filtering of pairs by their marketcap rank based of CoinGecko. The returned pairlist will be sorted based of their marketcap ranks.
```json
"pairlists": [
@@ -366,7 +381,8 @@ The optional `bearer_token` will be included in the requests Authorization Heade
]
```
`number_assets` defines the maximum number of pairs returned by the pairlist. `max_rank` will determine the maximum rank used in creating/filtering the pairlist. It's expected that some coins within the top `max_rank` marketcap will not be included in the resulting pairlist since not all pairs will have active trading pairs in your preferred market/stake/exchange combination.
`number_assets` defines the maximum number of pairs returned by the pairlist. `max_rank` will determine the maximum rank used in creating/filtering the pairlist. It's expected that some coins within the top `max_rank` marketcap will not be included in the resulting pairlist since not all pairs will have active trading pairs in your preferred market/stake/exchange combination.
While using a `max_rank` bigger than 250 is supported, it's not recommended, as it'll cause multiple API calls to CoinGecko, which can lead to rate limit issues.
The `refresh_period` setting defines the interval (in seconds) at which the marketcap rank data will be refreshed. The default is 86,400 seconds (1 day). The pairlist cache (`refresh_period`) applies to both generating pairlists (when in the first position in the list) and filtering instances (when not in the first position in the list).
@@ -376,6 +392,9 @@ If an incorrect category string is chosen, the plugin will print the available c
!!! Warning "Many categories"
Each added category corresponds to one API call to CoinGecko. The more categories you add, the longer the pairlist generation will take, potentially causing rate limit issues.
!!! Danger "Duplicate symbols in coingecko"
Coingecko often has duplicate symbols, where the same symbol is used for different coins. Freqtrade will use the symbol as is and try to search for it on the exchange. If the symbol exists - it will be used. Freqtrade will however not check if the _intended_ symbol is the one coingecko meant. This can sometimes lead to unexpected results, especially on low volume coins or with meme coin categories.
#### AgeFilter
Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`) or more than `max_days_listed` days (defaults `None` mean infinity).
@@ -28,7 +28,7 @@ Freqtrade is a free and open source crypto trading bot written in Python. It is
- 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).
- Download market data: Download historical data of the exchange and the markets your may want to trade with.
- Backtest: Test your strategy on downloaded historical data.
- Optimize: Find the best parameters for your strategy using hyperoptimization which employs machining learning methods. You can optimize buy, sell, take profit (ROI), stop-loss and trailing stop-loss parameters for your strategy.
- Optimize: Find the best parameters for your strategy using hyperoptimization which employs machine learning methods. You can optimize buy, sell, take profit (ROI), stop-loss and trailing stop-loss parameters for your strategy.
- 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.
@@ -40,21 +40,24 @@ Freqtrade is a free and open source crypto trading bot written in Python. It is
Please read the [exchange specific notes](exchanges.md) to learn about eventual, special configurations needed for each exchange.
- [X] [Binance](https://www.binance.com/)
- [X] [Bitmart](https://bitmart.com/)
- [X] [BingX](https://bingx.com/invite/0EM9RX)
- [X] [Bitmart](https://bitmart.com/)
- [X] [Bybit](https://bybit.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [HTX](https://www.htx.com/) (Former Huobi)
- [X] [HTX](https://www.htx.com/)
- [X] [Hyperliquid](https://hyperliquid.xyz/) (A decentralized exchange, or DEX)
- [X] [Kraken](https://kraken.com/)
- [X] [OKX](https://okx.com/) (Former OKEX)
- [X] [OKX](https://okx.com/)
- [X] [MyOKX](https://okx.com/) (OKX EEA)
- [ ] [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)_
### Supported Futures Exchanges (experimental)
- [X] [Binance](https://www.binance.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [OKX](https://okx.com/)
- [X] [Bybit](https://bybit.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [Hyperliquid](https://hyperliquid.xyz/) (A decentralized exchange, or DEX)
- [X] [OKX](https://okx.com/)
Please make sure to read the [exchange specific notes](exchanges.md), as well as the [trading with leverage](leverage.md) documentation before diving in.
You will run freqtrade in separated `virtual environment`
@@ -232,19 +242,18 @@ python3 -m venv .venv
source .venv/bin/activate
```
#### Install python dependencies
### Install python dependencies
```bash
python3 -m pip install --upgrade pip
python3 -m pip install -r requirements.txt
# install freqtrade
python3 -m pip install -e .
```
### Congratulations
[You are now ready](#you-are-ready) to run the bot.
[You are ready](#you-are-ready), and run the bot
#### (Optional) Post-installation Tasks
### (Optional) Post-installation Tasks
!!! Note
If you run the bot on a server, you should consider using [Docker](docker_quickstart.md) or a terminal multiplexer like `screen` or [`tmux`](https://en.wikipedia.org/wiki/Tmux) to avoid that the bot is stopped on logout.
@@ -333,9 +342,7 @@ cd build_helpers
bash install_ta-lib.sh ${CONDA_PREFIX} nosudo
```
### Congratulations
[You are ready](#you-are-ready), and run the bot
[You are now ready](#you-are-ready) to run the bot.
@@ -88,8 +88,9 @@ Make sure that the following 2 lines are available in your docker-compose file:
### Consuming the API
You can consume the API by using `freqtrade-client` (also available as `scripts/rest_client.py`).
This command can be installed independent of the bot by using `pip install freqtrade-client`.
We advise consuming the API by using the supported `freqtrade-client` package (also available as `scripts/rest_client.py`).
This command can be installed independent of any running freqtrade bot by using `pip install freqtrade-client`.
This module is designed to be lightweight, and only depends on the `requests` and `python-rapidjson` modules, skipping all heavy dependencies freqtrade otherwise needs.
@@ -144,57 +145,6 @@ This method will work for all arguments - check the "show" command for a list of
For a full list of available commands, please refer to the list below.
### Available endpoints
| Command | Description |
|----------|-------------|
| `ping` | Simple command testing the API Readiness - requires no authentication.
| `start` | Starts the trader.
| `stop` | Stops the trader.
| `stopbuy` | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
| `reload_config` | Reloads the configuration file.
| `trades` | List last trades. Limited to 500 trades per call.
| `trade/<tradeid>` | Get specific trade.
| `trades/<tradeid>` | DELETE - Remove trade from the database. Tries to close open orders. Requires manual handling of this trade on the exchange.
| `trades/<tradeid>/open-order` | DELETE - Cancel open order for this trade.
| `trades/<tradeid>/reload` | GET - Reload a trade from the Exchange. Only works in live, and can potentially help recover a trade that was manually sold on the exchange.
| `show_config` | Shows part of the current configuration with relevant settings to operation.
| `logs` | Shows last log messages.
| `status` | Lists all open trades.
| `count` | Displays number of trades used and available.
| `entries [pair]` | Shows profit statistics for each enter tags for given pair (or all pairs if pair isn't given). Pair is optional.
| `exits [pair]` | Shows profit statistics for each exit reasons for given pair (or all pairs if pair isn't given). Pair is optional.
| `mix_tags [pair]` | Shows profit statistics for each combinations of enter tag + exit reasons for given pair (or all pairs if pair isn't given). Pair is optional.
| `locks` | Displays currently locked pairs.
| `delete_lock <lock_id>` | Deletes (disables) the lock by id.
| `locks add <pair>, <until>, [side], [reason]` | Locks a pair until "until". (Until will be rounded up to the nearest timeframe).
| `profit` | Display a summary of your profit/loss from close trades and some stats about your performance.
| `forceexit <trade_id> [order_type] [amount]` | Instantly exits the given trade (ignoring `minimum_roi`), using the given order type ("market" or "limit", uses your config setting if not specified), and the chosen amount (full sell if not specified).
| `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).
| `weekly <n>` | Shows profit or loss per week, over the last n days (n defaults to 4).
| `monthly <n>` | Shows profit or loss per month, over the last n days (n defaults to 3).
| `stats` | Display a summary of profit / loss reasons as well as average holding times.
| `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.
| `pair_candles` | Returns dataframe for a pair / timeframe combination while the bot is running. **Alpha**
| `pair_history` | Returns an analyzed dataframe for a given timerange, analyzed by a given strategy. **Alpha**
| `plot_config` | Get plot config from the strategy (or nothing if not configured). **Alpha**
| `strategies` | List strategies in strategy directory. **Alpha**
| `strategy <strategy>` | Get specific Strategy content. **Alpha**
| `available_pairs` | List available backtest data. **Alpha**
| `version` | Show version.
| `sysinfo` | Show information about the system load.
| `health` | Show bot health (last bot loop).
!!! Warning "Alpha status"
Endpoints labeled with *Alpha status* above may change at any time without notice.
Possible commands can be listed from the rest-client script using the `help` command.
``` bash
@@ -266,6 +216,14 @@ forceexit
health
Provides a quick health check of the running bot.
lock_add
Manually lock a specific pair
:param pair: Pair to lock
:param until: Lock until this date (format "2024-03-30 16:00:00Z")
:param side: Side to lock (long, short, *)
:param reason: Reason for the lock
locks
Return current locks
@@ -344,6 +302,19 @@ trades
:param limit: Limits trades to the X last trades. Max 500 trades.
:param offset: Offset by this amount of trades.
list_open_trades_custom_data
Return a dict containing open trades custom-datas
:param key: str, optional - Key of the custom-data
:param limit: Limits trades to X trades.
:param offset: Offset by this amount of trades.
list_custom_data
Return a dict containing custom-datas of a specified trade
:param trade_id: int - ID of the trade
:param key: str, optional - Key of the custom-data
version
Return the version of the bot.
@@ -353,6 +324,62 @@ whitelist
```
### Available endpoints
If you wish to call the REST API manually via another route, e.g. directly via `curl`, the table below shows the relevant URL endpoints and parameters.
All endpoints in the below table need to be prefixed with the base URL of the API, e.g. `http://127.0.0.1:8080/api/v1/` - so the command becomes `http://127.0.0.1:8080/api/v1/<command>`.
| Endpoint | Method | Description / Parameters |
|-----------|--------|--------------------------|
| `/ping` | GET | Simple command testing the API Readiness - requires no authentication.
| `/start` | POST | Starts the trader.
| `/stop` | POST | Stops the trader.
| `/stopbuy` | POST | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
| `/reload_config` | POST | Reloads the configuration file.
| `/trades` | GET | List last trades. Limited to 500 trades per call.
| `/trade/<tradeid>` | GET | Get specific trade.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/trades/<tradeid>` | DELETE | Remove trade from the database. Tries to close open orders. Requires manual handling of this trade on the exchange.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/trades/<tradeid>/open-order` | DELETE | Cancel open order for this trade.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/trades/<tradeid>/reload` | POST | Reload a trade from the Exchange. Only works in live, and can potentially help recover a trade that was manually sold on the exchange.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/show_config` | GET | Shows part of the current configuration with relevant settings to operation.
| `/logs` | GET | Shows last log messages.
| `/status` | GET | Lists all open trades.
| `/count` | GET | Displays number of trades used and available.
| `/entries` | GET | Shows profit statistics for each enter tags for given pair (or all pairs if pair isn't given). Pair is optional.<br/>*Params:*<br/>- `pair` (`str`)
| `/exits` | GET | Shows profit statistics for each exit reasons for given pair (or all pairs if pair isn't given). Pair is optional.<br/>*Params:*<br/>- `pair` (`str`)
| `/mix_tags` | GET | Shows profit statistics for each combinations of enter tag + exit reasons for given pair (or all pairs if pair isn't given). Pair is optional.<br/>*Params:*<br/>- `pair` (`str`)
| `/locks` | GET | Displays currently locked pairs.
| `/locks` | POST | Locks a pair until "until". (Until will be rounded up to the nearest timeframe). Side is optional and is either `long` or `short` (default is `long`). Reason is optional.<br/>*Params:*<br/>- `<pair>` (`str`)<br/>- `<until>` (`datetime`)<br/>- `[side]` (`str`)<br/>- `[reason]` (`str`)
| `/locks/<lockid>` | DELETE | Deletes (disables) the lock by id.<br/>*Params:*<br/>- `lockid` (`int`)
| `/profit` | GET | Display a summary of your profit/loss from close trades and some stats about your performance.
| `/forceexit` | POST | Instantly exits the given trade (ignoring `minimum_roi`), using the given order type ("market" or "limit", uses your config setting if not specified), and the chosen amount (full sell if not specified). If `all` is supplied as the `tradeid`, then all currently open trades will be forced to exit.<br/>*Params:*<br/>- `<tradeid>` (`int` or `str`)<br/>- `<ordertype>` (`str`)<br/>- `[amount]` (`float`)
| `/forceenter` | POST | Instantly enters the given pair. Side is optional and is either `long` or `short` (default is `long`). Rate is optional. (`force_entry_enable` must be set to True)<br/>*Params:*<br/>- `<pair>` (`str`)<br/>- `<side>` (`str`)<br/>- `[rate]` (`float`)
| `/performance` | GET | Show performance of each finished trade grouped by pair.
| `/balance` | GET | Show account balance per currency.
| `/daily` | GET | Shows profit or loss per day, over the last n days (n defaults to 7).<br/>*Params:*<br/>- `<n>` (`int`)
| `/weekly` | GET | Shows profit or loss per week, over the last n days (n defaults to 4).<br/>*Params:*<br/>- `<n>` (`int`)
| `/monthly` | GET | Shows profit or loss per month, over the last n days (n defaults to 3).<br/>*Params:*<br/>- `<n>` (`int`)
| `/stats` | GET | Display a summary of profit / loss reasons as well as average holding times.
| `/whitelist` | GET | Show the current whitelist.
| `/blacklist` | GET | Show the current blacklist.
| `/blacklist` | POST | Adds the specified pair to the blacklist.<br/>*Params:*<br/>- `pair` (`str`)
| `/blacklist` | DELETE | Deletes the specified list of pairs from the blacklist.<br/>*Params:*<br/>- `[pair,pair]` (`list[str]`)
| `/edge` | GET | Show validated pairs by Edge if it is enabled.
| `/pair_candles` | GET | Returns dataframe for a pair / timeframe combination while the bot is running. **Alpha**
| `/pair_candles` | POST | Returns dataframe for a pair / timeframe combination while the bot is running, filtered by a provided list of columns to return. **Alpha**<br/>*Params:*<br/>- `<column_list>` (`list[str]`)
| `/pair_history` | GET | Returns an analyzed dataframe for a given timerange, analyzed by a given strategy. **Alpha**
| `/pair_history` | POST | Returns an analyzed dataframe for a given timerange, analyzed by a given strategy, filtered by a provided list of columns to return. **Alpha**<br/>*Params:*<br/>- `<column_list>` (`list[str]`)
| `/plot_config` | GET | Get plot config from the strategy (or nothing if not configured). **Alpha**
| `/strategies` | GET | List strategies in strategy directory. **Alpha**
| `/strategy/<strategy>` | GET | Get specific Strategy content by strategy class name. **Alpha**<br/>*Params:*<br/>- `<strategy>` (`str`)
| `/available_pairs` | GET | List available backtest data. **Alpha**
| `/version` | GET | Show version.
| `/sysinfo` | GET | Show information about the system load.
| `/health` | GET | Show bot health (last bot loop).
!!! Warning "Alpha status"
Endpoints labeled with *Alpha status* above may change at any time without notice.
### Message WebSocket
The API Server includes a websocket endpoint for subscribing to RPC messages from the freqtrade Bot.
@@ -30,12 +30,13 @@ The Order-type will be ignored if only one mode is available.
|----------|-------------|
| Binance | limit |
| Binance Futures | market, limit |
| Bingx | market, limit |
| HTX (former Huobi) | limit |
| Bingx | market, limit |
| HTX | limit |
| kraken | market, limit |
| Gate | limit |
| Okx | limit |
| Kucoin | stop-limit, stop-market|
| Hyperliquid (futures only) | limit |
!!! Note "Tight stoploss"
<ins>Do not set too low/tight stoploss value when using stop loss on exchange!</ins>
@@ -153,10 +154,10 @@ For example, simplified math:
In summary: The stoploss will be adjusted to be always be -10% of the highest observed price.
### Trailing stop loss, custom positive loss
### Trailing stop loss, different positive loss
You could also have a default stop loss when you are in the red with your buy (buy - fee), but once you hit a positive result (or an offset you define) the system will utilize a new stop loss, which can have a different value.
For example, your default stop loss is -10%, but once you have more than 0% profit (example 0.1%) a different trailing stoploss will be used.
You could also have a default stop loss when you are in the red with your buy (buy - fee), but once you hit a positive result (or an offset you define) the system will utilize a new stop loss, with a different value.
For example, your default stop loss is -10%, but once you have reached profitability (example 0.1%) a different trailing stoploss will be used.
!!! Note
If you want the stoploss to only be changed when you break even of making a profit (what most users want) please refer to next section with [offset enabled](#trailing-stop-loss-only-once-the-trade-has-reached-a-certain-offset).
@@ -207,7 +208,9 @@ Before this, `stoploss` is used for the trailing stoploss.
You can also keep a static stoploss until the offset is reached, and then trail the trade to take profits once the market turns.
If `trailing_only_offset_is_reached = True` then the trailing stoploss is only activated once the offset is reached. Until then, the stoploss remains at the configured `stoploss`.
If `trailing_only_offset_is_reached = True` then the trailing stoploss is only activated once the offset is reached. Until then, the stoploss remains at the configured `stoploss` and is not trailing.
Leaving this value as `trailing_only_offset_is_reached=False` will allow the trailing stoploss to start trailing as soon as the asset price increases above the initial entry price.
This option can be used with or without `trailing_stop_positive`, but uses `trailing_stop_positive_offset` as offset.
@@ -165,7 +165,8 @@ Called for open trade every iteration (roughly every 5 seconds) until a trade is
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), and is still mandatory.
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), and is still mandatory.
As custom stoploss acts as regular, changing stoploss, it will behave similar to `trailing_stop` - and trades exiting due to this will have the exit_reason of `"trailing_stop_loss"`.
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.
@@ -212,7 +213,7 @@ class AwesomeStrategy(IStrategy):
@@ -757,7 +758,7 @@ For performance reasons, it's disabled by default and freqtrade will show a warn
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.
This callback is also called when there is an open order (either buy or sell) waiting for execution - and will cancel the existing open order to place a new order if the amount, price or direction is different. Also partially filled orders will be canceled, and will be replaced with the new amount as returned by the callback.
`adjust_trade_position()` is called very frequently for the duration of a trade, so you must keep your implementation as performant as possible.
@@ -766,6 +767,23 @@ Adjustment orders can be assigned with a tag by returning a 2 element Tuple, wit
Modifications to leverage are not possible, and the stake-amount returned is assumed to be before applying leverage.
The combined stake currently allocated to the position is held in `trade.stake_amount`. Therefore `trade.stake_amount` will always be updated on every additional entry and partial exit made through `adjust_trade_position()`.
!!! Danger "Loose Logic"
On dry and live run, this function will be called every `throttle_process_secs` (default to 5s). If you have a loose logic, (e.g. increase position if RSI of the last candle is below 30), your bot will do extra re-entry every 5 secs until you either it run out of money, hit the `max_position_adjustment` limit, or a new candle with RSI more than 30 arrived.
Same thing also can happen with partial exit.
So be sure to have a strict logic and/or check for the last filled order and if an order is already open.
!!! Warning "Performance with many position adjustments"
Position adjustments can be a good approach to increase a strategy's output - but it can also have drawbacks if using this feature extensively.
Each of the orders will be attached to the trade object for the duration of the trade - hence increasing memory usage.
Trades with long duration and 10s or even 100ds of position adjustments are therefore not recommended, and should be closed at regular intervals to not affect performance.
!!! Warning "Backtesting"
During backtesting this callback is called for each candle in `timeframe` or `timeframe_detail`, so run-time performance will be affected.
This can also cause deviating results between live and backtesting, since backtesting can adjust the trade only once per candle, whereas live could adjust the trade multiple times per candle.
### Increase position
The strategy is expected to return a positive **stake_amount** (in stake currency) between `min_stake` and `max_stake` if and when an additional entry order should be made (position is increased -> buy order for long trades, sell order for short trades).
@@ -775,16 +793,22 @@ If there are not enough funds in the wallet (the return value is above `max_stak
Additional entries are ignored once you have reached the maximum amount of extra entries that you have set on `max_entry_position_adjustment`, but the callback is called anyway looking for partial exits.
!!! 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.
### Decrease position
The strategy is expected to return a negative stake_amount (in stake currency) for a partial exit.
Returning the full owned stake at that point (`-trade.stake_amount`) results in a full exit.
Returning a value more than the above (so remaining stake_amount would become negative) will result in the bot ignoring the signal.
!!! 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.
For a partial exit, it's important to know that the formula used to calculate the amount of the coin for the partial exit order is `amount to be exited partially = negative_stake_amount * trade.amount / trade.stake_amount`, where `negative_stake_amount` is the value returned from the `adjust_trade_position` function. As seen in the formula, the formula doesn't care about current profit/loss of the position. It only cares about `trade.amount` and `trade.stake_amount` which aren't affected by the price movement at all.
For example, let's say you buy 2 SHITCOIN/USDT at open rate of 50, which means the trade's stake amount is 100 USDT. Now the price raises to 200 and you want to sell half of it. In that case, you have to return -50% of `trade.stake_amount` (0.5 * 100 USDT) which equals to -50. The bot will calculate the amount it needed to sell, which is `50 * 2 / 100` which equals 1 SHITCOIN/USDT. If you return -200 (50% of 2 * 200), the bot will ignore it since `trade.stake_amount` is only 100 USDT but you asked to sell 200 USDT which means you are asking to sell 4 SHITCOIN/USDT.
Back to the example above, since current rate is 200, the current USDT value of your trade is now 400 USDT. Let's say you want to partially sell 100 USDT to take out the initial investment and leave the profit in the trade hoping that the price keeps rising. In that case, you have to do a different approach. First, you need to calculate the exact amount you needed to sell. In this case, since you want to sell 100 USDT worth based of current rate, the exact amount you need to partially sell is `100 * 2 / 400` which equals 0.5 SHITCOIN/USDT. Since we know now the exact amount we want to sell (0.5), the value you need to return in the `adjust_trade_position` function is `-amount to be exited partially * trade.stake_amount / trade.amount`, which equals -25. The bot will sell 0.5 SHITCOIN/USDT, keeping 1.5 in trade. You will receive 100 USDT from the partial exit.
!!! Warning "Stoploss calculation"
Stoploss is still calculated from the initial opening price, not averaged price.
@@ -792,15 +816,6 @@ Returning a value more than the above (so remaining stake_amount would become ne
While `/stopentry` 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 run-time performance will be affected.
This can also cause deviating results between live and backtesting, since backtesting can adjust the trade only once per candle, whereas live could adjust the trade multiple times per candle.
!!! Warning "Performance with many position adjustments"
Position adjustments can be a good approach to increase a strategy's output - but it can also have drawbacks if using this feature extensively.
Each of the orders will be attached to the trade object for the duration of the trade - hence increasing memory usage.
Trades with long duration and 10s or even 100ds of position adjustments are therefore not recommended, and should be closed at regular intervals to not affect performance.
``` python
# Default imports
@@ -820,8 +835,8 @@ class DigDeeperStrategy(IStrategy):
# This is called when placing the initial order (opening trade)
@@ -920,24 +938,25 @@ class DigDeeperStrategy(IStrategy):
The total profit for this trade was 950$ on a 3350$ investment (`100@8$ + 100@9$ + 150@11$`). As such - the final relative profit is 28.35% (`950 / 3350`).
## Adjust Entry Price
## Adjust order Price
The `adjust_entry_price()` callback may be used by strategy developer to refresh/replace limit orders upon arrival of new candles.
Be aware that `custom_entry_price()` is still the one dictating initial entry limit order price target at the time of entry trigger.
The `adjust_order_price()` callback may be used by strategy developer to refresh/replace limit orders upon arrival of new candles.
This callback is called once every iteration unless the order has been (re)placed within the current candle - limiting the maximum (re)placement of each order to once per candle.
This also means that the first call will be at the start of the next candle after the initial order was placed.
Be aware that `custom_entry_price()`/`custom_exit_price()` is still the one dictating initial limit order price target at the time of the signal.
Orders can be cancelled out of this callback by returning `None`.
Returning `current_order_rate` will keep the order on the exchange "as is".
Returning any other price will cancel the existing order, and replace it with a new order.
The trade open-date (`trade.open_date_utc`) will remain at the time of the very first order placed.
Please make sure to be aware of this - and eventually adjust your logic in other callbacks to account for this, and use the date of the first filled order instead.
If the cancellation of the original order fails, then the order will not be replaced - though the order will most likely have been canceled on exchange. Having this happen on initial entries will result in the deletion of the order, while on position adjustment orders, it'll result in the trade size remaining as is.
If the cancellation of the original order fails, then the order will not be replaced - though the order will most likely have been canceled on exchange. Having this happen on initial entries will result in the deletion of the order, while on position adjustment orders, it'll result in the trade size remaining as is.
If the order has been partially filled, the order will not be replaced. You can however use [`adjust_trade_position()`](#adjust-trade-position) to adjust the trade size to the expected position size, should this be necessary / desired.
!!! Warning "Regular timeout"
Entry `unfilledtimeout` mechanism (as well as `check_entry_timeout()`) takes precedence over this.
Entry Orders that are cancelled via the above methods will not have this callback called. Be sure to update timeout values to match your expectations.
Entry `unfilledtimeout` mechanism (as well as `check_entry_timeout()`/`check_exit_timeout()`) takes precedence over this callback.
Orders that are cancelled via the above methods will not have this callback called. Be sure to update timeout values to match your expectations.
```python
# Default imports
@@ -946,14 +965,26 @@ class AwesomeStrategy(IStrategy):
Entry price re-adjustment logic, returning the user desired limit price.
Exit and entry order price re-adjustment logic, returning the user desired limit price.
This only executes when a order was already placed, still open (unfilled fully or partially)
and not timed out on subsequent candles after entry trigger.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-callbacks/
When not implemented by a strategy, returns current_order_rate as default.
If current_order_rate is returned then the existing order is maintained.
If None is returned then order gets canceled but not replaced by a new one.
@@ -965,14 +996,16 @@ class AwesomeStrategy(IStrategy):
:param proposed_rate: Rate, calculated based on pricing settings in entry_pricing.
:param current_order_rate: Rate of the existing order in place.
: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 side: 'long' or 'short' - indicating the direction of the proposed trade
:param is_entry: True if the order is an entry order, False if it's an exit order.
: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 float or None: New entry price value if provided
"""
# Limit orders to use and follow SMA200 as price target for the first 10 minutes since entry trigger for BTC/USDT pair.
# Limit entry orders to use and follow SMA200 as price target for the first 10 minutes since entry trigger for BTC/USDT pair.
if (
pair == "BTC/USDT"
is_entry
and pair == "BTC/USDT"
and entry_tag == "long_sma200"
and side == "long"
and (current_time - timedelta(minutes=10)) <= trade.open_date_utc
@@ -989,6 +1022,26 @@ class AwesomeStrategy(IStrategy):
return current_order_rate
```
!!! danger "Incompatibility with `adjust_*_price()`"
If you have both `adjust_order_price()` and `adjust_entry_price()`/`adjust_exit_price()` implemented, only `adjust_order_price()` will be used.
If you need to adjust entry/exit prices, you can either implement the logic in `adjust_order_price()`, or use the split `adjust_entry_price()` / `adjust_exit_price()` callbacks, but not both.
Mixing these is not supported and will raise an error during bot startup.
### Adjust Entry Price
The `adjust_entry_price()` callback may be used by strategy developer to refresh/replace entry limit orders upon arrival.
It's a sub-set of `adjust_order_price()` and is called only for entry orders.
All remaining behavior is identical to `adjust_order_price()`.
The trade open-date (`trade.open_date_utc`) will remain at the time of the very first order placed.
Please make sure to be aware of this - and eventually adjust your logic in other callbacks to account for this, and use the date of the first filled order instead.
### Adjust Exit Price
The `adjust_exit_price()` callback may be used by strategy developer to refresh/replace exit limit orders upon arrival.
It's a sub-set of `adjust_order_price()` and is called only for exit orders.
All remaining behavior is identical to `adjust_order_price()`.
## Leverage Callback
When trading in markets that allow leverage, this method must return the desired Leverage (Defaults to 1 -> No leverage).
@@ -1003,7 +1056,7 @@ For markets / exchanges that don't support leverage, this method is ignored.
@@ -4,7 +4,7 @@ This page explains how to customize your strategies, add new indicators and set
If you haven't already, please familiarize yourself with:
- the [Freqtrade strategy 101](freqtrade-101.md), which provides a quick start to strategy development
- the [Freqtrade strategy 101](strategy-101.md), which provides a quick start to strategy development
- the [Freqtrade bot basics](bot-basics.md), which provides overall info on how the bot operates
## Develop your own strategy
@@ -513,7 +513,7 @@ By default, freqtrade will attempt to load strategies from all `.py` files withi
Assuming your strategy is called `AwesomeStrategy`, stored in the file `user_data/strategies/AwesomeStrategy.py`, then you can start freqtrade in dry (or live, depending on your configuration) mode with:
```bash
freqtrade trade --strategy AwesomeStrategy`
freqtrade trade --strategy AwesomeStrategy
```
Note that we're using the class name, not the file name.
@@ -545,7 +545,7 @@ def informative_pairs(self):
]
```
A full sample can be found [in the DataProvider section](#complete-data-provider-sample).
A full sample can be found [in the DataProvider section](#complete-dataprovider-sample).
!!! Warning
As these pairs will be refreshed as part of the regular whitelist refresh, it's best to keep this list short.
@@ -576,17 +576,20 @@ To easily define informative pairs, use the `@informative` decorator. All decora
and do not have access to data from other informative pairs. However, all informative dataframes for each pair are merged and passed to main `populate_indicators()` method.
!!! Note
Do not use the `@informative` decorator if you need to use data from one informative pair when generating another informative pair. Instead, define informative pairs manually as described [in the DataProvider section](#complete-data-provider-sample).
Do not use the `@informative` decorator if you need to use data from one informative pair when generating another informative pair. Instead, define informative pairs manually as described [in the DataProvider section](#complete-dataprovider-sample).
When hyperopting, use of the hyperoptable parameter `.value` attribute is not supported. Please use the `.range` attribute. See [optimizing an indicator parameter](hyperopt.md#optimizing-an-indicator-parameter) for more information.
A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
define informative indicators.
@@ -707,7 +710,7 @@ Options:
- Merge the dataframe without lookahead bias
- Forward-fill (optional)
For a full sample, please refer to the [complete data provider example](#complete-data-provider-sample) below.
For a full sample, please refer to the [complete data provider example](#complete-dataprovider-sample) below.
All columns of the informative dataframe will be available on the returning dataframe in a renamed fashion:
@@ -1119,6 +1122,7 @@ The following list contains some common patterns which should be avoided to prev
- don't use `.iloc[-1]` or any other absolute position in the dataframe within `populate_` functions, as this will be different between dry-run and backtesting. Absolute `iloc` indexing is safe to use in callbacks however - see [Strategy Callbacks](strategy-callbacks.md).
- don't use functions that use all dataframe or column values, e.g. `dataframe['mean_volume'] = dataframe['volume'].mean()`. As backtesting uses the full dataframe, at any point in the dataframe, the `'mean_volume'` series would include data from the future. Use rolling() calculations instead, e.g. `dataframe['volume'].rolling(<window>).mean()`.
- don't use `.resample('1h')`. This uses the left border of the period interval, so moves data from an hour boundary to the start of the hour. Use `.resample('1h', label='right')` instead.
- don't use `.merge()` to combine longer timeframes onto shorter ones. Instead, use the [informative pair](#informative-pairs) helpers. (A plain merge can implicitly cause a lookahead bias as date refers to open date, not close date).
!!! Tip "Identifying problems"
You should always use the two helper commands [lookahead-analysis](lookahead-analysis.md) and [recursive-analysis](recursive-analysis.md), which can each help you figure out problems with your strategy in different ways.
@@ -45,22 +45,55 @@ Get your "Id", you will use it for the config parameter `chat_id`.
#### Use Group id
You can use bots in telegram groups by just adding them to the group. You can find the group id by first adding a [RawDataBot](https://telegram.me/rawdatabot) to your group. The Group id is shown as id in the `"chat"` section, which the RawDataBot will send to you:
To get the group ID, you can add the bot to the group, start freqtrade, and issue a `/tg_info` command.
This will return the group id to you, without having to use some random bot.
While "chat_id" is still required, it doesn't need to be set to this particular group id for this command.
The response will also contain the "topic_id" if necessary - both in a format ready to copy/paste into your configuration.
``` json
"chat":{
"id":-1001332619709
{
"enabled": true,
"token": "********",
"chat_id": "-1001332619709",
"topic_id": "122"
}
```
For the Freqtrade configuration, you can then use the full value (including `-`if it's there) as string:
For the Freqtrade configuration, you can then use the full value (including `-` ) as string:
```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 unpleasant surprises.
##### Group Topic ID
To use a specific topic in a group, you can use the `topic_id` parameter in the configuration. This will allow you to use the bot in a specific topic in a group.
Without this, the bot will always respond to the general channel in the group if topics are enabled for a group chat.
```json
"chat_id": "-1001332619709",
"topic_id": "3"
```
Similar to the group-id - you can use `/tg_info` from the topic/thread to get the correct topic-id.
#### Authorized users
For groups, it can be useful to limit who can send commands to the bot.
If `"authorized_users": []` is present and empty, no user will be allowed to control the bot.
In the below example, only the user with the id "1234567" is allowed to control the bot - all other users will only be able to receive messages.
```json
"chat_id": "-1001332619709",
"topic_id": "3",
"authorized_users": ["1234567"]
```
## Control telegram noise
Freqtrade provides means to control the verbosity of your telegram bot.
@@ -93,9 +126,12 @@ Example configuration showing the different settings:
"trailing_stop_loss": "on",
"stop_loss": "on",
"stoploss_on_exchange": "on",
"custom_exit": "silent",
"partial_exit": "on"
"custom_exit": "silent", // custom_exit without specifying an exit reason
// "exit": "off", // Simplistic configuration to disable all exit messages
"exit_cancel": "on",
"exit_fill": "off",
"protection_trigger": "off",
@@ -108,16 +144,16 @@ Example configuration showing the different settings:
},
```
`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.
`strategy_msg` - Receive notifications from the strategy, sent via `self.dp.send_msg()` from the strategy [more details](strategy-customization.md#send-notification).
`show_candle` - show candle values as part of entry/exit messages. Only possible values are `"ohlc"` or `"off"`.
`balance_dust_level` will define what the `/balance` command takes as "dust" - Currencies with a balance below this will be shown.
`reload` allows you to disable reload-buttons on selected messages.
* `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.
Exit messages (`exit` and `exit_fill`) can be further controlled at individual exit reasons level, with the specific exit reason as the key. the default for all exit reasons is `on` - but can be configured via special `*` key - which will act as a wildcard for all exit reasons that are not explicitly defined.
* `*_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.
* `strategy_msg` - Receive notifications from the strategy, sent via `self.dp.send_msg()` from the strategy [more details](strategy-customization.md#send-notification).
* `show_candle` - show candle values as part of entry/exit messages. Only possible values are `"ohlc"` or `"off"`.
* `balance_dust_level` will define what the `/balance` command takes as "dust" - Currencies with a balance below this will be shown.
* `reload` allows you to disable reload-buttons on selected messages.
## Create a custom keyboard (command shortcut buttons)
@@ -238,16 +274,16 @@ Once all positions are sold, run `/stop` to completely stop the bot.
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
> **Direction:** Long
> **Leverage:** 1.0
> **Amount:**`26.64180098`
> **Enter Tag:** Awesome Long Signal
> **Open Rate:**`0.00007489`
> **Current Rate:**`0.00007489`
> **Unrealized Profit:**`12.95%`
> **Stoploss:**`0.00007389 (-0.02%)`
> **Trade ID:**`123``(since 1 days ago)`
> **Current Pair:** CVC/BTC
> **Direction:** Long
> **Leverage:** 1.0
> **Amount:**`26.64180098`
> **Enter Tag:** Awesome Long Signal
> **Open Rate:**`0.00007489`
> **Current Rate:**`0.00007489`
> **Unrealized Profit:**`12.95%`
> **Stoploss:**`0.00007389 (-0.02%)`
### /status table
@@ -274,34 +310,34 @@ current max
Return a summary of your profit/loss and performance.
> **ROI:** Close trades
> ∙ `0.00485701 BTC (2.2%) (15.2 Σ%)`
> ∙ `62.968 USD`
> **ROI:** All trades
> ∙ `0.00255280 BTC (1.5%) (6.43 Σ%)`
> ∙ `33.095 EUR`
>
> **Total Trade Count:**`138`
> **Bot started:**`2022-07-11 18:40:44`
> **First Trade opened:**`3 days ago`
> **Latest Trade opened:**`2 minutes ago`
> **Avg. Duration:**`2:33:45`
> **Best Performing:**`PAY/BTC: 50.23%`
> **Trading volume:**`0.5 BTC`
> **Profit factor:**`1.04`
> **Win / Loss:**`102 / 36`
> **Winrate:**`73.91%`
> **Expectancy (Ratio):**`4.87 (1.66)`
> **Max Drawdown:**`9.23% (0.01255 BTC)`
> **ROI:** Close trades
> ∙ `0.00485701 BTC (2.2%) (15.2 Σ%)`
> ∙ `62.968 USD`
> **ROI:** All trades
> ∙ `0.00255280 BTC (1.5%) (6.43 Σ%)`
> ∙ `33.095 EUR`
>
> **Total Trade Count:**`138`
> **Bot started:**`2022-07-11 18:40:44`
> **First Trade opened:**`3 days ago`
> **Latest Trade opened:**`2 minutes ago`
> **Avg. Duration:**`2:33:45`
> **Best Performing:**`PAY/BTC: 50.23%`
> **Trading volume:**`0.5 BTC`
> **Profit factor:**`1.04`
> **Win / Loss:**`102 / 36`
> **Winrate:**`73.91%`
> **Expectancy (Ratio):**`4.87 (1.66)`
> **Max Drawdown:**`9.23% (0.01255 BTC)`
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.
Profit Factor is calculated as gross profits / gross losses - and should serve as an overall metric for the strategy.
Expectancy corresponds to the average return per currency unit at risk, i.e. the winrate and the risk-reward ratio (the average gain of winning trades compared to the average loss of losing trades).
Expectancy Ratio is expected profit or loss of a subsequent trade based on the performance of all past trades.
Max drawdown corresponds to the backtesting metric `Absolute Drawdown (Account)` - calculated as `(Absolute Drawdown) / (DrawdownHigh + startingBalance)`.
Bot started date will refer to the date the bot was first started. For older bots, this will default to the first trade's open date.
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.
**Profit Factor** is calculated as gross profits / gross losses - and should serve as an overall metric for the strategy.
**Expectancy** corresponds to the average return per currency unit at risk, i.e. the winrate and the risk-reward ratio (the average gain of winning trades compared to the average loss of losing trades).
**Expectancy Ratio** is expected profit or loss of a subsequent trade based on the performance of all past trades.
**Max drawdown** corresponds to the backtesting metric `Absolute Drawdown (Account)` - calculated as `(Absolute Drawdown) / (DrawdownHigh + startingBalance)`.
**Bot started date** will refer to the date the bot was first started. For older bots, this will default to the first trade's open date.
### /forceexit <trade_id>
@@ -329,33 +365,36 @@ Note that for this to work, `force_entry_enable` needs to be set to true.
### /performance
Return the performance of each crypto-currency the bot has sold.
> Performance:
> 1. `RCN/BTC 0.003 BTC (57.77%) (1)`
> 2. `PAY/BTC 0.0012 BTC (56.91%) (1)`
> 3. `VIB/BTC 0.0011 BTC (47.07%) (1)`
> 4. `SALT/BTC 0.0010 BTC (30.24%) (1)`
> 5. `STORJ/BTC 0.0009 BTC (27.24%) (1)`
> ...
> Performance:
> 1. `RCN/BTC 0.003 BTC (57.77%) (1)`
> 2. `PAY/BTC 0.0012 BTC (56.91%) (1)`
> 3. `VIB/BTC 0.0011 BTC (47.07%) (1)`
> 4. `SALT/BTC 0.0010 BTC (30.24%) (1)`
> 5. `STORJ/BTC 0.0009 BTC (27.24%) (1)`
> ...
The relative performance is calculated against the total investment in the currency, aggregating all filled entries for the currency.
### /balance
Return the balance of all crypto-currency your have on the exchange.
> **Currency:** BTC
> **Available:** 3.05890234
> **Balance:** 3.05890234
> **Pending:** 0.0
> **Currency:** CVC
> **Available:** 86.64180098
> **Balance:** 86.64180098
> **Pending:** 0.0
> **Currency:** BTC
> **Available:** 3.05890234
> **Balance:** 3.05890234
> **Pending:** 0.0
>
> **Currency:** CVC
> **Available:** 86.64180098
> **Balance:** 86.64180098
> **Pending:** 0.0
### /daily <n>
Per default `/daily` will return the 7 last days. The example below if for `/daily 3`:
> **Daily Profit over the last 3 days:**
```
Day (count) USDT USD Profit %
-------------- ------------ ---------- ----------
@@ -370,6 +409,7 @@ Per default `/weekly` will return the 8 last weeks, including the current week.
from Monday. The example below if for `/weekly 3`:
> **Weekly Profit over the last 3 weeks (starting from Monday):**
@@ -35,6 +35,7 @@ The following attributes / properties are available for each individual trade -
| `trade_direction` | "long" / "short" | Trade direction in text - long or short. |
| `nr_of_successful_entries` | int | Number of successful (filled) entry orders. |
| `nr_of_successful_exits` | int | Number of successful (filled) exit orders. |
| `has_open_orders` | boolean | Has the trade open orders (excluding stoploss orders). |
## Class methods
@@ -143,6 +144,7 @@ Most properties here can be None as they are dependent on the exchange response.
| `remaining` | float | Remaining amount |
| `cost` | float | Cost of the order - usually average * filled (*Exchange dependent on futures, may contain the cost with or without leverage and may be in contracts.*) |
| `stake_amount` | float | Stake amount used for this order. *Added in 2023.7.* |
| `stake_amount_filled` | float | Filled Stake amount used for this order. *Added in 2024.11.* |
| `order_date` | datetime | Order creation date **use `order_date_utc` instead** |
| `order_date_utc` | datetime | Order creation date (in UTC) |
| `order_fill_date` | datetime | Order fill date **use `order_fill_utc` instead** |
--reset Reset sample files to their original state.
```
--8<-- "commands/create-userdir.md"
!!! Warning
Using `--reset` may result in loss of data, since this will overwrite all sample files without asking again.
@@ -38,15 +30,7 @@ optional arguments:
Creates a new configuration file, asking some questions which are important selections for a configuration.
```
usage: freqtrade new-config [-h] [-c PATH]
optional arguments:
-h, --help show this help message and exit
-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.
```
--8<-- "commands/new-config.md"
!!! Warning
Only vital questions are asked. Freqtrade offers a lot more configuration possibilities, which are listed in the [Configuration documentation](configuration.md#configuration-parameters)
@@ -73,21 +57,7 @@ Especially useful with [split configuration files](configuration.md#multiple-con
Specify strategy class name which will be used by the
bot.
--template {full,minimal,advanced}
Use a template which is either `minimal`, `full`
(containing multiple sample indicators) or `advanced`.
Default: `full`.
```
--8<-- "commands/new-strategy.md"
### Sample usage of new-strategy
@@ -162,38 +116,7 @@ Use the `list-strategies` subcommand to see all strategies in one particular dir
This subcommand is useful for finding problems in your environment with loading strategies: modules with strategies that contain errors and failed to load are printed in red (LOAD FAILED), while strategies with duplicate names are printed in yellow (DUPLICATE NAME).
--no-color Disable colorization of hyperopt results. May be
useful if you are redirecting output to a file.
--recursive-strategy-search
Recursively search for a strategy in the strategies
folder.
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.
```
--8<-- "commands/list-strategies.md"
!!! Warning
Using these commands will try to load all python files from a directory. This can be a security risk if untrusted files reside in this directory, since all module-level code is executed.
@@ -224,36 +147,7 @@ It provides a quick list of all available loss functions in your environment.
This subcommand can be useful for finding problems in your environment with loading loss functions: modules with Hyperopt-Loss functions that contain errors and failed to load are printed in red (LOAD FAILED), while hyperopt-Loss functions with duplicate names are printed in yellow (DUPLICATE NAME).
--hyperopt-path PATH Specify additional lookup path for Hyperopt Loss
functions.
-1, --one-column Print output in one column.
--no-color Disable colorization of hyperopt results. May be
useful if you are redirecting output to a file.
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
--logfile FILE, --log-file 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, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
```
--8<-- "commands/list-hyperoptloss.md"
## List freqAI models
@@ -261,49 +155,13 @@ Use the `list-freqaimodels` subcommand to see all freqAI models available.
This subcommand is useful for finding problems in your environment with loading freqAI models: modules with models that contain errors and failed to load are printed in red (LOAD FAILED), while models with duplicate names are printed in yellow (DUPLICATE NAME).
Please refer to the [corresponding documentation](advanced-setup.md#use-a-different-database-system) to learn about requirements for different database systems.
-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.
```
--8<-- "commands/webserver.md"
### Webserver mode - docker
@@ -609,37 +338,7 @@ Adding `--show-pair-list` outputs a sorted pair list you can easily copy/paste i
??? 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.
"--days and --timerange are mutually exclusive. You can only specify one or the other."
)
if"pairs"notinconfig:
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