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@@ -6,7 +6,7 @@ This guide walks you through utilizing public trade data for advanced orderflow
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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).
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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).
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!!! Warning "Performance"
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!!! Warning "Performance"
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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. It can also cause increased memory usage. Please ensure you have sufficient resources available.
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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.
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## Getting Started
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## Getting Started
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@@ -44,12 +44,13 @@ This guide walks you through utilizing public trade data for advanced orderflow
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To download historical trade data for backtesting, use the --dl-trades flag with the freqtrade download-data command.
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To download historical trade data for backtesting, use the --dl-trades flag with the freqtrade download-data command.
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```bash
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```bash
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freqtrade download-data -p BTC/USDT:USDT --timerange 20230101- --trading-mode futures --timeframes 5m --dl-trades
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freqtrade download-data -p BTC/USDT:USDT --timerange 20230101- --trading-mode futures --timeframes 5m --dl-trades
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```
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```
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## Accessing Orderflow Data
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## Accessing Orderflow Data
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Once activated, several new columns become available in your dataframe:
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Once activated, several new columns become available in your dataframe:
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``` python
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``` python
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dataframe["trades"] # Contains information about each individual trade.
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dataframe["trades"] # Contains information about each individual trade.
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@@ -94,5 +95,4 @@ The `orderflow` dataframe includes columns like:
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- `total_volume`: Total volume (ask amount + bid amount) at each price level.
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- `total_volume`: Total volume (ask amount + bid amount) at each price level.
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- `total_trades`: Total number of trades (ask + bid) at each price level.
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- `total_trades`: Total number of trades (ask + bid) at each price level.
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By leveraging these features, you can gain valuable insights into market sentiment and potential trading opportunities based on order flow analysis.
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By leveraging these features, you can gain valuable insights into market sentiment and potential trading opportunities based on order flow analysis.
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