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add doc for custom exit price

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axel 2021-08-05 18:16:16 -04:00
parent 84d082033b
commit 0985b11267
1 changed files with 16 additions and 6 deletions
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docs/strategy-advanced.md
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@ -357,13 +357,13 @@ See [Dataframe access](#dataframe-access) for more information about dataframe u
--- ---
## Custom order entry price rules ## Custom order price rules
By default, freqtrade use the orderbook to automatically set an order price, you also have the option to create custom order prices based on your strategy. By default, freqtrade use the orderbook to automatically set an order price, you also have the option to create custom order prices based on your strategy.
You can use this feature by setting the `use_custom_entry_price` option to `true` in config and creating a custom_entry_price function. You can use this feature by creating a custom_entry_price function in your strategy file to customize entry prices and custom_exit_price for exits.
### Custom order entry price exemple ### Custom order entry and exit price exemple
``` python ``` python
from datetime import datetime, timedelta, timezone from datetime import datetime, timedelta, timezone
from freqtrade.persistence import Trade from freqtrade.persistence import Trade
@ -373,13 +373,23 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods # ... populate_* methods
def custom_entry_price(self, pair: str, current_time: datetime, def custom_entry_price(self, pair: str, current_time: datetime,
proposed_rate, **kwargs) -> float: proposed_rate, **kwargs) -> float:
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair, dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
timeframe=self.timeframe) timeframe=self.timeframe)
entryprice = dataframe['bollinger_10_lowerband'].iat[-1] proposed_entryprice = dataframe['bollinger_10_lowerband'].iat[-1]
return entryprice return proposed_entryprice
def custom_exit_price(self, pair: str, trade: Trade,
current_time: datetime, proposed_rate: float,
current_profit: float, **kwargs) -> float:
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
timeframe=self.timeframe)
proposed_exitprice = dataframe['bollinger_10_upperband'].iat[-1]
return proposed_exitprice
``` ```