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docs: Update "tag" examples with advanced examples

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Matthias
2025-07-05 08:56:10 +02:00
parent 5f4184536a
commit e98f3cfedf
1 changed files with 36 additions and 13 deletions
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49
docs/strategy-advanced.md
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@@ -174,17 +174,27 @@ class AwesomeStrategy(IStrategy):
## Enter Tag ## Enter Tag
When your strategy has multiple buy signals, you can name the signal that triggered. When your strategy has multiple entry signals, you can name the signal that triggered.
Then you can access your buy signal on `custom_exit` Then you can access your entry signal on `custom_exit`
```python ```python
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe["enter_tag"] = ""
signal_rsi = (qtpylib.crossed_above(dataframe["rsi"], 35))
signal_bblower = (dataframe["bb_lowerband"] < dataframe["close"])
# Additional conditions
dataframe.loc[ dataframe.loc[
( (
(dataframe['rsi'] < 35) & signal_rsi
(dataframe['volume'] > 0) | signal_bblower
), # ... additional signals to enter a long position
['enter_long', 'enter_tag']] = (1, 'buy_signal_rsi') )
& (dataframe["volume"] > 0)
, "enter_long"
] = 1
# Concatenate the tags so all signals are kept
dataframe.loc[signal_rsi, "enter_tag"] += "long_signal_rsi "
dataframe.loc[signal_bblower, "enter_tag"] += "long_signal_bblower "
return dataframe return dataframe
@@ -192,8 +202,11 @@ def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_r
current_profit: float, **kwargs): current_profit: float, **kwargs):
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
last_candle = dataframe.iloc[-1].squeeze() last_candle = dataframe.iloc[-1].squeeze()
if trade.enter_tag == 'buy_signal_rsi' and last_candle['rsi'] > 80: if "long_signal_rsi" in trade.enter_tag and last_candle["rsi"] > 80:
return 'sell_signal_rsi' return "exit_signal_rsi"
if "long_signal_bblower" in trade.enter_tag and last_candle["high"] > last_candle["bb_upperband"]:
return "exit_signal_bblower"
# ...
return None return None
``` ```
@@ -213,17 +226,27 @@ Similar to [Entry Tagging](#enter-tag), you can also specify an exit tag.
``` python ``` python
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe["exit_tag"] = ""
rsi_exit_signal = (dataframe["rsi"] > 70)
ema_exit_signal = (dataframe["ema20"] < dataframe["ema50"])
# Additional conditions
dataframe.loc[ dataframe.loc[
( (
(dataframe['rsi'] > 70) & rsi_exit_signal
(dataframe['volume'] > 0) | ema_exit_signal
), # ... additional signals to exit a long position
['exit_long', 'exit_tag']] = (1, 'exit_rsi') ) &
(dataframe["volume"] > 0)
,
"exit_long"] = 1
# Concatenate the tags so all signals are kept
dataframe.loc[rsi_exit_signal, "exit_tag"] += "exit_signal_rsi "
dataframe.loc[rsi_exit_signal2, "exit_tag"] += "exit_signal_rsi "
return dataframe return dataframe
``` ```
The provided exit-tag is then used as sell-reason - and shown as such in backtest results. The provided exit-tag is then used as exit-reason - and shown as such in backtest results.
!!! Note !!! Note
`exit_reason` is limited to 100 characters, remaining data will be truncated. `exit_reason` is limited to 100 characters, remaining data will be truncated.