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Merge pull request #9576 from freqtrade/simplify-freqai-example

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Make freqai example strat *even* simpler
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Matthias 2023-12-18 20:01:02 +01:00 committed by GitHub
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1 changed files with 5 additions and 18 deletions
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23
freqtrade/templates/FreqaiExampleStrategy.py
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@ -6,7 +6,7 @@ import talib.abstract as ta
from pandas import DataFrame
from technical import qtpylib
from freqtrade.strategy import CategoricalParameter, IStrategy
from freqtrade.strategy import IStrategy
logger = logging.getLogger(__name__)
@ -45,11 +45,6 @@ class FreqaiExampleStrategy(IStrategy):
startup_candle_count: int = 40
can_short = True
std_dev_multiplier_buy = CategoricalParameter(
[0.75, 1, 1.25, 1.5, 1.75], default=1.25, space="buy", optimize=True)
std_dev_multiplier_sell = CategoricalParameter(
[0.75, 1, 1.25, 1.5, 1.75], space="sell", default=1.25, optimize=True)
def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
metadata: Dict, **kwargs) -> DataFrame:
"""
@ -239,21 +234,13 @@ class FreqaiExampleStrategy(IStrategy):
dataframe = self.freqai.start(dataframe, metadata, self)
for val in self.std_dev_multiplier_buy.range:
dataframe[f'target_roi_{val}'] = (
dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * val
)
for val in self.std_dev_multiplier_sell.range:
dataframe[f'sell_roi_{val}'] = (
dataframe["&-s_close_mean"] - dataframe["&-s_close_std"] * val
)
return dataframe
def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
enter_long_conditions = [
df["do_predict"] == 1,
df["&-s_close"] > df[f"target_roi_{self.std_dev_multiplier_buy.value}"],
df["&-s_close"] > 0.01,
]
if enter_long_conditions:
@ -263,7 +250,7 @@ class FreqaiExampleStrategy(IStrategy):
enter_short_conditions = [
df["do_predict"] == 1,
df["&-s_close"] < df[f"sell_roi_{self.std_dev_multiplier_sell.value}"],
df["&-s_close"] < -0.01,
]
if enter_short_conditions:
@ -276,14 +263,14 @@ class FreqaiExampleStrategy(IStrategy):
def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
exit_long_conditions = [
df["do_predict"] == 1,
df["&-s_close"] < df[f"sell_roi_{self.std_dev_multiplier_sell.value}"] * 0.25,
df["&-s_close"] < 0
]
if exit_long_conditions:
df.loc[reduce(lambda x, y: x & y, exit_long_conditions), "exit_long"] = 1
exit_short_conditions = [
df["do_predict"] == 1,
df["&-s_close"] > df[f"target_roi_{self.std_dev_multiplier_buy.value}"] * 0.25,
df["&-s_close"] > 0
]
if exit_short_conditions:
df.loc[reduce(lambda x, y: x & y, exit_short_conditions), "exit_short"] = 1