65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
# --- Do not remove these libs ---
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from freqtrade.strategy.interface import IStrategy
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from pandas import DataFrame
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# --------------------------------
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import talib.abstract as ta
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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class AverageStrategy(IStrategy):
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"""
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author@: Gert Wohlgemuth
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idea:
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buys and sells on crossovers - doesn't really perfom that well and its just a proof of concept
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"""
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# Minimal ROI designed for the strategy.
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# This attribute will be overridden if the config file contains "minimal_roi"
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minimal_roi = {
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"0": 0.5
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}
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# Optimal stoploss designed for the strategy
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# This attribute will be overridden if the config file contains "stoploss"
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stoploss = -0.2
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# Optimal timeframe for the strategy
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timeframe = '4h'
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe['maShort'] = ta.EMA(dataframe, timeperiod=8)
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dataframe['maMedium'] = ta.EMA(dataframe, timeperiod=21)
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return dataframe
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def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Based on TA indicators, populates the buy signal for the given dataframe
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:param dataframe: DataFrame
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:return: DataFrame with buy column
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"""
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dataframe.loc[
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(
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qtpylib.crossed_above(dataframe['maShort'], dataframe['maMedium'])
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),
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'buy'] = 1
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return dataframe
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def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Based on TA indicators, populates the sell signal for the given dataframe
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:param dataframe: DataFrame
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:return: DataFrame with buy column
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"""
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dataframe.loc[
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(
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qtpylib.crossed_above(dataframe['maMedium'], dataframe['maShort'])
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),
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'sell'] = 1
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return dataframe
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