84 lines
2.2 KiB
Python
84 lines
2.2 KiB
Python
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# --- Do not remove these libs ---
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from freqtrade.strategy.interface import IStrategy
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from typing import Dict, List
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from functools import reduce
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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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class MACDStrategy(IStrategy):
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"""
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author@: Gert Wohlgemuth
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idea:
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uptrend definition:
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MACD above MACD signal
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and CCI < -50
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downtrend definition:
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MACD below MACD signal
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and CCI > 100
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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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"60": 0.01,
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"30": 0.03,
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"20": 0.04,
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"0": 0.05
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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 = -0.3
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# Optimal timeframe for the strategy
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timeframe = '5m'
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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macd = ta.MACD(dataframe)
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dataframe['macd'] = macd['macd']
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dataframe['macdsignal'] = macd['macdsignal']
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dataframe['macdhist'] = macd['macdhist']
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dataframe['cci'] = ta.CCI(dataframe)
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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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(dataframe['macd'] > dataframe['macdsignal']) &
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(dataframe['cci'] <= -50.0)
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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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(dataframe['macd'] < dataframe['macdsignal']) &
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(dataframe['cci'] >= 100.0)
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),
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'sell'] = 1
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return dataframe
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