# Source: generated via dynamic_strategy_generator from freqtrade.strategy import IStrategy from pandas import DataFrame import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib class ACO_67_3(IStrategy): timeframe = '1h' # Standard ROI and Stoploss minimal_roi = {"0": 0.1, "60": 0.05, "120": 0.0} stoploss = -0.05 def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['adx'] = ta.ADX(dataframe, timeperiod=14) res = ta.AROON(dataframe, timeperiod=10) dataframe['aroondown'] = res.iloc[:, 0] dataframe['aroonup'] = res.iloc[:, 1] dataframe['dema'] = ta.DEMA(dataframe, timeperiod=10) dataframe['natr'] = ta.NATR(dataframe, timeperiod=14) stochrsi = ta.STOCHRSI(dataframe, timeperiod=7, fastk_period=3, fastd_period=3) dataframe['fastk'] = stochrsi['fastk'] dataframe['fastd'] = stochrsi['fastd'] dataframe['apo'] = ta.APO(dataframe, fastperiod=12, slowperiod=26) dataframe['ppo'] = ta.PPO(dataframe, fastperiod=5, slowperiod=20) dataframe['sar'] = ta.SAR(dataframe, acceleration=0.03, maximum=0.3) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['adx'] > 25) ) & ( qtpylib.crossed_above(dataframe['aroonup'], dataframe['aroondown']) ) & ( qtpylib.crossed_above(dataframe['close'], dataframe['dema']) ) & ( (dataframe['natr'] > 2.0) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['fastk'] > 85) ) & ( qtpylib.crossed_below(dataframe['apo'], 0) ) & ( qtpylib.crossed_below(dataframe['apo'], 0) ) & ( qtpylib.crossed_below(dataframe['ppo'], 0) ) & ( qtpylib.crossed_below(dataframe['close'], dataframe['sar']) ), 'exit_long'] = 1 return dataframe