from freqtrade.strategy.interface import IStrategy from typing import Dict, List from functools import reduce from pandas import DataFrame import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib from typing import Dict, List from functools import reduce from pandas import DataFrame, DatetimeIndex, merge import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib import numpy # noqa class ClucMay72018_2(IStrategy): """ author@: Gert Wohlgemuth works on new objectify branch! """ minimal_roi = { "0": 0.01 } stoploss = -0.05 ticker_interval = '5m' def populate_indicators(self, dataframe: DataFrame) -> DataFrame: dataframe['rsi'] = ta.RSI(dataframe, timeperiod=5) rsiframe = DataFrame(dataframe['rsi']).rename(columns={'rsi': 'close'}) dataframe['emarsi'] = ta.EMA(rsiframe, timeperiod=5) macd = ta.MACD(dataframe) dataframe['macd'] = macd['macd'] dataframe['adx'] = ta.ADX(dataframe) bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) dataframe['bb_lowerband'] = bollinger['lower'] dataframe['bb_middleband'] = bollinger['mid'] dataframe['bb_upperband'] = bollinger['upper'] dataframe['ema100'] = ta.EMA(dataframe, timeperiod=50) return dataframe def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame: """ Based on TA indicators, populates the buy signal for the given dataframe :param dataframe: DataFrame :return: DataFrame with buy column """ dataframe.loc[ ( (dataframe['close'] < dataframe['ema100']) & (dataframe['close'] < 0.985 * dataframe['bb_lowerband']) & (dataframe['volume'] < (dataframe['volume'].rolling(window=30).mean().shift(1) * 20)) ), 'buy'] = 1 return dataframe def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame: """ Based on TA indicators, populates the sell signal for the given dataframe :param dataframe: DataFrame :return: DataFrame with buy column """ dataframe.loc[ ( (dataframe['close'] > dataframe['bb_middleband']) ), 'sell'] = 1 return dataframe