import numpy as np # noqa import pandas as pd # noqa from pandas import DataFrame from freqtrade.strategy.interface import IStrategy import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib from technical.util import resample_to_interval, resampled_merge from freqtrade.strategy import IStrategy, merge_informative_pair from technical.indicators import ichimoku class Ichimoku_v31_Heikin(IStrategy): minimal_roi = { "0": 100 } stoploss = -0.99 timeframe = '1h' inf_tf = '4h' process_only_new_candles = True use_sell_signal = True sell_profit_only = False ignore_roi_if_buy_signal = True startup_candle_count = 150 order_types = { 'buy': 'market', 'sell': 'market', 'stoploss': 'market', 'stoploss_on_exchange': False } def informative_pairs(self): if not self.dp: return [] pairs = self.dp.current_whitelist() informative_pairs = [(pair, '4h') for pair in pairs] return informative_pairs def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: if not self.dp: return dataframe dataframe_inf = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe=self.inf_tf) heikinashi = qtpylib.heikinashi(dataframe_inf) dataframe_inf['ha_open'] = heikinashi['open'] dataframe_inf['ha_close'] = heikinashi['close'] dataframe_inf['ha_high'] = heikinashi['high'] dataframe_inf['ha_low'] = heikinashi['low'] ha_ichi = ichimoku(heikinashi, conversion_line_period=20, base_line_periods=60, laggin_span=120, displacement=30 ) dataframe_inf['senkou_a'] = ha_ichi['senkou_span_a'] dataframe_inf['senkou_b'] = ha_ichi['senkou_span_b'] dataframe_inf['cloud_green'] = ha_ichi['cloud_green'] dataframe_inf['cloud_red'] = ha_ichi['cloud_red'] dataframe = merge_informative_pair(dataframe, dataframe_inf, self.timeframe, self.inf_tf, ffill=True) """ Senkou Span A > Senkou Span B = Cloud Green Senkou Span B > Senkou Span A = Cloud Red """ return dataframe def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( ((dataframe['ha_close_4h'].crossed_above(dataframe['senkou_a_4h'])) & (dataframe['ha_close_4h'].shift() < (dataframe['senkou_a_4h'])) & (dataframe['cloud_green_4h'] == True)) | ((dataframe['ha_close_4h'].crossed_above(dataframe['senkou_b_4h'])) & (dataframe['ha_close_4h'].shift() < (dataframe['senkou_b_4h'])) & (dataframe['cloud_red_4h'] == True)) ), 'buy'] = 1 return dataframe def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['ha_close_4h'] < dataframe['senkou_a_4h']) | (dataframe['ha_close_4h'] < dataframe['senkou_b_4h']) ), 'sell'] = 1 return dataframe