115 lines
4.6 KiB
Python
115 lines
4.6 KiB
Python
"""
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Supertrend strategy:
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* Description: Generate a 3 supertrend indicators based on different pairs for [period, multiplier] -> [period: 10, multiplier: 1], [period: 11, multiplier: 2], [period: 13, multiplier: 3]
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Buys if the 3 indicators are 'up'
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Sells if the 3 indicators are 'down'
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* Author: @juankysoriano (Juan Carlos Soriano)
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* github: https://github.com/juankysoriano/
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"""
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import logging
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from numpy.lib import math
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from freqtrade.strategy.interface import IStrategy
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from freqtrade.strategy.hyper import IntParameter
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from pandas import DataFrame
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import talib.abstract as ta
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import numpy as np
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class Supertrend(IStrategy):
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# ROI table:
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minimal_roi = {
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"0": 0.087,
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"372": 0.058,
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"861": 0.029,
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"2221": 0
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}
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# Stoploss:
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stoploss = -0.265
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# Trailing stop:
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trailing_stop = True
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trailing_stop_positive = 0.05
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trailing_stop_positive_offset = 0.144
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trailing_only_offset_is_reached = False
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timeframe = '1h'
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startup_candle_count = 10
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe['supertrend_1'] = self.supertrend(dataframe, 1, 10)['STX']
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dataframe['supertrend_2'] = self.supertrend(dataframe, 2, 11)['STX']
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dataframe['supertrend_3'] = self.supertrend(dataframe, 3, 12)['STX']
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return dataframe
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def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe.loc[
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(
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(dataframe['supertrend_1'] == 'up') &
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(dataframe['supertrend_2'] == 'up') &
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(dataframe['supertrend_3'] == 'up') & # The three indicators are 'up' for the current candle
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(dataframe['volume'] > 0) # There is at least some trading volume
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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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dataframe.loc[
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(
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(dataframe['supertrend_1'] == 'down') &
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(dataframe['supertrend_2'] == 'down') &
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(dataframe['supertrend_3'] == 'down') & # The three indicators are 'down' for the current candle
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(dataframe['volume'] > 0) # There is at least some trading volume
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),
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'sell'] = 1
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return dataframe
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"""
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Supertrend Indicator; adapted for freqtrade
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from: https://github.com/freqtrade/freqtrade-strategies/issues/30
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"""
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def supertrend(self, dataframe: DataFrame, multiplier, period):
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df = dataframe.copy()
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df['TR'] = ta.TRANGE(df)
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df['ATR'] = ta.SMA(df['TR'], period)
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st = 'ST_' + str(period) + '_' + str(multiplier)
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stx = 'STX_' + str(period) + '_' + str(multiplier)
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# Compute basic upper and lower bands
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df['basic_ub'] = (df['high'] + df['low']) / 2 + multiplier * df['ATR']
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df['basic_lb'] = (df['high'] + df['low']) / 2 - multiplier * df['ATR']
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# Compute final upper and lower bands
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df['final_ub'] = 0.00
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df['final_lb'] = 0.00
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for i in range(period, len(df)):
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df['final_ub'].iat[i] = df['basic_ub'].iat[i] if df['basic_ub'].iat[i] < df['final_ub'].iat[i - 1] or df['close'].iat[i - 1] > df['final_ub'].iat[i - 1] else df['final_ub'].iat[i - 1]
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df['final_lb'].iat[i] = df['basic_lb'].iat[i] if df['basic_lb'].iat[i] > df['final_lb'].iat[i - 1] or df['close'].iat[i - 1] < df['final_lb'].iat[i - 1] else df['final_lb'].iat[i - 1]
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# Set the Supertrend value
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df[st] = 0.00
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for i in range(period, len(df)):
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df[st].iat[i] = df['final_ub'].iat[i] if df[st].iat[i - 1] == df['final_ub'].iat[i - 1] and df['close'].iat[i] <= df['final_ub'].iat[i] else \
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df['final_lb'].iat[i] if df[st].iat[i - 1] == df['final_ub'].iat[i - 1] and df['close'].iat[i] > df['final_ub'].iat[i] else \
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df['final_lb'].iat[i] if df[st].iat[i - 1] == df['final_lb'].iat[i - 1] and df['close'].iat[i] >= df['final_lb'].iat[i] else \
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df['final_ub'].iat[i] if df[st].iat[i - 1] == df['final_lb'].iat[i - 1] and df['close'].iat[i] < df['final_lb'].iat[i] else 0.00
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# Mark the trend direction up/down
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df[stx] = np.where((df[st] > 0.00), np.where((df['close'] < df[st]), 'down', 'up'), np.NaN)
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# Remove basic and final bands from the columns
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df.drop(['basic_ub', 'basic_lb', 'final_ub', 'final_lb'], inplace=True, axis=1)
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df.fillna(0, inplace=True)
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return DataFrame(index=df.index, data={
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'ST' : df[st],
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'STX' : df[stx]
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})
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