# source: https://raw.githubusercontent.com/viktors1982/trading/93bc1627e6f0f212ecfb199073c214267da3b775/freqtrade/strategies/SuperIchi.py # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # flake8: noqa: F401 # --- Do not remove these libs --- import numpy as np # noqa import pandas as pd # noqa pd.options.mode.chained_assignment = None # default='warn' from pandas import DataFrame from freqtrade.strategy import IStrategy from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter # -------------------------------- # Add your lib to import here import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib from freqtrade.persistence import Trade, PairLocks import math import math import logging from datetime import datetime, timedelta, timezone from timeit import default_timer as timer from datetime import timedelta def funcgithub_viktors1982_trading__SuperIchi__20220317_121547(dtloc, source = 'close', length = 14, mult = 2): """ // This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) https://creativecommons.org/licenses/by-nc-sa/4.0/ // github_viktors1982_trading__SuperIchi__20220317_121547 [LUX] https://www.tradingview.com/script/vDGd9X9y-github_viktors1982_trading__SuperIchi__20220317_121547-LUX/ :return: avg translated for freqtrade: viksal1982 viktors.s@gmail.com """ dtfT = dtloc.copy() dtfT['TR'] = ta.TRANGE(dtfT) dtfT['ATR'] = dtfT['TR'].ewm(alpha=1 / length).mean() * mult dtfT['up'] = ((dtfT['high'] + dtfT['low']) / 2 ) + dtfT['ATR'] dtfT['dn'] = ((dtfT['high'] + dtfT['low']) / 2 ) - dtfT['ATR'] def calcFt(dfr, init=0): global calc_source global calc_upper global calc_lower global calc_os global calc_max global calc_min global calc_spt global calc_prev_spt if init == 1: calc_source = 0.0 calc_upper = 0.0 calc_lower = 0.0 calc_os = 0 calc_max = 0.0 calc_min = 9999999999999999.0 calc_spt = 0.0 calc_prev_spt = 0.0 return if calc_source < calc_upper: if dfr['up'] < calc_upper: calc_upper = dfr['up'] else: calc_upper = dfr['up'] if calc_source > calc_lower: if dfr['dn'] > calc_lower: calc_lower = dfr['dn'] else: calc_lower = dfr['dn'] if dfr[source] > calc_upper: calc_os = 1 elif dfr[source] < calc_lower: calc_os = 0 calc_prev_spt = calc_spt if calc_os == 1: calc_spt = calc_lower else: calc_spt = calc_upper is_crossed = False if dfr[source] > calc_prev_spt and dfr[source] < calc_spt: is_crossed = True if dfr[source] < calc_prev_spt and dfr[source] > calc_spt: is_crossed = True if is_crossed == True: if dfr[source] > calc_max: calc_max = dfr[source] elif calc_os == 1: if dfr[source] > calc_max: calc_max = dfr[source] else: calc_max = calc_spt if is_crossed == True: if dfr[source] < calc_min: calc_min = dfr[source] elif calc_os == 0: if dfr[source] < calc_min: calc_min = dfr[source] else: calc_min = calc_spt avg = (calc_max + calc_min)/2 calc_source = dfr[source] return avg, calc_min,calc_max,calc_spt,calc_os calcFt(None, init=1) dtfT[['calc_avg','calc_min', 'calc_max','calc_spt','calc_os']] = dtfT.apply(calcFt, axis = 1, result_type='expand') return dtfT['calc_avg'] class github_viktors1982_trading__SuperIchi__20220317_121547(IStrategy): INTERFACE_VERSION = 2 minimal_roi = { "0": 0.999 } stoploss = -0.99 # Trailing stoploss trailing_stop = False # Buy hyperspace params: buy_params = { "kijun_len_buy": 7, "kijun_mult_buy": 3, "tenkan_len_buy": 22, "tenkan_mult_buy": 1, } # Sell hyperspace params: sell_params = { "kijun_len_sell": 23, "kijun_mult_sell": 5, "tenkan_len_sell": 10, "tenkan_mult_sell": 3, } tenkan_len_buy = IntParameter(1, 30, default=buy_params['tenkan_len_buy'], space='buy', optimize=True) tenkan_mult_buy = IntParameter(1, 6, default=buy_params['tenkan_mult_buy'], space='buy', optimize=True) kijun_len_buy = IntParameter(1, 30, default=buy_params['kijun_len_buy'], space='buy', optimize=True) kijun_mult_buy = IntParameter(1, 6, default=buy_params['kijun_mult_buy'], space='buy', optimize=True) tenkan_len_sell = IntParameter(1, 30, default=sell_params['tenkan_len_sell'], space='sell', optimize=True) tenkan_mult_sell = IntParameter(1, 6, default=sell_params['tenkan_mult_sell'], space='sell', optimize=True) kijun_len_sell = IntParameter(1, 30, default=sell_params['kijun_len_sell'], space='sell', optimize=True) kijun_mult_sell = IntParameter(1, 6, default=sell_params['kijun_mult_sell'], space='sell', optimize=True) # Optimal timeframe for the strategy. timeframe = '5m' custom_3c_pairs = {} custom_main = {} # Run "populate_indicators()" only for new candle. process_only_new_candles = False # These values can be overridden in the "ask_strategy" section in the config. use_sell_signal = True sell_profit_only = False ignore_roi_if_buy_signal = False # Number of candles the strategy requires before producing valid signals startup_candle_count: int = 100 # Optional order type mapping. order_types = { 'buy': 'limit', 'sell': 'limit', 'stoploss': 'market', 'stoploss_on_exchange': False } # Optional order time in force. order_time_in_force = { 'buy': 'gtc', 'sell': 'gtc' } plot_config = { # Main plot indicators (Moving averages, ...) 'main_plot': { 'tenkan_b': {'color': 'red'}, 'kijun_b': {'color': 'blue'}, 'tenkan_s': {'color': 'yellow'}, 'kijun_s': {'color': 'black'} }, 'subplots': { } } def informative_pairs(self): return [] def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: if self.config['runmode'].value != 'hyperopt': dataframe['tenkan_b'] = funcgithub_viktors1982_trading__SuperIchi__20220317_121547(dataframe, source = 'close', length = self.tenkan_len_buy.value, mult = self.tenkan_mult_buy.value) dataframe['kijun_b'] = funcgithub_viktors1982_trading__SuperIchi__20220317_121547(dataframe, source = 'close', length = self.kijun_len_buy.value, mult = self.kijun_mult_buy.value) dataframe['Buy_s'] = np.where( ((dataframe['tenkan_b'] > dataframe['kijun_b']) & (dataframe['tenkan_b'].shift(1) < dataframe['kijun_b'].shift(1))),1,0) dataframe['tenkan_s'] = funcgithub_viktors1982_trading__SuperIchi__20220317_121547(dataframe, source = 'close', length = self.tenkan_len_sell.value, mult = self.tenkan_mult_sell.value) dataframe['kijun_s'] = funcgithub_viktors1982_trading__SuperIchi__20220317_121547(dataframe, source = 'close', length = self.kijun_len_sell.value, mult = self.kijun_mult_sell.value) dataframe['Sell_s'] = np.where( ((dataframe['tenkan_s'] < dataframe['kijun_s']) & (dataframe['tenkan_s'].shift(1) > dataframe['kijun_s'].shift(1))),1,0) return dataframe def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: if self.config['runmode'].value == 'hyperopt': dataframe['tenkan_b'] = funcgithub_viktors1982_trading__SuperIchi__20220317_121547(dataframe, source = 'close', length = self.tenkan_len_buy.value, mult = self.tenkan_mult_buy.value) dataframe['kijun_b'] = funcgithub_viktors1982_trading__SuperIchi__20220317_121547(dataframe, source = 'close', length = self.kijun_len_buy.value, mult = self.kijun_mult_buy.value) dataframe['Buy_s'] = np.where( ((dataframe['tenkan_b'] > dataframe['kijun_b']) & (dataframe['tenkan_b'].shift(1) < dataframe['kijun_b'].shift(1))),1,0) dataframe.loc[ ( ((dataframe['Buy_s'] == 1 )) & (dataframe['volume'] > 0) # Make sure Volume is not 0 ), 'buy'] = 1 return dataframe def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: if self.config['runmode'].value == 'hyperopt': dataframe['tenkan_s'] = funcgithub_viktors1982_trading__SuperIchi__20220317_121547(dataframe, source = 'close', length = self.tenkan_len_sell.value, mult = self.tenkan_mult_sell.value) dataframe['kijun_s'] = funcgithub_viktors1982_trading__SuperIchi__20220317_121547(dataframe, source = 'close', length = self.kijun_len_sell.value, mult = self.kijun_mult_sell.value) dataframe['Sell_s'] = np.where( ((dataframe['tenkan_s'] < dataframe['kijun_s']) & (dataframe['tenkan_s'].shift(1) > dataframe['kijun_s'].shift(1))),1,0) dataframe.loc[ ( (dataframe['Sell_s'] == 1 ) & (dataframe['volume'] > 0) # Make sure Volume is not 0 ), 'sell'] = 1 return dataframe