# source: https://raw.githubusercontent.com/sisxmax/Freqtrade-Strategy-Library/e1315c78f00c4d813217ced1e7bc9f8364d3a06d/Ichimoku.py # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # flake8: noqa: F401 # isort: skip_file # --- Do not remove these imports --- import numpy as np import pandas as pd from datetime import datetime, timedelta, timezone from pandas import DataFrame from typing import Dict, Optional, Union, Tuple, List from freqtrade.optimize.space import Categorical, Dimension, Integer, SKDecimal from freqtrade.strategy import ( IStrategy, Trade, Order, PairLocks, informative, # @informative decorator # Hyperopt Parameters BooleanParameter, CategoricalParameter, DecimalParameter, IntParameter, RealParameter, # timeframe helpers timeframe_to_minutes, timeframe_to_next_date, timeframe_to_prev_date, # Strategy helper functions merge_informative_pair, stoploss_from_absolute, stoploss_from_open, ) # -------------------------------- # Add your lib to import here import talib.abstract as ta import pandas_ta as pta from technical import qtpylib from technical.indicators import ichimoku # ========================================== # Ultimate Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247 Cloud Strategy [2944% Profit Backtest] # YouTube Link: https://youtu.be/EumlRRIx0WA # ========================================== # ================================ # Download Historical Data # ================================ """ freqtrade download-data \ -c user_data/binance_futures_Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247.json \ --timerange 20220101- \ -t 5m 15m 30m 1h 4h 1d """ # ================================ # Lookahead Analysis # ================================ """ freqtrade lookahead-analysis \ --strategy Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247 \ --timeframe 4h \ --timerange 20230101-20240501 \ -c user_data/binance_futures_Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247.json \ --max-open-trades 1 \ -p AVAX/USDT:USDT """ # ================================ # Hyperopt Optimization # ================================ """ freqtrade hyperopt \ --strategy Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247 \ --config user_data/binance_futures_Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247.json \ --timeframe 4h \ --timerange 20230101-20240501 \ --hyperopt-loss MultiMetricHyperOptLoss \ --spaces buy\ -e 50 \ --j -2 \ --random-state 9319 \ --min-trades 20 \ -p AVAX/USDT:USDT \ --max-open-trades 1 \ --analyze-per-epoch """ # ================================ # Backtesting # ================================ """ freqtrade backtesting \ --strategy Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247 \ --timeframe 4h \ --timerange 20230101-20250101 \ --breakdown month \ -c user_data/binance_futures_Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247.json \ --max-open-trades 1 \ -p AVAX/USDT:USDT \ --cache none \ --timeframe-detail 30m """ # ================================ # Start FreqUI Web Interface # ================================ """ freqtrade webserver \ --config user_data/config_binance_futures.json """ class Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247(IStrategy): # Strategy interface version - allow new iterations of the strategy interface. # Check the documentation or the Sample strategy to get the latest version. INTERFACE_VERSION = 3 # Optimal timeframe for the strategy. timeframe = "4h" # Can this strategy go short? can_short: bool = True # Minimal ROI designed for the strategy. # This attribute will be overridden if the config file contains "minimal_roi". minimal_roi = {} # Optimal stoploss designed for the strategy. # This attribute will be overridden if the config file contains "stoploss". stoploss = -0.25 # Trailing stoploss trailing_stop = False # trailing_only_offset_is_reached = False # trailing_stop_positive = 0.01 # trailing_stop_positive_offset = 0.0 # Disabled / not configured # Run "populate_indicators()" only for new candle. process_only_new_candles = True # These values can be overridden in the config. use_exit_signal = True exit_profit_only = False ignore_roi_if_entry_signal = False # Number of candles the strategy requires before producing valid signals startup_candle_count: int = 200 conversion_line_periods = IntParameter(5, 15, default=9, space="buy") base_line_periods = IntParameter(20, 35, default=26, space="buy") atr_mult = CategoricalParameter([1.5, 2, 2.5, 3], default=2.5, space="buy") converstion_cross_rolling_window = CategoricalParameter([3, 6, 9, 12, 15], default=6, space="buy") leverage_level = IntParameter(1, 10, default=1, space='buy', optimize=False, load=False) @property def plot_config(self): plot_config = { 'main_plot': { f'conversion_line_{self.conversion_line_periods.value}_{self.base_line_periods.value}': {'color': 'rgb(41, 98, 255)', 'style': 'line', 'width': 2}, f'base_line_{self.conversion_line_periods.value}_{self.base_line_periods.value}': {'color': 'rgb(183, 28, 28)', 'style': 'line', 'width': 2}, f'upper_{self.conversion_line_periods.value}_{self.base_line_periods.value}': { 'color': 'rgb(165, 214, 167)', 'fill_to': f'lower_{self.conversion_line_periods.value}_{self.base_line_periods.value}', 'fill_label': 'Github_sisxmax_Freqtrade_Strategy_Library__Ichimoku__20260316_095247 Cloud', 'fill_color': 'rgba(67, 160, 71, 0.1)', }, f'lower_{self.conversion_line_periods.value}_{self.base_line_periods.value}': { 'color': 'rgb(239, 154, 154)', }, } } return plot_config def informative_pairs(self): """ Define additional, informative pair/interval combinations to be cached from the exchange. These pair/interval combinations are non-tradeable, unless they are part of the whitelist as well. For more information, please consult the documentation :return: List of tuples in the format (pair, interval) Sample: return [("ETH/USDT", "5m"), ("BTC/USDT", "15m"), ] """ # get access to all pairs available in whitelist. # pairs = self.dp.current_whitelist() # # Assign tf to each pair so they can be downloaded and cached for strategy. # informative_pairs = [(pair, self.informative_timeframe) for pair in pairs] return [] def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: for conversion_line_val in self.conversion_line_periods.range: for base_line_val in self.base_line_periods.range: ichi = ichimoku(dataframe, conversion_line_period=conversion_line_val, base_line_periods=base_line_val) dataframe[f'conversion_line_{conversion_line_val}_{base_line_val}'] = ichi['tenkan_sen'] dataframe[f'base_line_{conversion_line_val}_{base_line_val}'] = ichi['kijun_sen'] dataframe[f'upper_{conversion_line_val}_{base_line_val}'] = np.maximum(ichi['senkou_span_a'], ichi['senkou_span_b']) dataframe[f'lower_{conversion_line_val}_{base_line_val}'] = np.minimum(ichi['senkou_span_a'], ichi['senkou_span_b']) # ATR dataframe["atr"] = ta.ATR(dataframe) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: conversion_line_val = self.conversion_line_periods.value base_line_val = self.base_line_periods.value dataframe.loc[ ( (dataframe[f'conversion_line_{conversion_line_val}_{base_line_val}'] > dataframe[f'base_line_{conversion_line_val}_{base_line_val}']) & (dataframe['close'] > dataframe[f'upper_{conversion_line_val}_{base_line_val}']) & (dataframe[f'conversion_line_{conversion_line_val}_{base_line_val}'] >= dataframe[f'conversion_line_{conversion_line_val}_{base_line_val}'].shift(1)) & (dataframe[f'base_line_{conversion_line_val}_{base_line_val}'] >= dataframe[f'base_line_{conversion_line_val}_{base_line_val}'].shift(1)) & # Checks if conversion line crossed above the base line within the specified rolling window (dataframe[f'conversion_line_{conversion_line_val}_{base_line_val}'].rolling(window=self.converstion_cross_rolling_window.value).apply( lambda x: any(qtpylib.crossed_above(x, dataframe[f'base_line_{conversion_line_val}_{base_line_val}'].iloc[x.index[0]:x.index[-1]+1]))) ) & (dataframe['volume'] > 0) ), 'enter_long'] = 1 dataframe.loc[ ( (dataframe[f'conversion_line_{conversion_line_val}_{base_line_val}'] < dataframe[f'base_line_{conversion_line_val}_{base_line_val}']) & (dataframe['close'] < dataframe[f'lower_{conversion_line_val}_{base_line_val}']) & (dataframe[f'conversion_line_{conversion_line_val}_{base_line_val}'] <= dataframe[f'conversion_line_{conversion_line_val}_{base_line_val}'].shift(1)) & (dataframe[f'base_line_{conversion_line_val}_{base_line_val}'] <= dataframe[f'base_line_{conversion_line_val}_{base_line_val}'].shift(1)) & # Checks if conversion line crossed below the base line within the specified rolling window (dataframe[f'conversion_line_{conversion_line_val}_{base_line_val}'].rolling(window=self.converstion_cross_rolling_window.value).apply( lambda x: any(qtpylib.crossed_below(x, dataframe[f'base_line_{conversion_line_val}_{base_line_val}'].iloc[x.index[0]:x.index[-1]+1]))) ) & (dataframe['volume'] > 0) ), 'enter_short'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: conversion_line_val = self.conversion_line_periods.value base_line_val = self.base_line_periods.value exit_threshold = dataframe['atr'] * self.atr_mult.value dataframe.loc[ ( (qtpylib.crossed_below(dataframe['close'], (dataframe[f'base_line_{conversion_line_val}_{base_line_val}'] - exit_threshold))) & (dataframe['volume'] > 0) ), 'exit_long'] = 1 dataframe.loc[ ( (qtpylib.crossed_above(dataframe['close'], (dataframe[f'base_line_{conversion_line_val}_{base_line_val}'] + exit_threshold))) & (dataframe['volume'] > 0) ), 'exit_short'] = 1 return dataframe def leverage(self, pair: str, current_time: datetime, current_rate: float, proposed_leverage: float, max_leverage: float, side: str, **kwargs) -> float: return self.leverage_level.value