# source: https://raw.githubusercontent.com/RoboticAutomations/freqtradestrategies/52c4bd40414645f079a980cf4486dc7af4061efb/AIRA%20-%20open%20code%20v2/strategies/rsi-momentum/mk2.py # directory_url: https://github.com/RoboticAutomations/freqtradestrategies/blob/main/AIRA - open code v2/strategies/rsi-momentum/ # User: RoboticAutomations # Repository: freqtradestrategies # --------------------import numpy as np import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib from pandas import DataFrame from datetime import datetime from typing import Optional from freqtrade.persistence import Trade from freqtrade.strategy.interface import IStrategy from freqtrade.strategy import ( IStrategy, IntParameter ) class Github_RoboticAutomations_freqtradestrategies__mk2__20260915_233254(IStrategy): INTERFACE_VERSION = 3 timeframe = '5m' can_short = True process_only_new_candles = True use_custom_exit = True minimal_roi = { "0": 0.128, "16": 0.102, "31": 0.078, "46": 0.046, "61": 0.038, } stoploss = -0.213 trailing_stop = True trailing_stop_positive = 0.035 trailing_stop_positive_offset = 0.128 trailing_only_offset_is_reached = True max_stake_per_trade = 100 max_portfolio_percentage_per_trade = 0.05 max_entry_position_adjustment = 3 process_only_new_candles = True max_dca_orders = 3 max_total_stake_per_pair = 250 max_single_dca_amount = 50 buy_params = { "rsi_entry_long": 41, "rsi_entry_short": 59, "window": 24, } sell_params = { "rsi_exit_long": 17, "rsi_exit_short": 83, } max_open_trades = 20 rsi_entry_long = IntParameter(0, 100, default=buy_params.get('rsi_entry_long'), space='buy', optimize=True) rsi_exit_long = IntParameter(0, 100, default=sell_params.get('rsi_exit_long'), space='sell', optimize=True) rsi_entry_short = IntParameter(0, 100, default=buy_params.get('rsi_entry_short'), space='buy', optimize=True) rsi_exit_short = IntParameter(0, 100, default=sell_params.get('rsi_exit_short'), space='sell', optimize=True) window = IntParameter(5, 100, default=buy_params.get('window'), space='buy', optimize=False) def leverage(self, pair: str, current_time: datetime, current_rate: float, proposed_leverage: float, max_leverage: float, side: str, **kwargs) -> float: return 5 @property def protections(self): return [{ "method": "CooldownPeriod", "stop_duration_candles": 12, "protection_per_coin": True }] @property def plot_config(self): return { 'main_plot': { 'ema_fast': {'color': 'orange'}, 'ema_slow': {'color': 'pink'}, 'ema_long': {'color': 'blue'}, 'rsi_ema': {}, }, 'subplots': { 'MACD': { 'macd': {'color': 'orange'}, 'macdsignal': {'color': 'pink'}, }, 'Misc': { 'rsi': {}, 'rsi_gra': {}, 'mom': {}, 'plus_di': {}, 'minus_di': {}, }, } } def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14) dataframe['rsi_ema'] = dataframe['rsi'].ewm(span=self.window.value).mean() dataframe['rsi_gra'] = np.gradient(dataframe['rsi_ema']) dataframe['ema_fast'] = ta.EMA(dataframe, timeperiod=12) dataframe['ema_slow'] = ta.EMA(dataframe, timeperiod=26) dataframe['ema_long'] = ta.EMA(dataframe, timeperiod=100) macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9) dataframe['macd'] = macd['macd'] dataframe['macdsignal'] = macd['macdsignal'] dataframe['macd_golden_cross'] = qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal']).astype(int) dataframe['macd_dead_cross'] = qtpylib.crossed_below(dataframe['macd'], dataframe['macdsignal']).astype(int) # 保留DI和动量指标计算（出场信号仍可能用） dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=14) dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=14) dataframe['mom'] = ta.MOM(dataframe, timeperiod=10) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['macd_slope'] = np.gradient(dataframe['macd']) # 多头开仓：保留RSI和梯度判断，增加MACD斜率判断和macd 0) & (dataframe['macd'] < dataframe['macdsignal']) ) dataframe.loc[cond_long, 'enter_long'] = 1 # 空头开仓：保留RSI和梯度判断，增加MACD斜率判断和macd>macdsignal（死叉前），去掉EMA和DI判断，保留mom判断 cond_short = ( (dataframe['rsi'] > self.rsi_entry_short.value) & qtpylib.crossed_below(dataframe['rsi_gra'], 0) & (dataframe['macd_slope'] < 0) & (dataframe['macd'] > dataframe['macdsignal']) ) dataframe.loc[cond_short, 'enter_short'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['exit_long'] = 0 dataframe['exit_short'] = 0 dataframe.loc[ ( (dataframe['rsi'] > self.rsi_exit_long.value) & qtpylib.crossed_below(dataframe['rsi_gra'], 0) & (dataframe['low'] < dataframe['low'].rolling(window=20).min()) ), 'exit_long' ] = 1 dataframe.loc[ ( (dataframe['rsi'] < self.rsi_exit_short.value) & qtpylib.crossed_above(dataframe['rsi_gra'], 0) & (dataframe['high'] > dataframe['high'].rolling(window=20).max()) ), 'exit_short' ] = 1 return dataframe def custom_exit( self, pair: str, trade: Trade, current_time: datetime, current_rate: float, current_profit: float, **kwargs ) -> Optional[str]: dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) if dataframe is None or len(dataframe) < 1: return None last_candle = dataframe.iloc[-1] opened_at = trade.open_date_utc df_since_entry = dataframe[dataframe['date'] >= opened_at] if trade.trade_direction == 'long': had_golden_cross = df_since_entry['macd_golden_cross'].sum() > 0 if ( had_golden_cross and last_candle['macdsignal'] > last_candle['macd'] and last_candle['ema_slow'] > last_candle['ema_fast'] and last_candle['rsi'] < 36 ): return "exit_long_custom" if trade.trade_direction == 'short': had_dead_cross = df_since_entry['macd_dead_cross'].sum() > 0 if ( had_dead_cross and last_candle['macd'] > last_candle['macdsignal'] and last_candle['ema_fast'] > last_candle['ema_slow'] and last_candle['rsi'] > 64 ): return "exit_short_custom" return None