# ══════════════════════════════════════════════════════════════ # anis solidscale - Elite Spot Trading Suite # STRATEGIE : BollingerMACDReversal # CATEGORIE : Mean-reversion — BB + MACD Confirmation # ══════════════════════════════════════════════════════════════ # # LOGIQUE : # Combine un niveau extreme (BB lower) avec une confirmation # de retournement de momentum (MACD histogram rising). # 1. Close < BB lower (prix extreme bas) # 2. MACD histogram en hausse (2 bougies) # 3. RSI < seuil (oversold confirme) # 4. Volume > SMA volume # 5. Sortie : close >= BB middle OU RSI > seuil exit # ══════════════════════════════════════════════════════════════ import sys from pathlib import Path from pandas import DataFrame from freqtrade.strategy import IStrategy, IntParameter sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent)) from utils.indicators import CommonIndicators from utils.logging_utils import TradeLogger from utils.telegram_notifier import TelegramNotifier class BollingerMACDReversal(IStrategy): INTERFACE_VERSION = 3 can_short = False timeframe = "4h" startup_candle_count = 80 minimal_roi = {"0": 0.08, "240": 0.04, "720": 0.02, "1440": 0.01} stoploss = -0.06 trailing_stop = True trailing_stop_positive = 0.02 trailing_stop_positive_offset = 0.03 trailing_only_offset_is_reached = True # ── Buy params ── bb_period = IntParameter(15, 30, default=20, space="buy") rsi_period = IntParameter(7, 21, default=14, space="buy") rsi_entry = IntParameter(20, 45, default=40, space="buy") # ── Sell params ── rsi_exit = IntParameter(60, 80, default=70, space="sell") _logger = None _notifier = None def __getstate__(self): state = self.__dict__.copy() state["_logger"] = None state["_notifier"] = None return state def __setstate__(self, state): self.__dict__.update(state) def _init_utils(self) -> None: if self._logger is None: self._logger = TradeLogger(strategy_name="BollingerMACDReversal") self._notifier = TelegramNotifier() def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: self._init_utils() for p in range(self.bb_period.low, self.bb_period.high + 1): dataframe = CommonIndicators.add_bollinger_bands(dataframe, period=p) for p in range(self.rsi_period.low, self.rsi_period.high + 1): dataframe = CommonIndicators.add_rsi(dataframe, period=p) dataframe = CommonIndicators.add_macd(dataframe) dataframe = CommonIndicators.add_volume_sma(dataframe, period=20) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: bb_lower = f"bb_lower_{self.bb_period.value}" bb_middle = f"bb_middle_{self.bb_period.value}" rsi_col = f"rsi_{self.rsi_period.value}" # MACD histogram rising (1 bougie suffit — 2 bougies trop restrictif sur 3 paires 4h) macd_rising = ( dataframe["macd_histogram"] > dataframe["macd_histogram"].shift(1) ) # BB lower proximity (close dans les 1% de la bande basse — strict < trop rare sur 3 paires 4h) conditions = ( (dataframe["close"] <= dataframe[bb_lower] * 1.01) & macd_rising & (dataframe[rsi_col] < self.rsi_entry.value) & (dataframe["volume"] > 0) ) dataframe.loc[conditions, "enter_long"] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: bb_middle = f"bb_middle_{self.bb_period.value}" rsi_col = f"rsi_{self.rsi_period.value}" conditions = ( (dataframe["close"] >= dataframe[bb_middle]) | (dataframe[rsi_col] > self.rsi_exit.value) ) dataframe.loc[conditions, "exit_long"] = 1 return dataframe