# ══════════════════════════════════════════════════════════════ # anis solidscale - Elite Spot Trading Suite # STRATEGIE : CCIMomentumTrendLite # CATEGORIE : Momentum — CCI Deviation (Simplifie) # ══════════════════════════════════════════════════════════════ # Version simplifiee de CCIMomentumTrend : # - 2 params : cci_period (buy) + cci_exit (sell) # - cci_entry=100, ema=50, persistence=2 fixes # ══════════════════════════════════════════════════════════════ 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 CCIMomentumTrendLite(IStrategy): INTERFACE_VERSION = 3 can_short = False timeframe = "4h" startup_candle_count = 80 minimal_roi = {"0": 0.10, "240": 0.05, "720": 0.03, "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 # ── Hyperopt params (1 buy + 1 sell) ── cci_period = IntParameter(14, 30, default=20, space="buy") cci_exit = IntParameter(-20, 20, default=0, space="sell") # ── Params fixes ── CCI_ENTRY = 100 EMA_PERIOD = 50 PERSISTENCE = 2 _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="CCIMomentumTrendLite") self._notifier = TelegramNotifier() def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: self._init_utils() for p in range(self.cci_period.low, self.cci_period.high + 1): dataframe = CommonIndicators.add_cci(dataframe, period=p) dataframe = CommonIndicators.add_ema(dataframe, period=self.EMA_PERIOD) dataframe = CommonIndicators.add_volume_sma(dataframe, period=20) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: cci_col = f"cci_{self.cci_period.value}" ema_col = f"ema_{self.EMA_PERIOD}" # CCI > CCI_ENTRY pendant PERSISTENCE bougies consecutives cci_above = dataframe[cci_col] > self.CCI_ENTRY for i in range(1, self.PERSISTENCE): cci_above = cci_above & (dataframe[cci_col].shift(i) > self.CCI_ENTRY) conditions = ( cci_above & (dataframe["close"] > dataframe[ema_col]) & (dataframe["volume"] > dataframe["volume_sma_20"]) & (dataframe["volume"] > 0) ) dataframe.loc[conditions, "enter_long"] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: cci_col = f"cci_{self.cci_period.value}" conditions = dataframe[cci_col] < self.cci_exit.value dataframe.loc[conditions, "exit_long"] = 1 return dataframe