# source: https://raw.githubusercontent.com/Danson77/Freqtrade_AIO_UI/f0bf29851d0577f244c17c0aa7d593ba3a7f3551/user_data/backtest_reports/Registerd_with_100USDT/ElliotV5HOMod2/ElliotV5HOMod2.py # directory_url: https://github.com/Danson77/Freqtrade_AIO_UI/blob/main/user_data/backtest_reports/Registerd_with_100USDT/ElliotV5HOMod2/ # User: Danson77 # Repository: Freqtrade_AIO_UI # --------------------# --- Do not remove these libs --- from freqtrade.strategy.interface import IStrategy from pandas import DataFrame import talib.abstract as ta import numpy as np import freqtrade.vendor.qtpylib.indicators as qtpylib from freqtrade.strategy import DecimalParameter, IntParameter # -------------------------------- def EWO(dataframe: DataFrame, ema_length: int = 5, ema2_length: int = 35) -> DataFrame: """ Elliot Wave Oscillator (EWO) = (EMA(fast) - EMA(slow)) / close * 100 """ ema1 = ta.EMA(dataframe["close"], timeperiod=int(ema_length)) ema2 = ta.EMA(dataframe["close"], timeperiod=int(ema2_length)) return (ema1 - ema2) / dataframe["close"] * 100 class Github_Danson77_Freqtrade_AIO_UI__ElliotV5HOMod2__20260520_191933(IStrategy): """ Fixed / cleaned for your current intent: - No informative timeframe overhead (removed, since unused). - No EMA precompute loops (massive speed + RAM win). - Entry logic unchanged. - Exit signal logic kept but DISABLED by default (use_exit_signal=False), so it cannot hurt. - Plot columns maintained. """ can_short = False # ROI / risk (kept) minimal_roi = { "0": 0.05, "40": 0.04, "201": 0.03 } ignore_roi_if_entry_signal = False stoploss = -0.25 use_custom_stoploss = False trailing_stop = True trailing_stop_positive = 0.001 trailing_stop_positive_offset = 0.01 trailing_only_offset_is_reached = True use_entry_signal = True # You are explicitly running on ROI+trailing+stoploss exits: use_exit_signal = False exit_profit_only = False exit_profit_offset = 0.03 timeframe = "5m" process_only_new_candles = False startup_candle_count = 200 order_types = { "entry": "market", "exit": "market", "trailing_stop_loss": "market", "emergency_exit": "market", "force_entry": "market", "force_exit": "market", "stoploss": "market", "stoploss_on_exchange": False, "stoploss_on_exchange_interval": 60, "stoploss_on_exchange_limit_ratio": 0.99, } order_time_in_force = {"entry": "gtc", "exit": "gtc"} plot_config = { "main_plot": { "ma_buy": {"color": "orange"}, "ma_sell": {"color": "orange"}, } } @property def protections(self): return [ {"method": "CooldownPeriod", "stop_duration_candles": 5}, { "method": "MaxDrawdown", "lookback_period_candles": 72, # 6h on 5m "trade_limit": 20, "stop_duration_candles": 6, # 30m "max_allowed_drawdown": 0.03, }, { "method": "StoplossGuard", "lookback_period_candles": 48, # 4h "trade_limit": 4, "stop_duration_candles": 4, # 20m "only_per_pair": False, }, { "method": "LowProfitPairs", "lookback_period_candles": 24, # 2h "trade_limit": 2, "stop_duration_candles": 12, # 1h "required_profit": 0.02, }, { "method": "LowProfitPairs", "lookback_period_candles": 144, # 12h "trade_limit": 4, "stop_duration_candles": 24, # 2h "required_profit": 0.04, }, ] # -------- Parameters (keep ranges, but compute only what we use) -------- fast_ewo = 50 slow_ewo = 200 enable_opt_buy = True base_nb_candles_buy = IntParameter(5, 80, default=19, space="buy", optimize=enable_opt_buy) ewo_high = DecimalParameter(2.0, 12.0, default=5.417, space="buy", optimize=enable_opt_buy) ewo_low = DecimalParameter(-20.0, -8.0, default=-17.251, space="buy", optimize=enable_opt_buy) low_offset = DecimalParameter(0.9, 0.99, default=0.983, space="buy", optimize=enable_opt_buy) rsi_buy = IntParameter(30, 70, default=61, space="buy", optimize=enable_opt_buy) # These sell params are only useful if you later enable use_exit_signal=True base_nb_candles_sell = IntParameter(5, 80, default=24, space="sell", optimize=False) high_offset = DecimalParameter(0.99, 1.1, default=1.011, space="sell", optimize=False) # ---------------------------------------------------------------------- def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # Only compute the EMA periods actually used right now (FAST + clean) buy_len = int(self.base_nb_candles_buy.value) sell_len = int(self.base_nb_candles_sell.value) dataframe["ma_buy"] = ta.EMA(dataframe["close"], timeperiod=buy_len) dataframe["ma_sell"] = ta.EMA(dataframe["close"], timeperiod=sell_len) dataframe["EWO"] = EWO(dataframe, self.fast_ewo, self.slow_ewo) dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14) dataframe["rsi_fast"] = ta.RSI(dataframe, timeperiod=4) dataframe["rsi_slow"] = ta.RSI(dataframe, timeperiod=20) dataframe["hma_50"] = qtpylib.hull_moving_average(dataframe["close"], window=50) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe["enter_long"] = 0 dataframe["enter_tag"] = None ma_buy = dataframe["ma_buy"] cond_high = ( (dataframe["close"] < ma_buy * self.low_offset.value) & (dataframe["EWO"] > self.ewo_high.value) & (dataframe["rsi"] < self.rsi_buy.value) & (dataframe["volume"] > 0) ) cond_low = ( (dataframe["close"] < ma_buy * self.low_offset.value) & (dataframe["EWO"] < self.ewo_low.value) & (dataframe["rsi"] < self.rsi_buy.value) & (dataframe["volume"] > 0) ) dataframe.loc[cond_high, ["enter_long", "enter_tag"]] = [1, "ewo_high"] dataframe.loc[cond_low, ["enter_long", "enter_tag"]] = [1, "ewo_low"] return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Kept for debugging / future toggling. NOTE: Disabled unless you set use_exit_signal = True. """ dataframe["exit_long"] = 0 dataframe["exit_tag"] = None ma_sell = dataframe["ma_sell"] exit_tp_rollover = ( (dataframe["close"] > ma_sell * self.high_offset.value) & (dataframe["rsi_fast"] < dataframe["rsi_slow"]) & (dataframe["rsi"] > 50) & (dataframe["volume"] > 0) ) dataframe.loc[exit_tp_rollover, ["exit_long", "exit_tag"]] = [1, "tp_rollover"] return dataframe