# source: https://raw.githubusercontent.com/Danson77/Freqtrade_AIO_UI/f0bf29851d0577f244c17c0aa7d593ba3a7f3551/user_data/backtest_reports/Registerd_with_100USDT/BearBull3/BearBull3.py # directory_url: https://github.com/Danson77/Freqtrade_AIO_UI/blob/main/user_data/backtest_reports/Registerd_with_100USDT/BearBull3/ # User: Danson77 # Repository: Freqtrade_AIO_UI # --------------------from freqtrade.strategy import stoploss_from_open, merge_informative_pair, DecimalParameter, IntParameter, CategoricalParameter from freqtrade.strategy import IStrategy, merge_informative_pair from pandas import DataFrame import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib from functools import reduce from freqtrade.persistence import Trade from datetime import datetime, timedelta # based on BinHV45 strategy: https://github.com/freqtrade/freqtrade-strategies/blob/master/user_data/strategies/berlinguyinca/BinHV45.py # use at own risk ######################################################################################################################################################## class Github_Danson77_Freqtrade_AIO_UI__BearBull3__20260520_191933(IStrategy): ######################################################################################################################################################## # Hyperopt ######################################################################################################################################################## buy_params = { "bbdelta_close": 0.023, "bbdelta_close_2": 0.05, "closedelta_close": 0.014, "closedelta_close_2": 0.003, "tail_bbdelta": 0.104, "tail_bbdelta_2": 0.21, } sell_params = { "base_nb_candles_sell": 16, "high_offset": 1.084, "high_offset_2": 1.401, } ######################################################################################################################################################## # Main ######################################################################################################################################################## can_short = False minimal_roi = { #"0": 0.15, } 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 use_exit_signal = True exit_profit_only = False exit_profit_offset = 0.03 ######################################################################################################################################################## # Main ######################################################################################################################################################## timeframe = '5m' informative = '1h' 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'}, # Color for the buy moving average. 'ma_sell': {'color': 'orange'}, # Color for the sell moving average. }, } ######################################################################################################################################################## # Trade Protections ######################################################################################################################################################## @property def protections(self): return [ # Cooldown any signal for 5 candles (25 m) after a trade { "method": "CooldownPeriod", "stop_duration_candles": 5 }, # Allow up to 3% drawdown over the last 9 h before pausing { "method": "MaxDrawdown", "lookback_period_candles": 72, # 6 h → 9 h "trade_limit": 20, "stop_duration_candles": 6, # longer pause "max_allowed_drawdown": 0.03 # 3% drawdown allowed }, # Only guard if you’ve lost >3% over a rolling 4 h period { "method": "StoplossGuard", "lookback_period_candles": 48, # 4 h "trade_limit": 4, "stop_duration_candles": 4, "only_per_pair": False }, # Prevent pairs that only net <2% profit over 2 h, block for 1 h { "method": "LowProfitPairs", "lookback_period_candles": 24, # 2 h "trade_limit": 2, "stop_duration_candles": 12, # 1 h "required_profit": 0.02 # 2% }, # Prevent pairs that only net <4% profit over 12 h, block for 2 h { "method": "LowProfitPairs", "lookback_period_candles": 144, # 12 h "trade_limit": 4, "stop_duration_candles": 24, # 2 h "required_profit": 0.04 # 4% } ] ######################################################################################################################################################## ######################################################################################################################################################## # Parameters ######################################################################################################################################################## ## Buy_params #is_optimize_buy1 = True #is_optimize_buy2 = True #bbdelta_close = DecimalParameter(0.004, 0.024, default=buy_params['bbdelta_close'], space='buy', optimize=is_optimize_buy1) #closedelta_close = DecimalParameter(0.001, 0.014, default=buy_params['closedelta_close'], space='buy', optimize=is_optimize_buy1) #tail_bbdelta = DecimalParameter(0.05, 0.30, default=buy_params['tail_bbdelta'], space='buy', optimize=is_optimize_buy1) #bbdelta_close_2 = DecimalParameter(0.010, 0.055, default=buy_params['bbdelta_close_2'], space='buy', optimize=is_optimize_buy2) #closedelta_close_2 = DecimalParameter(0.001, 0.015, default=buy_params['closedelta_close_2'], space='buy', optimize=is_optimize_buy2) #tail_bbdelta_2 = DecimalParameter(0.1, 0.4, default=buy_params['tail_bbdelta_2'], space='buy', optimize=is_optimize_buy2) ## Sell_params #is_optimize_sell = True #base_nb_candles_sell = IntParameter(2, 25, default=sell_params['base_nb_candles_sell'], space='sell', optimize=is_optimize_sell) #high_offset = DecimalParameter(0.95, 1.1, default=sell_params['high_offset'], space='sell', optimize=is_optimize_sell) #high_offset_2 = DecimalParameter(0.99, 1.5, default=sell_params['high_offset_2'], space='sell', optimize=is_optimize_sell) ## = IntParameter(5, 80, default=sell_params['base_nb_candles_sell'], space='sell', optimize=is_optimize_sell) ## = DecimalParameter(0.99, 1.1, default=sell_params['high_offset'], space='sell', optimize=is_optimize_sell) ## Unclog params (sell space – exits) #is_optimize_unclog = True #unclog_max_days = IntParameter(3, 30, default=10, space='sell', optimize=is_optimize_unclog) ## exit losers only below this profit threshold #unclog_min_profit = DecimalParameter(-0.20, 0.05, default=0.0, space='sell', optimize=is_optimize_unclog) is_optimize_buy1 = True is_optimize_buy2 = True is_optimize_sell = True is_optimize_unclog = True bbdelta_close = DecimalParameter(0.016, 0.030,# around 0.023 default=buy_params['bbdelta_close'], space='buy', optimize=is_optimize_buy1) closedelta_close = DecimalParameter(0.010, 0.020,# around 0.014 default=buy_params['closedelta_close'], space='buy', optimize=is_optimize_buy1) tail_bbdelta = DecimalParameter(0.08, 0.15,# around 0.104 default=buy_params['tail_bbdelta'], space='buy', optimize=is_optimize_buy1) bbdelta_close_2 = DecimalParameter(0.035, 0.065,# around 0.05 default=buy_params['bbdelta_close_2'], space='buy', optimize=is_optimize_buy2) closedelta_close_2 = DecimalParameter(0.0015, 0.0045,# around 0.003 default=buy_params['closedelta_close_2'], space='buy', optimize=is_optimize_buy2) tail_bbdelta_2 = DecimalParameter(0.16, 0.28,# around 0.21 default=buy_params['tail_bbdelta_2'], space='buy', optimize=is_optimize_buy2) base_nb_candles_sell = IntParameter(10, 24,# around 16 default=sell_params['base_nb_candles_sell'], space='sell', optimize=is_optimize_sell) high_offset = DecimalParameter(1.02, 1.14,# around 1.084 default=sell_params['high_offset'], space='sell', optimize=is_optimize_sell) high_offset_2 = DecimalParameter(1.25, 1.55,# around 1.401 default=sell_params['high_offset_2'], space='sell', optimize=is_optimize_sell) unclog_max_days = IntParameter(7, 18,# around 10 default=10, space='sell', optimize=is_optimize_unclog) unclog_min_profit = DecimalParameter(-0.08, 0.02,# small loss up to slight profit default=0.0, space='sell', optimize=is_optimize_unclog) ######################################################################################################################################################## # Infromative ######################################################################################################################################################## def informative_pairs(self): pairs = self.dp.current_whitelist() informative_pairs = [(pair, self.informative) for pair in pairs] return informative_pairs ######################################################################################################################################################## # Indicators ######################################################################################################################################################## def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # macd timeframe for trend detection (informative TF) inf_tf = self.informative # e.g. '1h' macd_df = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe=inf_tf) # Safety: if informative data missing, just skip (prevents crashes) if macd_df is None or macd_df.empty or 'close' not in macd_df.columns: dataframe['macdhist_' + inf_tf] = 0.0 else: macd_df['macdhist'] = ta.MACD(macd_df, fastperiod=10, slowperiod=20, signalperiod=10)['macdhist'] dataframe = merge_informative_pair(dataframe, macd_df, self.timeframe, inf_tf, ffill=True) # Calculate all ma_sell values for val in self.base_nb_candles_sell.range: dataframe[f'ma_sell_{val}'] = ta.EMA(dataframe, timeperiod=val) dataframe['sma_9'] = ta.SMA(dataframe, timeperiod=9) dataframe['hma_50'] = qtpylib.hull_moving_average(dataframe['close'], window=50) dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14) dataframe['rsi_slow'] = ta.RSI(dataframe, timeperiod=20) dataframe['rsi_fast'] = ta.RSI(dataframe, timeperiod=4) # normal timeframe bb = ta.BBANDS(dataframe, timeperiod=40, nbdevup=2.0, nbdevdn=2.0) dataframe['mid'] = bb['middleband'] dataframe['lower'] = bb['lowerband'] dataframe['bbdelta'] = (dataframe['mid'] - dataframe['lower']).abs() #dataframe['pricedelta'] = (dataframe['open'] - dataframe['close']).abs() dataframe['closedelta'] = (dataframe['close'] - dataframe['close'].shift()).abs() dataframe['tail'] = (dataframe['close'] - dataframe['low']).abs() return dataframe ######################################################################################################################################################## # Entry ######################################################################################################################################################## def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['enter_long'] = 0 dataframe['enter_tag'] = None bearish = ( (dataframe[f'macdhist_{self.informative}'] < 0) & (dataframe['lower'].shift() > 0) & (dataframe['bbdelta'] > dataframe['close'] * self.bbdelta_close.value) & (dataframe['closedelta'] > dataframe['close'] * self.closedelta_close.value) & (dataframe['tail'] < dataframe['bbdelta'] * self.tail_bbdelta.value) & (dataframe['close'] < dataframe['lower'].shift()) & (dataframe['close'] <= dataframe['close'].shift()) ) bullish = ( (dataframe[f'macdhist_{self.informative}'] > 0) & (dataframe['lower'].shift() > 0) & (dataframe['bbdelta'] > dataframe['close'] * self.bbdelta_close_2.value) & (dataframe['closedelta'] > dataframe['close'] * self.closedelta_close_2.value) & (dataframe['tail'] < dataframe['bbdelta'] * self.tail_bbdelta_2.value) & (dataframe['close'] < dataframe['lower'].shift()) & (dataframe['close'] <= dataframe['close'].shift()) ) entry_condition = (bearish | bullish) & (dataframe['volume'] > 0) dataframe.loc[entry_condition, ['enter_long', 'enter_tag']] = [1, 'macdhist'] return dataframe ######################################################################################################################################################## # Exit ######################################################################################################################################################## def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['exit_long'] = 0 dataframe['exit_tag'] = None exit_sma = ( (dataframe['close'] > dataframe['sma_9']) & (dataframe['close'] > (dataframe[f'ma_sell_{self.base_nb_candles_sell.value}'] * self.high_offset_2.value)) & (dataframe['rsi'] > 50) & (dataframe['volume'] > 0) & (dataframe['rsi_fast'] > dataframe['rsi_slow']) ) exit_hma = ( (dataframe['close'] < dataframe['hma_50']) & (dataframe['close'] > (dataframe[f'ma_sell_{self.base_nb_candles_sell.value}'] * self.high_offset.value)) & (dataframe['volume'] > 0) & (dataframe['rsi_fast'] > dataframe['rsi_slow']) & (dataframe['exit_long'] == 0) ) dataframe.loc[exit_sma, ['exit_long', 'exit_tag']] = [1, 'sma_9'] dataframe.loc[exit_hma, ['exit_long', 'exit_tag']] = [1, 'hma_50'] return dataframe ######################################################################################################################################################## # Custom to Sell unclog ######################################################################################################################################################## # def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float, current_profit: float, **kwargs): # # Sell any positions at a loss if they are held for more than X days. # # Hyperopted unclog parameters # max_days = int(self.unclog_max_days.value) # min_profit = float(self.unclog_min_profit.value) # # held_days = (current_time - trade.open_date_utc).days # # # If position is stuck longer than max_days and profit is below threshold, # # force-exit to unclog capital. # if held_days >= max_days and current_profit <= min_profit: # return 'unclog' # # # otherwise: no custom exit # return None