# source: https://raw.githubusercontent.com/TheoBrigitte/freqtrade/b9feaaa2f845aed5612b3c7726a0590ee233c846/strategies/profiters/SqueezeMomentum.py # --- Do not remove these libs --- from freqtrade.strategy.interface import IStrategy from pandas import DataFrame import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib import numpy as np from freqtrade.strategy import DecimalParameter, IntParameter, BooleanParameter, CategoricalParameter, stoploss_from_open from datetime import datetime # -------------------------------- def EWO(dataframe, ema_length=5, ema2_length=35): df = dataframe.copy() ema1 = ta.EMA(df, timeperiod=ema_length) ema2 = ta.EMA(df, timeperiod=ema2_length) emadif = (ema1 - ema2) / df['close'] * 100 return emadif """ ======================================================= SELL REASON STATS ======================================================== | Sell Reason | Sells | Win Draws Loss Win% | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | |--------------------+---------+--------------------------+----------------+----------------+-------------------+----------------| | sell_signal | 392 | 159 0 233 40.6 | -0.45 | -178.25 | -892.121 | -59.42 | | trailing_stop_loss | 187 | 187 0 0 100 | 3.53 | 659.86 | 3302.61 | 219.95 | ====================================================== LEFT OPEN TRADES REPORT ====================================================== | Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | Avg Duration | Win Draw Loss Win% | |--------+--------+----------------+----------------+-------------------+----------------+----------------+-------------------------| | TOTAL | 0 | 0.00 | 0.00 | 0.000 | 0.00 | 0:00 | 0 0 0 0 | =============== SUMMARY METRICS ================ | Metric | Value | |------------------------+---------------------| | Backtesting from | 2021-10-12 00:00:00 | | Backtesting to | 2021-11-12 00:00:00 | | Max open trades | 3 | | | | | Total/Daily Avg Trades | 579 / 18.68 | | Starting balance | 1000.000 USDT | | Final balance | 3410.494 USDT | | Absolute profit | 2410.494 USDT | | Total profit % | 241.05% | | Trades per day | 18.68 | | Avg. daily profit % | 7.78% | | Avg. stake amount | 500.000 USDT | | Total trade volume | 289500.000 USDT | | | | | Best Pair | QRDO/USDT 35.47% | | Worst Pair | DAG/USDT -12.07% | | Best trade | ARX/USDT 8.93% | | Worst trade | ATOM/USDT -11.35% | | Best day | 235.119 USDT | | Worst day | -36.114 USDT | | Days win/draw/lose | 26 / 0 / 5 | | Avg. Duration Winners | 1:41:00 | | Avg. Duration Loser | 3:10:00 | | Rejected Buy signals | 217074 | | | | | Min balance | 955.214 USDT | | Max balance | 3410.494 USDT | | Drawdown | 22.67% | | Drawdown | 113.471 USDT | | Drawdown high | 2385.361 USDT | | Drawdown low | 2271.890 USDT | | Drawdown Start | 2021-11-10 17:55:00 | | Drawdown End | 2021-11-10 23:05:00 | | Market change | 0% | ================================================ Epoch details: * 5/90: 579 trades. 346/0/233 Wins/Draws/Losses. Avg profit 0.83%. Median profit 0.54%. Total profit 2410.49362831 USDT ( 241.05%). Avg duration 2:17:00 min. Objective: -112.66357 # Buy hyperspace params: buy_params = { "ADX_thresold": 40, "BB_length": 20, "BB_multifactor": 2, "KC_length": 25, "KC_multifactor": 1.5, "RSI_overbought": 45, "use_true_range": True, } # Sell hyperspace params: sell_params = { "pHSL": -0.08, # value loaded from strategy "pPF_1": 0.016, # value loaded from strategy "pPF_2": 0.08, # value loaded from strategy "pSL_1": 0.011, # value loaded from strategy "pSL_2": 0.04, # value loaded from strategy } # ROI table: # value loaded from strategy minimal_roi = { "0": 0.3 } # Stoploss: stoploss = -0.99 # value loaded from strategy # Trailing stop: trailing_stop = True # value loaded from strategy trailing_stop_positive = 0.005 # value loaded from strategy trailing_stop_positive_offset = 0.03 # value loaded from strategy trailing_only_offset_is_reached = True # value loaded from strategy """ """ ======================================================= SELL REASON STATS ======================================================== | Sell Reason | Sells | Win Draws Loss Win% | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | |--------------------+---------+--------------------------+----------------+----------------+-------------------+----------------| | sell_signal | 457 | 196 0 261 42.9 | -0.57 | -258.56 | -1294.08 | -86.19 | | trailing_stop_loss | 261 | 261 0 0 100 | 3.57 | 931.7 | 4663.14 | 310.57 | | force_sell | 2 | 0 0 2 0 | -0.64 | -1.28 | -6.389 | -0.43 | ======================================================= LEFT OPEN TRADES REPORT ======================================================= | Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | Avg Duration | Win Draw Loss Win% | |----------+--------+----------------+----------------+-------------------+----------------+----------------+-------------------------| | MHC/USDT | 1 | -0.36 | -0.36 | -1.801 | -0.18 | 1:30:00 | 0 0 1 0 | | XLM/USDT | 1 | -0.92 | -0.92 | -4.588 | -0.46 | 1:05:00 | 0 0 1 0 | | TOTAL | 2 | -0.64 | -1.28 | -6.389 | -0.64 | 1:18:00 | 0 0 2 0 | =============== SUMMARY METRICS ================ | Metric | Value | |------------------------+---------------------| | Backtesting from | 2021-10-12 00:00:00 | | Backtesting to | 2021-11-12 00:00:00 | | Max open trades | 3 | | | | | Total/Daily Avg Trades | 720 / 23.23 | | Starting balance | 1000.000 USDT | | Final balance | 4362.668 USDT | | Absolute profit | 3362.668 USDT | | Total profit % | 336.27% | | Trades per day | 23.23 | | Avg. daily profit % | 10.85% | | Avg. stake amount | 500.000 USDT | | Total trade volume | 360000.000 USDT | | | | | Best Pair | XNL/USDT 45.69% | | Worst Pair | DAG/USDT -8.3% | | Best trade | XNL/USDT 19.72% | | Worst trade | DAPPT/USDT -9.72% | | Best day | 229.122 USDT | | Worst day | -8.923 USDT | | Days win/draw/lose | 29 / 0 / 3 | | Avg. Duration Winners | 1:43:00 | | Avg. Duration Loser | 3:23:00 | | Rejected Buy signals | 377484 | | | | | Min balance | 968.162 USDT | | Max balance | 4376.206 USDT | | Drawdown | 18.82% | | Drawdown | 94.205 USDT | | Drawdown high | 3312.883 USDT | | Drawdown low | 3218.678 USDT | | Drawdown Start | 2021-11-10 15:55:00 | | Drawdown End | 2021-11-10 23:40:00 | | Market change | 0% | ================================================ Epoch details: 462/684: 720 trades. 457/0/263 Wins/Draws/Losses. Avg profit 0.93%. Median profit 0.69%. Total profit 3362.66761261 USDT ( 336.27%). Avg duration 2:19:00 min. Objective: -147.06218 # Buy hyperspace params: buy_params = { "ADX_thresold": 33, "BB_length": 22, "BB_multifactor": 1.5, "KC_length": 28, "KC_multifactor": 1, "RSI_overbought": 45, "use_true_range": False, } # Sell hyperspace params: sell_params = { "pHSL": -0.08, # value loaded from strategy "pPF_1": 0.016, # value loaded from strategy "pPF_2": 0.08, # value loaded from strategy "pSL_1": 0.011, # value loaded from strategy "pSL_2": 0.04, # value loaded from strategy } # ROI table: # value loaded from strategy minimal_roi = { "0": 0.3 } # Stoploss: stoploss = -0.99 # value loaded from strategy # Trailing stop: trailing_stop = True # value loaded from strategy trailing_stop_positive = 0.005 # value loaded from strategy trailing_stop_positive_offset = 0.03 # value loaded from strategy trailing_only_offset_is_reached = True # value loaded from strategy """ class Github_TheoBrigitte_freqtrade__SqueezeMomentum__20250415_204015(IStrategy): INTERFACE_VERSION = 2 # Buy hyperspace params: buy_params = { 'BB_length': 20, 'BB_multifactor': 2.0, 'KC_length': 11, 'KC_multifactor': 1.5, 'use_true_range': True, 'RSI_overbought': 60, 'ADX_thresold': 33, } # Sell hyperspace params: sell_params = { } # ROI table: # value loaded from strategy minimal_roi = { "0": 0.3 } # Stoploss: stoploss = -0.99 # value loaded from strategy # Trailing stop: trailing_stop = True # value loaded from strategy trailing_stop_positive = 0.005 # value loaded from strategy trailing_stop_positive_offset = 0.03 # value loaded from strategy trailing_only_offset_is_reached = True # value loaded from strategy use_custom_stoploss = False # Sell signal use_exit_signal = True exit_profit_only = False exit_profit_offset = 0.01 ignore_roi_if_entry_signal = False process_only_new_candles = True startup_candle_count = 30 # Parameters BB_length = IntParameter(10, 30, default=buy_params['BB_length'], space='buy', optimize=True) BB_multifactor = CategoricalParameter([0.5, 1, 1.5, 2, 2.5, 3, 3.5], default=buy_params['BB_multifactor'], space='buy', optimize=True) KC_length = IntParameter(10, 30, default=buy_params['KC_length'], space='buy', optimize=True) KC_multifactor = CategoricalParameter([0.5, 1, 1.5, 2, 2.5, 3, 3.5], default=buy_params['KC_multifactor'], space='buy', optimize=True) use_true_range = BooleanParameter(default=buy_params['use_true_range'], space='buy', optimize=True) # Guards RSI_overbought = CategoricalParameter([45, 50, 55, 60, 65], default=buy_params['RSI_overbought'], space='buy', optimize=True) ADX_thresold = CategoricalParameter([15, 20, 25, 30, 33, 35, 40, 45, 50], default=buy_params['ADX_thresold'], space='buy', optimize=True) ## Trailing params # hard stoploss profit pHSL = DecimalParameter(-0.200, -0.040, default=-0.08, decimals=3, space='sell', load=True) # profit threshold 1, trigger point, SL_1 is used pPF_1 = DecimalParameter(0.008, 0.020, default=0.016, decimals=3, space='sell', load=True) pSL_1 = DecimalParameter(0.008, 0.020, default=0.011, decimals=3, space='sell', load=True) # profit threshold 2, SL_2 is used pPF_2 = DecimalParameter(0.040, 0.100, default=0.080, decimals=3, space='sell', load=True) pSL_2 = DecimalParameter(0.020, 0.070, default=0.040, decimals=3, space='sell', load=True) # Optimal timeframe for the strategy timeframe = '5m' ## Custom Trailing stoploss ( credit to Perkmeister for this custom stoploss to help the strategy ride a green candle ) def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, current_rate: float, current_profit: float, **kwargs) -> float: # hard stoploss profit HSL = self.pHSL.value PF_1 = self.pPF_1.value SL_1 = self.pSL_1.value PF_2 = self.pPF_2.value SL_2 = self.pSL_2.value # For profits between PF_1 and PF_2 the stoploss (sl_profit) used is linearly interpolated # between the values of SL_1 and SL_2. For all profits above PL_2 the sl_profit value # rises linearly with current profit, for profits below PF_1 the hard stoploss profit is used. if (current_profit > PF_2): sl_profit = SL_2 + (current_profit - PF_2) elif (current_profit > PF_1): sl_profit = SL_1 + ((current_profit - PF_1) * (SL_2 - SL_1) / (PF_2 - PF_1)) else: sl_profit = HSL # Only for hyperopt invalid return if (sl_profit >= current_profit): return -0.99 return stoploss_from_open(sl_profit, current_profit) def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ // // @author LazyBear // List of all my indicators: https://www.tradingview.com/v/4IneGo8h/ // // Calculate BB source = close basis = sma(source, length) dev = multKC * stdev(source, length) upperBB = basis + dev lowerBB = basis - dev // Calculate KC ma = sma(source, lengthKC) range = useTrueRange ? tr : (high - low) rangema = sma(range, lengthKC) upperKC = ma + rangema * multKC lowerKC = ma - rangema * multKC sqzOn = (lowerBB > lowerKC) and (upperBB < upperKC) sqzOff = (lowerBB < lowerKC) and (upperBB > upperKC) noSqz = (sqzOn == false) and (sqzOff == false) val = linreg(source - avg(avg(highest(high, lengthKC), lowest(low, lengthKC)),sma(close,lengthKC)), lengthKC,0) bcolor = iff( val > 0, iff( val > nz(val[1]), lime, green), iff( val < nz(val[1]), red, maroon)) scolor = noSqz ? blue : sqzOn ? black : gray plot(val, color=bcolor, style=histogram, linewidth=4) plot(0, color=scolor, style=cross, linewidth=2) """ if self.use_true_range.value: dataframe[f'range'] = ta.TRANGE(dataframe) else: dataframe[f'range'] = dataframe['high'] - dataframe['low'] for val in self.BB_length.range: # BB dataframe[f'ma_{val}'] = ta.SMA(dataframe, val) dataframe[f'stdev_{val}'] = ta.STDDEV(dataframe, val) # KC dataframe[f'rangema_{val}'] = ta.SMA(dataframe[f'range'], val) # Linreg dataframe[f'hh_close_{val}'] = ta.MAX(dataframe['high'], val) dataframe[f'll_close_{val}'] = ta.MIN(dataframe['low'], val) dataframe[f'avg_hh_ll_{val}'] = (dataframe[f'hh_close_{val}'] + dataframe[f'll_close_{val}']) / 2 dataframe[f'avg_close_{val}'] = ta.SMA(dataframe['close'], val) dataframe[f'avg_{val}'] = (dataframe[f'avg_hh_ll_{val}'] + dataframe[f'avg_close_{val}']) / 2 dataframe[f'val_{val}'] = ta.LINEARREG(dataframe['close'] - dataframe[f'avg_{val}'], val, 0) # min val dataframe[f'val_min_{val}'] = ta.MIN(dataframe[f'val_{val}'], 50) # max val dataframe[f'val_max_{val}'] = ta.MAX(dataframe[f'val_{val}'], 50) # stdev val dataframe[f'val_stdev_{val}'] = ta.STDDEV(dataframe[f'val_{val}'], 50) # average val dataframe[f'val_avg_{val}'] = ta.SMA(dataframe[f'val_{val}'], 50) for val in self.KC_length.range: # BB dataframe[f'ma_{val}'] = ta.SMA(dataframe, val) dataframe[f'stdev_{val}'] = ta.STDDEV(dataframe, val) # KC dataframe[f'rangema_{val}'] = ta.SMA(dataframe[f'range'], val) # RSI dataframe['rsi'] = ta.RSI(dataframe) # EMA dataframe['ema_50'] = ta.EMA(dataframe, 50) dataframe['ema_200'] = ta.EMA(dataframe, 200) # ADX dataframe['adx'] = ta.ADX(dataframe, 14) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: bb_length = self.BB_length.value mult = self.BB_multifactor.value kc = self.KC_multifactor.value kc_length = self.KC_length.value is_sqzOn = ( (dataframe[f'ma_{bb_length}'] - dataframe[f'stdev_{bb_length}'] * mult > dataframe[f'ma_{kc_length}'] - dataframe[f'rangema_{kc_length}'] * kc) & (dataframe[f'ma_{bb_length}'] + dataframe[f'stdev_{bb_length}'] * mult < dataframe[f'ma_{kc_length}'] + dataframe[f'rangema_{kc_length}'] * kc) ) is_sqzOff = ( (dataframe[f'ma_{bb_length}'] - dataframe[f'stdev_{bb_length}'] * mult < dataframe[f'ma_{kc_length}'] - dataframe[f'rangema_{kc_length}'] * kc) & (dataframe[f'ma_{bb_length}'] + dataframe[f'stdev_{bb_length}'] * mult > dataframe[f'ma_{kc_length}'] + dataframe[f'rangema_{kc_length}'] * kc) ) # is_noSqz = ( # ((not is_sqzOn) & (not is_sqzOff)) # ) dataframe.loc[ ( # (dataframe[f'sqzOn_{self.KC_length.value}_{self.KC_multifactor.value}'] == 1) & # (dataframe[f'val_{self.BB_length.value}'] > 0) & # (dataframe[f'val_{self.BB_length.value}'].shift(1) < 0) & # (dataframe[f'sqzOn_{self.KC_length.value}_{self.KC_multifactor.value}'].shift(1) == 1) & (is_sqzOff) & (dataframe[f'val_{self.BB_length.value}'].shift(2) > dataframe[f'val_{self.BB_length.value}'].shift(1)) & (dataframe[f'val_{self.BB_length.value}'].shift(1) < dataframe[f'val_{self.BB_length.value}']) & # (dataframe[f'val_{self.BB_length.value}'].shift(1) == dataframe[f'val_min_{self.BB_length.value}']) & # (dataframe[f'val_{self.BB_length.value}'].shift(1) < dataframe[f'val_avg_{self.BB_length.value}'] - dataframe[f'val_stdev_{self.BB_length.value}']) & (dataframe[f'val_{self.BB_length.value}'] < 0) & (dataframe['adx'] > self.ADX_thresold.value) & # (dataframe[f'sqzOn_{self.KC_length.value}_{self.KC_multifactor.value}'].rolling(10).sum() < 3) & (dataframe['rsi'] < self.RSI_overbought.value) & # (dataframe['close'] > dataframe['ema_50']) & # (dataframe['ema_50'] > dataframe['ema_200']) & (dataframe['volume'] > 0) ), 'buy'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe[f'val_{self.BB_length.value}'].shift(2) < dataframe[f'val_{self.BB_length.value}'].shift(1)) & (dataframe[f'val_{self.BB_length.value}'].shift(1) > dataframe[f'val_{self.BB_length.value}']) & (dataframe[f'val_{self.BB_length.value}'].shift(1) == dataframe[f'val_max_{self.BB_length.value}']) & (dataframe[f'val_{self.BB_length.value}'] > 0) & (dataframe['volume'] > 0) ), 'sell'] = 1 #dataframe.to_csv('user_data/csvs/%s_%s.csv' % (self.__class__.__name__, metadata["pair"].replace("/", "_"))) return dataframe