# source: https://raw.githubusercontent.com/RoboticAutomations/freqtradestrategies/52c4bd40414645f079a980cf4486dc7af4061efb/AIRA%20-%20open%20code%20v2/strategies/elliott-wave/AngleWaveCT.py # directory_url: https://github.com/RoboticAutomations/freqtradestrategies/blob/main/AIRA - open code v2/strategies/elliott-wave/ # User: RoboticAutomations # Repository: freqtradestrategies # --------------------# --- Do not remove these libs --- import math from freqtrade.strategy.interface import IStrategy from typing import Dict, List from functools import reduce from pandas import DataFrame # -------------------------------- import talib.abstract as ta import numpy as np import freqtrade.vendor.qtpylib.indicators as qtpylib import datetime import pandas_ta as pta from technical.util import resample_to_interval, resampled_merge from datetime import datetime, timedelta from freqtrade.persistence import Trade from freqtrade.strategy import stoploss_from_open, merge_informative_pair, DecimalParameter, IntParameter, \ CategoricalParameter import technical.indicators as ftt from freqtrade.exchange import timeframe_to_minutes # Buy hyperspace params: buy_params = { "base_nb_candles_buy": 8, "ewof": 8, "ewos": 89, "ewo_high_mult": 1.3618, "ewo_bear_mult": 1.65, "ewo_bull_mult": 1.01618, "low_offset": 0.95, # 34, # 0.942 for BTC and 0.934 for USDT "rsi_buy": 61 # with regular ewo 45 } # Sell hyperspace params: sell_params = { "base_nb_candles_sell": 8, "high_offset": 1.01918 # 1.019 } def EWO(dataframe, ema_length=8, ema2_length=89): df = dataframe.copy() ema1 = ta.EMA(df, timeperiod=ema_length.value) ema2 = ta.EMA(df, timeperiod=ema2_length.value) emadif = (ema1 - ema2) / df['close'] * 100 return emadif class Github_RoboticAutomations_freqtradestrategies__AngleWaveCT__20260915_233254(IStrategy): INTERFACE_VERSION = 3 # ROI table: minimal_roi = { "0": 0.215, "40": 0.132, "87": 0.086, "360": 0.03 } # Stoploss: stoploss = -0.318 # -0.042 # -0.318 use_custom_stoploss = True # SMAOffset base_nb_candles_buy = IntParameter(5, 80, default=buy_params['base_nb_candles_buy'], space='buy', optimize=True) base_nb_candles_sell = IntParameter(5, 80, default=sell_params['base_nb_candles_sell'], space='sell', optimize=True) low_offset = DecimalParameter(0.9, 0.99, default=buy_params['low_offset'], space='buy', decimals=2, optimize=True) high_offset = DecimalParameter(0.99, 1.1, default=sell_params['high_offset'], decimals=2, space='sell', optimize=True) fast_ewo = IntParameter(5, 8, default=buy_params['ewof'], space='buy', optimize=True) slow_ewo = IntParameter(50, 100, default=buy_params['ewos'], space='buy', optimize=True) ewo_lo_limit = DecimalParameter(-5, 0, default=-2.5, decimals=1, space='buy', optimize=True) ewo_bear_x = DecimalParameter(1.62, 1.80, default=buy_params['ewo_bear_mult'], decimals=2, space='buy', optimize=True) ewo_high_x = DecimalParameter(1.30, 1.40, default=buy_params['ewo_high_mult'], decimals=2, space='buy', optimize=True) ewo_bull_x = DecimalParameter(1.01, 1.3, default=buy_params['ewo_bull_mult'], decimals=3, space='buy', optimize=True) rsi_buy_low = IntParameter(30, 50, default=35, space='buy', optimize=True) rsi_buy_high = IntParameter(50, 70, default=buy_params['rsi_buy'], space='buy', optimize=True) ### trailing stop loss optimiziation ### tsl_target5 = DecimalParameter(low=0.2, high=0.4, decimals=1, default=0.3, space='sell', optimize=True, load=True) ts5 = DecimalParameter(low=0.04, high=0.06, default=0.05, decimals=2,space='sell', optimize=True, load=True) tsl_target4 = DecimalParameter(low=0.15, high=0.2, default=0.2, decimals=2, space='sell', optimize=True, load=True) ts4 = DecimalParameter(low=0.03, high=0.05, default=0.045, decimals=2, space='sell', optimize=True, load=True) tsl_target3 = DecimalParameter(low=0.10, high=0.15, default=0.15, decimals=2, space='sell', optimize=True, load=True) ts3 = DecimalParameter(low=0.025, high=0.04, default=0.035, decimals=3, space='sell', optimize=True, load=True) tsl_target2 = DecimalParameter(low=0.06, high=0.10, default=0.1, decimals=3, space='sell', optimize=True, load=True) ts2 = DecimalParameter(low=0.015, high=0.03, default=0.02, decimals=3, space='sell', optimize=True, load=True) tsl_target1 = DecimalParameter(low=0.04, high=0.06, default=0.06, decimals=3, space='sell', optimize=True, load=True) ts1 = DecimalParameter(low=0.01, high=0.016, default=0.013, decimals=3, space='sell', optimize=True, load=True) tsl_target0 = DecimalParameter(low=0.02, high=0.04, default=0.03, decimals=3, space='sell', optimize=True, load=True) ts0 = DecimalParameter(low=0.008, high=0.015, default=0.013, decimals=3, space='sell', optimize=True, load=True) # # Trailing stop: # trailing_stop = True # trailing_stop_positive = 0.00618 # trailing_stop_positive_offset = 0.042 # trailing_only_offset_is_reached = True # Sell signal use_sell_signal = True sell_profit_only = False sell_profit_offset = 0.01 ignore_roi_if_buy_signal = True ## Optional order time in force. order_time_in_force = { 'buy': 'gtc', 'sell': 'ioc' } # Optimal timeframe for the strategy timeframe = '5m' informative_timeframe = '1h' process_only_new_candles = True startup_candle_count = 89 plot_config = { 'main_plot': { 'ma_buy': {'color': 'orange'}, 'ma_sell': {'color': 'orange'}, }, } @property def protections(self): return [ { "method": "CooldownPeriod", "stop_duration_candles": 1 }, { "method": "MaxDrawdown", "lookback_period_candles": 30, "trade_limit": 6, "stop_duration_candles": 16, "max_allowed_drawdown": 0.1 }, { "method": "StoplossGuard", "lookback_period_candles": 10, "trade_limit": 3, "stop_duration_candles": 6, "required_profit": 0.0, "only_per_pair": False, "only_per_side": False }, { "method": "LowProfitPairs", "lookback_period_candles": 6, "trade_limit": 2, "stop_duration_candles": 60, "required_profit": 0.02 } ] ### Trailing Stop ### def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, current_rate: float, current_profit: float, **kwargs) -> float: for stop5 in self.tsl_target5.range: if (current_profit > stop5): for stop5a in self.ts5.range: self.dp.send_msg(f'*** {pair} *** Profit: {current_profit} - lvl5 {stop5}/{stop5a} activated') return stop5a for stop4 in self.tsl_target4.range: if (current_profit > stop4): for stop4a in self.ts4.range: self.dp.send_msg(f'*** {pair} *** Profit {current_profit} - lvl4 {stop4}/{stop4a} activated') return stop4a for stop3 in self.tsl_target3.range: if (current_profit > stop3): for stop3a in self.ts3.range: self.dp.send_msg(f'*** {pair} *** Profit {current_profit} - lvl3 {stop3}/{stop3a} activated') return stop3a for stop2 in self.tsl_target2.range: if (current_profit > stop2): for stop2a in self.ts2.range: self.dp.send_msg(f'*** {pair} *** Profit {current_profit} - lvl2 {stop2}/{stop2a} activated') return stop2a for stop1 in self.tsl_target1.range: if (current_profit > stop1): for stop1a in self.ts1.range: self.dp.send_msg(f'*** {pair} *** Profit {current_profit} - lvl1 {stop1}/{stop1a} activated') return stop1a for stop0 in self.tsl_target0.range: if (current_profit > stop0): for stop0a in self.ts0.range: self.dp.send_msg(f'*** {pair} *** Profit {current_profit} - lvl0 {stop0}/{stop0a} activated') return stop0a return self.stoploss def informative_pairs(self): pairs = self.dp.current_whitelist() informative_pairs = [(pair, self.informative_timeframe) for pair in pairs] return informative_pairs def get_informative_indicators(self, metadata: dict): dataframe = self.dp.get_pair_dataframe( pair=metadata['pair'], timeframe=self.informative_timeframe) return dataframe def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # Calculate all ma_buy values for val in self.base_nb_candles_buy.range: dataframe[f'ma_buy_{val}'] = ta.EMA(dataframe, timeperiod=val) # Calculate all ma_sell values for val in self.base_nb_candles_sell.range: dataframe[f'ma_sell_{val}'] = ta.EMA(dataframe, timeperiod=val) # Elliot dataframe['EWO'] = EWO(dataframe, self.fast_ewo, self.slow_ewo) # EMAs for Bear/Bull dataframe['ema'] = ta.EMA(dataframe, timeperiod=self.fast_ewo.value) dataframe['ema2'] = ta.EMA(dataframe, timeperiod=self.slow_ewo.value) # RSI dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14) # 14) dataframe['rsi_ma'] = ta.SMA(dataframe['rsi'], timeperiod=8) # 5) # absolute ewo dataframe["ABSEWO"] = dataframe["EWO"] dataframe.loc[dataframe["EWO"] < 0, "ABSEWO"] = dataframe["EWO"] * - 1 # seperate pos and neg ewo dataframe.loc[dataframe["EWO"] > 0, "POSEWO"] = dataframe["EWO"] dataframe.loc[dataframe["EWO"] < 0, "NEGEWO"] = dataframe["EWO"] dataframe["POSEWO"].fillna(method="ffill", inplace=True) dataframe["NEGEWO"].fillna(method="ffill", inplace=True) # angle of the ema candlesBack = 3 backQuote = dataframe['ema'].shift(candlesBack) deltaX = candlesBack deltaY = dataframe['ema'] - backQuote dataframe['angleRad'] = (deltaY / deltaX).apply(lambda x: math.atan(x)) dataframe['angle_perc'] = (dataframe['angleRad'] / dataframe['close']) * 100 threshold = 0 # .0000001 dataframe["ema_angle_up"] = dataframe['angleRad'] > 0 + threshold dataframe["ema_angle_down"] = dataframe['angleRad'] < 0 - threshold # ewo normalized dataframe['min'] = dataframe["EWO"].rolling(89).min() dataframe['max'] = dataframe["EWO"].rolling(89).max() dataframe['dif'] = dataframe['max'].sub(dataframe['min']) dataframe["ewoNorm"] = dataframe["EWO"] / dataframe['dif'] dataframe['ewoNormMa'] = ta.SMA(dataframe["ewoNorm"], timeperiod=self.fast_ewo.value) dataframe['ewoNormMaHigh'] = 0.0618 # angle of the ewoNorm candlesBack2 = 1 backQuote2 = dataframe['ewoNorm'].shift(candlesBack2) deltaX2 = candlesBack2 deltaY2 = dataframe['ewoNorm'] - backQuote2 dataframe['ewoAngleRad'] = (deltaY2 / deltaX2).apply(lambda x: math.atan(x)) dataframe["ewo_angle_up"] = dataframe['ewoAngleRad'] > -0.0001 dataframe["ewo_angle_down"] = dataframe['ewoAngleRad'] < 0.0001 emaPercent = dataframe['ema'] / dataframe['ema2'] avg_positive_ewo = dataframe["POSEWO"].rolling(self.base_nb_candles_buy.value).mean() avg_negative_ewo = dataframe["NEGEWO"].rolling(self.base_nb_candles_buy.value).mean() avg_abs_ewo = dataframe["ABSEWO"].rolling(self.base_nb_candles_buy.value).mean() # scale the buys. if we bear then push back the buys if we bull make more buys dataframe["ewo_low_mult"] = self.ewo_bull_x.value # / emaPercent # 0.618 dataframe.loc[dataframe["ema"] < dataframe["ema2"], "ewo_low_mult"] = self.ewo_bear_x.value # for buy below rolling ewo low ewo_low = avg_negative_ewo * dataframe["ewo_low_mult"] dataframe['ewo_low'] = ewo_low # for rsi buy ewo_high = avg_positive_ewo * self.ewo_high_x.value dataframe['ewo_high'] = ewo_high dataframe['ewo_limit'] = self.ewo_lo_limit.value dataframe['atr_pcnt'] = (qtpylib.atr(dataframe) / dataframe['close']) dataframe['ma_lo'] = (dataframe[f'ma_buy_{self.base_nb_candles_buy.value}'] * (self.low_offset.value - (dataframe['atr_pcnt']/3))) dataframe['ma_hi'] = (dataframe[f'ma_buy_{self.base_nb_candles_buy.value}'] * (self.high_offset.value + dataframe['atr_pcnt'])) return dataframe def do_informative_indicators(self, inf: DataFrame, metadata: dict) -> DataFrame: # informative = dataframe = self.dp.get_pair_dataframe( # pair=metadata['pair'], timeframe=self.informative_timeframe) inf['inf_ema'] = ta.SMA(inf["close"], timeperiod=self.fast_ewo.value) inf['inf_ema2'] = ta.SMA(inf["close"], timeperiod=self.slow_ewo.value) # print(inf['inf_ema']) return inf def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # if self.config['runmode'].value in ('backtest', 'hyperopt'): # assert (timeframe_to_minutes(self.timeframe) <= 5), "Backtest this strategy in 5m or 1m timeframe." if self.timeframe == self.informative_timeframe: dataframe = self.do_indicators(dataframe, metadata) else: if not self.dp: return dataframe informative = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe=self.informative_timeframe) # todo this dont work why when i run informative indicators does this not work... informative = self.do_informative_indicators(informative.copy(), metadata) # informative = self.do_indicators(informative.copy(), metadata) dataframe = self.do_indicators(dataframe.copy(), metadata) dataframe = merge_informative_pair(dataframe, informative, self.timeframe, self.informative_timeframe, ffill=True) skip_columns = [(s + "_" + self.informative_timeframe) for s in ['date', 'open', 'high', 'low', 'close', 'volume']] dataframe.rename(columns=lambda s: s.replace("_{}".format(self.informative_timeframe), "") if ( not s in skip_columns) else s, inplace=True) return dataframe def populate_buy_trend(self, df: DataFrame, metadata: dict) -> DataFrame: df.loc[ ( (df['EWO'] > df['ewo_high']) & # (df['close'] < (df[f'ma_buy_{self.base_nb_candles_buy.value}'] * self.low_offset.value)) & (df['close'] < df['ma_lo']) & # (df["ewo_angle_up"]) & (df['volume'] > 0) # Make sure Volume is not 0 ), ['enter_long', 'enter_tag']] = (1, 'EWO > HIGH') df.loc[ ( (df['EWO'] < df['ewo_high']) & (df['close'] < df['ma_lo']) & (df["ewo_angle_up"]) & (df['volume'] > 0) # Make sure Volume is not 0 ), ['enter_long', 'enter_tag']] = (1, 'EWO < HIGH') df.loc[ ( (qtpylib.crossed_above(df['EWO'], df['ewo_high'])) & (df['close'] < df['ma_lo']) & (df["ewo_angle_up"]) & (df['rsi'] < self.rsi_buy_high.value) & (df['volume'] > 0) # Make sure Volume is not 0 ), ['enter_long', 'enter_tag']] = (1, 'EWO XO HIGH') df.loc[ ( (qtpylib.crossed_above(df['EWO'], df['ewo_low'])) & (df['close'] < df['ma_lo']) & (df['EWO'] < self.ewo_lo_limit.value) & (df['rsi'] < self.rsi_buy_low.value) & (df['volume'] > 0) # Make sure Volume is not 0 ), ['enter_long', 'enter_tag']] = (1, 'EWO XO LOW') df.loc[ ( (df['EWO'] < df['ewo_low']) & (df['close'] < df['ma_lo']) & (df['EWO'] < self.ewo_lo_limit.value) & (df['rsi'] < self.rsi_buy_low.value) & (df['volume'] > 0) # Make sure Volume is not 0 ), ['enter_long', 'enter_tag']] = (1, 'EWO < LOW') # df.loc[ # ( # ((df['angle_perc'] - df['angle_perc'].shift(1)) > 0.07 ) & # ((df['angle_perc'].shift(1) - df['angle_perc'].shift(2)) < 0 ) & # (df['angle_perc'] < 0.17) & # (df['angle_perc'] > 0) & # (df['close'] > (df[f'ma_sell_{self.base_nb_candles_sell.value}'] * self.high_offset.value)) & # (df['volume'] > 0) # Make sure Volume is not 0 # ), # ['enter_long', 'enter_tag']] = (1, 'Angle Change Pos') df.loc[ ( ((df['angle_perc'] - df['angle_perc'].shift(1)) > 0.07 ) & ((df['angle_perc'].shift(1) - df['angle_perc'].shift(2)) < 0 ) & (df['angle_perc'] < 0) & (df['open'] < (df[f'ma_buy_{self.base_nb_candles_buy.value}'] * self.low_offset.value)) & (df['volume'] > 0) # Make sure Volume is not 0 ), ['enter_long', 'enter_tag']] = (1, 'Angle Change Neg') return df def populate_sell_trend(self, df: DataFrame, metadata: dict) -> DataFrame: df.loc[ ( (df['close'] > df['ma_hi']) & (df['EWO'] > df['ewo_high']) & # (df['angle_perc'] < 0.10) & (df['EWO'] > 0) & (df['volume'] > 0) # Make sure Volume is not 0 ), ['exit_long', 'exit_tag']] = (1, 'EWO High') df.loc[ ( (df['close'] > df['ma_hi']) & (df['rsi'] >= 89) & (df['EWO'] > 0) & (df['volume'] > 0) # Make sure Volume is not 0 ), ['exit_long', 'exit_tag']] = (1, 'EWO rsi limit') df.loc[ ( (df['close'] > df['ma_hi']) & (df['rsi'] >= 89) & (df['EWO'] < 0) & (df['volume'] > 0) # Make sure Volume is not 0 ), ['exit_long', 'exit_tag']] = (1, 'EWO low rsi limit') return df # "0": 0.202, # "141": 0.094, # "380": 0.017, # "1459": 0 # ============================================================ BACKTESTING REPORT ============================================================ # | Pair | Entries | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | Avg Duration | Win Draw Loss Win% | # |------------+-----------+----------------+----------------+-------------------+----------------+----------------+-------------------------| # | ORAI/USDT | 383 | 1.00 | 383.32 | 519743.915 | 51974.39 | 3:08:00 | 295 0 88 77.0 | # | CTI/USDT | 426 | 0.98 | 415.54 | 518202.754 | 51820.28 | 4:10:00 | 319 1 106 74.9 | # | EWT/USDT | 380 | 1.31 | 498.67 | 271591.642 | 27159.16 | 3:40:00 | 325 0 55 85.5 | # | EOSC/USDT | 1003 | 1.34 | 1348.19 | 268456.489 | 26845.65 | 3:44:00 | 720 8 275 71.8 | # | OPUL/USDT | 133 | 0.72 | 95.39 | 234658.280 | 23465.83 | 4:49:00 | 106 0 27 79.7 | # | YFDAI/USDT | 178 | 1.06 | 189.22 | 234636.196 | 23463.62 | 3:59:00 | 141 0 37 79.2 | # | RNDR/USDT | 269 | 0.53 | 142.58 | 228253.623 | 22825.36 | 4:44:00 | 210 0 59 78.1 | # | QNT/USDT | 251 | 1.05 | 264.73 | 214297.194 | 21429.72 | 3:45:00 | 207 1 43 82.5 | # | JASMY/USDT | 95 | 0.49 | 46.49 | 151439.029 | 15143.90 | 3:54:00 | 76 0 19 80.0 | # | GALAX/USDT | 111 | 0.53 | 58.78 | 143250.873 | 14325.09 | 4:55:00 | 90 0 21 81.1 | # | AGIX/USDT | 127 | 0.55 | 69.52 | 134443.919 | 13444.39 | 5:26:00 | 96 0 31 75.6 | # | ROSE/USDT | 295 | 0.40 | 118.29 | 104638.442 | 10463.84 | 4:37:00 | 223 0 72 75.6 | # | COMP/USDT | 248 | 0.61 | 151.96 | 62535.598 | 6253.56 | 5:48:00 | 179 0 69 72.2 | # | AVAX/USDT | 188 | 0.62 | 117.26 | 57317.005 | 5731.70 | 4:48:00 | 145 0 43 77.1 | # | DYDX/USDT | 93 | 0.18 | 16.67 | 48686.734 | 4868.67 | 5:01:00 | 70 0 23 75.3 | # | DOGE/USDT | 105 | 0.43 | 45.23 | 42279.791 | 4227.98 | 3:32:00 | 74 0 31 70.5 | # | GRT/USDT | 246 | 0.42 | 104.23 | 39110.810 | 3911.08 | 4:38:00 | 186 0 60 75.6 | # | UNI/USDT | 168 | -0.10 | -17.03 | 33827.663 | 3382.77 | 5:46:00 | 124 0 44 73.8 | # | IOTA/USDT | 7 | 1.55 | 10.86 | 32847.307 | 3284.73 | 2:57:00 | 6 0 1 85.7 | # | VET/USDT | 441 | 0.92 | 406.32 | 28803.019 | 2880.30 | 6:07:00 | 344 0 97 78.0 | # | ZEC/USDT | 229 | 0.84 | 191.68 | 23252.881 | 2325.29 | 6:48:00 | 173 1 55 75.5 | # | INJ/USDT | 25 | 0.29 | 7.33 | 22088.809 | 2208.88 | 5:26:00 | 17 0 8 68.0 | # | OCEAN/USDT | 4 | 1.33 | 5.30 | 16089.918 | 1608.99 | 5:36:00 | 4 0 0 100 | # | ENJ/USDT | 116 | 0.22 | 25.00 | 15146.552 | 1514.66 | 5:42:00 | 78 0 38 67.2 | # | ALGO/USDT | 520 | 0.26 | 137.67 | 11437.256 | 1143.73 | 6:29:00 | 374 1 145 71.9 | # | RLY/USDT | 90 | 0.37 | 33.65 | 10712.860 | 1071.29 | 5:49:00 | 63 0 27 70.0 | # | BAT/USDT | 66 | -0.11 | -7.07 | 7533.069 | 753.31 | 5:58:00 | 47 0 19 71.2 | # | SUSHI/USDT | 149 | 0.06 | 8.21 | 6935.974 | 693.60 | 6:20:00 | 99 0 50 66.4 | # | XDC/USDT | 100 | 0.36 | 35.84 | 4308.025 | 430.80 | 8:49:00 | 67 1 32 67.0 | # | FIL/USDT | 100 | -0.45 | -45.41 | 3294.538 | 329.45 | 6:33:00 | 64 0 36 64.0 | # | FTM/USDT | 171 | -0.31 | -52.17 | -4205.788 | -420.58 | 5:37:00 | 118 0 53 69.0 | # | KAVA/USDT | 13 | -0.23 | -2.95 | -13975.465 | -1397.55 | 7:03:00 | 9 0 4 69.2 | # | XLM/USDT | 259 | 0.25 | 63.71 | -15020.157 | -1502.02 | 7:40:00 | 186 2 71 71.8 | # | XTZ/USDT | 354 | 0.51 | 181.46 | -19408.109 | -1940.81 | 6:04:00 | 269 1 84 76.0 | # | DOT/USDT | 155 | 0.34 | 52.52 | -21405.279 | -2140.53 | 5:22:00 | 125 0 30 80.6 | # | KLAY/USDT | 2 | -3.85 | -7.69 | -22372.845 | -2237.28 | 15:42:00 | 0 0 2 0 | # | SOL/USDT | 50 | -0.19 | -9.48 | -27906.484 | -2790.65 | 6:07:00 | 34 0 16 68.0 | # | BTC/USDT | 203 | 0.24 | 48.51 | -28814.674 | -2881.47 | 12:30:00 | 141 11 51 69.5 | # | EOS/USDT | 199 | -0.07 | -13.47 | -32819.270 | -3281.93 | 8:45:00 | 147 1 51 73.9 | # | ANKR/USDT | 72 | 0.44 | 31.36 | -34286.282 | -3428.63 | 5:27:00 | 57 0 15 79.2 | # | TRX/USDT | 245 | 0.46 | 112.00 | -34358.719 | -3435.87 | 8:22:00 | 169 2 74 69.0 | # | ETC/USDT | 289 | 0.11 | 31.07 | -35982.250 | -3598.22 | 7:05:00 | 209 3 77 72.3 | # | IMX/USDT | 41 | -0.21 | -8.78 | -37435.415 | -3743.54 | 6:07:00 | 30 0 11 73.2 | # | THETA/USDT | 134 | 0.43 | 57.78 | -44210.763 | -4421.08 | 5:33:00 | 98 0 36 73.1 | # | LINK/USDT | 149 | -0.17 | -25.23 | -44337.942 | -4433.79 | 6:50:00 | 103 0 46 69.1 | # | HBAR/USDT | 40 | -0.37 | -14.96 | -50657.739 | -5065.77 | 7:56:00 | 27 0 13 67.5 | # | TRU/USDT | 20 | -1.13 | -22.54 | -80748.034 | -8074.80 | 6:40:00 | 11 0 9 55.0 | # | AGLD/USDT | 44 | -0.58 | -25.51 | -89057.213 | -8905.72 | 7:43:00 | 29 0 15 65.9 | # | EGLD/USDT | 29 | -0.84 | -24.34 | -89991.975 | -8999.20 | 8:14:00 | 16 0 13 55.2 | # | ADA/USDT | 238 | -0.23 | -54.71 | -91312.660 | -9131.27 | 7:32:00 | 162 0 76 68.1 | # | MATIC/USDT | 91 | -0.78 | -70.84 | -93385.185 | -9338.52 | 6:42:00 | 61 0 30 67.0 | # | NEAR/USDT | 107 | -0.23 | -24.27 | -97835.185 | -9783.52 | 7:33:00 | 73 0 34 68.2 | # | YFI/USDT | 196 | 0.19 | 37.86 | -145312.915 | -14531.29 | 5:43:00 | 138 0 58 70.4 | # | ATOM/USDT | 597 | 0.09 | 51.52 | -172430.204 | -17243.02 | 6:50:00 | 424 0 173 71.0 | # | XRP/USDT | 443 | -0.20 | -87.01 | -222127.681 | -22212.77 | 9:22:00 | 301 5 137 67.9 | # | VELO/USDT | 342 | -0.45 | -155.22 | -262351.608 | -26235.16 | 6:34:00 | 232 2 108 67.8 | # | ETH/USDT | 311 | -0.20 | -63.46 | -320341.045 | -32034.10 | 11:08:00 | 206 5 100 66.2 | # | TOTAL | 11340 | 0.43 | 4863.54 | 1357729.279 | 135772.93 | 6:01:00 | 8297 45 2998 73.2 | # ============================================================= ENTER TAG STATS ============================================================== # | TAG | Entries | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | Avg Duration | Win Draw Loss Win% | # |------------+-----------+----------------+----------------+-------------------+----------------+----------------+-------------------------| # | EWO < LOW | 10364 | 0.40 | 4149.99 | 938103.124 | 93810.31 | 6:15:00 | 7572 44 2748 73.1 | # | EWO > HIGH | 966 | 0.73 | 707.13 | 418948.553 | 41894.86 | 3:29:00 | 717 1 248 74.2 | # | EWO XO LOW | 10 | 0.64 | 6.42 | 677.602 | 67.76 | 4:42:00 | 8 0 2 80.0 | # | TOTAL | 11340 | 0.43 | 4863.54 | 1357729.279 | 135772.93 | 6:01:00 | 8297 45 2998 73.2 | # ======================================================= EXIT REASON STATS ======================================================== # | Exit Reason | Exits | Win Draws Loss Win% | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | # |--------------------+---------+--------------------------+----------------+----------------+-------------------+----------------| # | trailing_stop_loss | 6011 | 5441 0 570 90.5 | 1.51 | 9103.56 | 7.36194e+06 | 1517.26 | # | EWO High | 4425 | 2087 0 2338 47.2 | -1.22 | -5409.28 | -6.85188e+06 | -901.55 | # | roi | 753 | 708 45 0 100 | 2.44 | 1835.52 | 1.16115e+06 | 305.92 | # | EWO rsi limit | 87 | 37 0 50 42.5 | -1.53 | -133.1 | -33764.1 | -22.18 | # | EWO low rsi limit | 46 | 24 0 22 52.2 | -0.54 | -24.82 | -3339.25 | -4.14 | # | stop_loss | 18 | 0 0 18 0 | -28.24 | -508.33 | -276373 | -84.72 | # ======================================================= LEFT OPEN TRADES REPORT ======================================================== # | Pair | Entries | 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 | 2019-01-01 00:00:00 | # | Backtesting to | 2023-04-30 00:00:00 | # | Max open trades | 6 | # | | | # | Total/Daily Avg Trades | 11340 / 7.18 | # | Starting balance | 1000 USDT | # | Final balance | 1358729.279 USDT | # | Absolute profit | 1357729.279 USDT | # | Total profit % | 135772.93% | # | CAGR % | 429.41% | # | Profit factor | 1.11 | # | Trades per day | 7.18 | # | Avg. daily profit % | 85.93% | # | Avg. stake amount | 94657.76 USDT | # | Total trade volume | 1073419000.083 USDT | # | | | # | Best Pair | EOSC/USDT 1348.19% | # | Worst Pair | VELO/USDT -155.22% | # | Best trade | TRX/USDT 182.12% | # | Worst trade | VELO/USDT -28.24% | # | Best day | 222555.567 USDT | # | Worst day | -709320.388 USDT | # | Days win/draw/lose | 886 / 338 / 352 | # | Avg. Duration Winners | 3:27:00 | # | Avg. Duration Loser | 12:45:00 | # | Rejected Entry signals | 1579329 | # | Entry/Exit Timeouts | 0 / 0 | # | | | # | Min balance | 968.649 USDT | # | Max balance | 2634960.342 USDT | # | Max % of account underwater | 68.52% | # | Absolute Drawdown (Account) | 49.81% | # | Absolute Drawdown | 1312533.509 USDT | # | Drawdown high | 2633960.342 USDT | # | Drawdown low | 1321426.832 USDT | # | Drawdown Start | 2021-12-03 10:20:00 | # | Drawdown End | 2022-11-10 03:25:00 | # | Market change | 149.10% | # ===================================================== # "pair_whitelist": [ # "ATOM/USDT", # "XRP/USDT", # "QNT/USDT", # "AKT/USDT", # "IOTA/USDT", # "ADA/USDT", # "OSMO/USDT", # "BTC/USDT", # "ETH/USDT", # "CSPR/USDT", # "ETC/USDT", # "XDC/USDT", # "LINK/USDT", # "MATIC/USDT", # "AVAX/USDT", # "HBAR/USDT", # "SCRT/USDT", # "KAVA/USDT", # "INJ/USDT", # "NEAR/USDT", # "DOT/USDT", # "ALGO/USDT", # "XLM/USDT", # "RNDR/USDT", # "ORAI/USDT", # "AGIX/USDT", # "GRT/USDT", # "DOGE/USDT", # "SOL/USDT", # "TRX/USDT", # "UNI/USDT", # "LDO/USDT", # "FIL/USDT", # "VET/USDT", # "EGLD/USDT", # "THETA/USDT", # "XTZ/USDT", # "IMX/USDT", # "ZEC/USDT", # "GMX/USDT", # "KLAY/USDT", # "OP/USDT", # "ROSE/USDT", # "ENJ/USDT", # "DYDX/USDT", # "OCEAN/USDT", # "FLR/USDT", # "EWT/USDT", # "JASMY/USDT", # "APT/USDT", # "APE/USDT", # "EOS/USDT", # "LUNC/USDT", # "ANKR/USDT", # "GALAX/USDT", # "OPUL/USDT", # "FET/USDT", # "FTM/USDT", # "EOSC/USDT", # "VELO/USDT", # "YFDAI/USDT", # "BAT/USDT", # "TRU/USDT", # "YFI/USDT", # "COMP/USDT", # "AGLD/USDT", # "SUSHI/USDT", # "RLY/USDT", # "CTI/USDT",