UziChan2
♡
Basics
mode: spot
timeframe: 1m
interface version: 3
Settings
stoploss: -0.1
has minimal roi
process only new candles
Indicators
EMA
pandas_ta
talib
13 related strategies (⧉ identical code, ≈ similar name)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 | # --- Do not remove these libs --- from freqtrade.strategy.interface import IStrategy from pandas import DataFrame # -------------------------------- import talib.abstract as ta import logging import pandas_ta as pta from pandas import DataFrame, Series from datetime import datetime, timezone from freqtrade.persistence import Trade logger = logging.getLogger(__name__) class UziChan2(IStrategy): INTERFACE_VERSION = 3 minimal_roi = {'0': 0.1} stoploss = -0.1 timeframe = '1m' def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float, current_profit: float, **kwargs): dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) if current_profit * 100 > 1: logger.info(f'custom sell for {pair} at {current_rate}') return 'sell_1.2pc' return None def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['perc'] = (dataframe['high'] - dataframe['low']) / dataframe['low'] * 100 dataframe['avg3_perc'] = ta.EMA(dataframe['perc'], 3) dataframe['perc_norm'] = (dataframe['perc'] - dataframe['perc'].rolling(50).min()) / (dataframe['perc'].rolling(50).max() - dataframe['perc'].rolling(50).min()) # Uzirox's channel prezzo periodo = 15 dataframe['uc_mid'] = pta.ssf(dataframe['close'], 5) dataframe['uc_stdv'] = ta.STDDEV(dataframe['uc_mid'], periodo).round(5) dataframe['uc_low'] = ta.EMA(dataframe['uc_mid'] - dataframe['uc_stdv'], 3).round(5) dataframe['uc_up'] = ta.EMA(dataframe['uc_mid'] + dataframe['uc_stdv'], 3).round(5) dataframe['co'] = ta.ADOSC(dataframe, fastperiod=30, slowperiod=100).round(3) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[((dataframe['close'] < dataframe['uc_low']) | (dataframe['open'] < dataframe['uc_low'])) & (dataframe['co'] > dataframe['co'].shift()), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[(dataframe['high'] > dataframe['uc_up']) & (dataframe['co'] > dataframe['co'].shift()), 'exit_long'] = 1 return dataframe class UziChanTB2(UziChan2): process_only_new_candles = True custom_info_trail_buy = dict() custom_info_trail_sell = dict() # Trailing buy parameters trailing_buy_order_enabled = True trailing_sell_order_enabled = True #trailing_expire_seconds = 1800 #NOTE 5m timeframe trailing_expire_seconds = 1800 / 5 #NOTE 1m timeframe #trailing_expire_seconds = 1800*3 #NOTE 15m timeframe # If the current candle goes above min_uptrend_trailing_profit % before trailing_expire_seconds_uptrend seconds, buy the coin trailing_buy_uptrend_enabled = True trailing_sell_uptrend_enabled = True trailing_expire_seconds_uptrend = 90 min_uptrend_trailing_profit = 0.02 debug_mode = True trailing_buy_max_stop = 0.02 # stop trailing buy if current_price > starting_price * (1+trailing_buy_max_stop) trailing_buy_max_buy = 0.0 # buy if price between uplimit (=min of serie (current_price * (1 + trailing_buy_offset())) and (start_price * 1+trailing_buy_max_buy)) trailing_sell_max_stop = 0.02 # stop trailing sell if current_price < starting_price * (1+trailing_buy_max_stop) trailing_sell_max_sell = 0.0 # sell if price between downlimit (=max of serie (current_price * (1 + trailing_sell_offset())) and (start_price * 1+trailing_sell_max_sell)) abort_trailing_when_sell_signal_triggered = True init_trailing_buy_dict = {'trailing_buy_order_started': False, 'trailing_buy_order_uplimit': 0, 'start_trailing_price': 0, 'enter_tag': None, 'start_trailing_time': None, 'offset': 0, 'allow_trailing': False} init_trailing_sell_dict = {'trailing_sell_order_started': False, 'trailing_sell_order_downlimit': 0, 'start_trailing_sell_price': 0, 'sell_tag': None, 'start_trailing_time': None, 'offset': 0, 'allow_sell_trailing': False} def trailing_buy(self, pair, reinit=False): # returns trailing buy info for pair (init if necessary) if not pair in self.custom_info_trail_buy: self.custom_info_trail_buy[pair] = dict() if reinit or not 'trailing_buy' in self.custom_info_trail_buy[pair]: self.custom_info_trail_buy[pair]['trailing_buy'] = self.init_trailing_buy_dict.copy() return self.custom_info_trail_buy[pair]['trailing_buy'] def trailing_sell(self, pair, reinit=False): # returns trailing sell info for pair (init if necessary) if not pair in self.custom_info_trail_sell: self.custom_info_trail_sell[pair] = dict() if reinit or not 'trailing_sell' in self.custom_info_trail_sell[pair]: self.custom_info_trail_sell[pair]['trailing_sell'] = self.init_trailing_sell_dict.copy() return self.custom_info_trail_sell[pair]['trailing_sell'] def trailing_buy_info(self, pair: str, current_price: float): # current_time live, dry run current_time = datetime.now(timezone.utc) if not self.debug_mode: return trailing_buy = self.trailing_buy(pair) duration = 0 try: duration = current_time - trailing_buy['start_trailing_time'] except TypeError: duration = 0 finally: logger.info(f"pair: {pair} : start: {trailing_buy['start_trailing_price']:.4f}, duration: {duration}, current: {current_price:.4f}, uplimit: {trailing_buy['trailing_buy_order_uplimit']:.4f}, profit: {self.current_trailing_buy_profit_ratio(pair, current_price) * 100:.2f}%, offset: {trailing_buy['offset']}") def trailing_sell_info(self, pair: str, current_price: float): # current_time live, dry run current_time = datetime.now(timezone.utc) if not self.debug_mode: return trailing_sell = self.trailing_sell(pair) duration = 0 try: duration = current_time - trailing_sell['start_trailing_time'] except TypeError: duration = 0 finally: logger.info(f"'\x1b[36m'SELL: pair: {pair} : start: {trailing_sell['start_trailing_sell_price']:.4f}, duration: {duration}, current: {current_price:.4f}, downlimit: {trailing_sell['trailing_sell_order_downlimit']:.4f}, profit: {self.current_trailing_sell_profit_ratio(pair, current_price) * 100:.2f}%, offset: {trailing_sell['offset']}") def current_trailing_buy_profit_ratio(self, pair: str, current_price: float) -> float: trailing_buy = self.trailing_buy(pair) if trailing_buy['trailing_buy_order_started']: return (trailing_buy['start_trailing_price'] - current_price) / trailing_buy['start_trailing_price'] else: return 0 def current_trailing_sell_profit_ratio(self, pair: str, current_price: float) -> float: trailing_sell = self.trailing_sell(pair) if trailing_sell['trailing_sell_order_started']: return (current_price - trailing_sell['start_trailing_sell_price']) / trailing_sell['start_trailing_sell_price'] #return 0-((trailing_sell['start_trailing_sell_price'] - current_price) / trailing_sell['start_trailing_sell_price']) else: return 0 def trailing_buy_offset(self, dataframe, pair: str, current_price: float): # return rebound limit before a buy in % of initial price, function of current price # return None to stop trailing buy (will start again at next buy signal) # return 'forcebuy' to force immediate buy # (example with 0.5%. initial price : 100 (uplimit is 100.5), 2nd price : 99 (no buy, uplimit updated to 99.5), 3price 98 (no buy uplimit updated to 98.5), 4th price 99 -> BUY current_trailing_profit_ratio = self.current_trailing_buy_profit_ratio(pair, current_price) last_candle = dataframe.iloc[-1] adapt = last_candle['perc_norm'].round(5) default_offset = 0.0045 * (1 + adapt) #NOTE: default_offset 0.0045 <--> 0.009 trailing_buy = self.trailing_buy(pair) if not trailing_buy['trailing_buy_order_started']: return default_offset # example with duration and indicators # dry run, live only last_candle = dataframe.iloc[-1] current_time = datetime.now(timezone.utc) trailing_duration = current_time - trailing_buy['start_trailing_time'] if trailing_duration.total_seconds() > self.trailing_expire_seconds: if current_trailing_profit_ratio > 0 and last_candle['enter_long'] == 1: # more than 1h, price under first signal, buy signal still active -> buy return 'forcebuy' else: # wait for next signal return None elif self.trailing_buy_uptrend_enabled and trailing_duration.total_seconds() < self.trailing_expire_seconds_uptrend and (current_trailing_profit_ratio < -1 * self.min_uptrend_trailing_profit): # less than 90s and price is rising, buy return 'forcebuy' if current_trailing_profit_ratio < 0: # current price is higher than initial price return default_offset trailing_buy_offset = {0.06: 0.02, 0.03: 0.01, 0: default_offset} for key in trailing_buy_offset: if current_trailing_profit_ratio > key: return trailing_buy_offset[key] return default_offset def trailing_sell_offset(self, dataframe, pair: str, current_price: float): # return rebound limit before a buy in % of initial price, function of current price # return None to stop trailing buy (will start again at next buy signal) # return 'forcebuy' to force immediate buy # (example with 0.5%. initial price : 100 (uplimit is 100.5), 2nd price : 99 (no buy, uplimit updated to 99.5), 3price 98 (no buy uplimit updated to 98.5), 4th price 99 -> BUY current_trailing_sell_profit_ratio = self.current_trailing_sell_profit_ratio(pair, current_price) last_candle = dataframe.iloc[-1] adapt = last_candle['perc_norm'].round(5) default_offset = 0.003 * (1 + adapt) #NOTE: default_offset 0.003 <--> 0.006 trailing_sell = self.trailing_sell(pair) if not trailing_sell['trailing_sell_order_started']: return default_offset # example with duration and indicators # dry run, live only last_candle = dataframe.iloc[-1] current_time = datetime.now(timezone.utc) trailing_duration = current_time - trailing_sell['start_trailing_time'] if trailing_duration.total_seconds() > self.trailing_expire_seconds: if current_trailing_sell_profit_ratio > 0 and last_candle['exit_long'] != 0: # more than 1h, price over first signal, sell signal still active -> sell return 'forcesell' else: # wait for next signal return None elif self.trailing_sell_uptrend_enabled and trailing_duration.total_seconds() < self.trailing_expire_seconds_uptrend and (current_trailing_sell_profit_ratio < -1 * self.min_uptrend_trailing_profit): # less than 90s and price is falling, sell return 'forcesell' if current_trailing_sell_profit_ratio > 0: # current price is lower than initial price return default_offset # 0.06: 0.02, # 0.03: 0.01, trailing_sell_offset = {0.1: default_offset} for key in trailing_sell_offset: if current_trailing_sell_profit_ratio < key: return trailing_sell_offset[key] return default_offset # end of trailing sell parameters # ----------------------------------------------------- def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe = super().populate_indicators(dataframe, metadata) self.trailing_buy(metadata['pair']) self.trailing_sell(metadata['pair']) return dataframe def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, time_in_force: str, **kwargs) -> bool: val = super().confirm_trade_entry(pair, order_type, amount, rate, time_in_force, **kwargs) if val: if self.trailing_buy_order_enabled and self.config['runmode'].value in ('live', 'dry_run'): val = False dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) if len(dataframe) >= 1: last_candle = dataframe.iloc[-1].squeeze() current_price = rate trailing_buy = self.trailing_buy(pair) trailing_buy_offset = self.trailing_buy_offset(dataframe, pair, current_price) if trailing_buy['allow_trailing']: if not trailing_buy['trailing_buy_order_started'] and last_candle['enter_long'] == 1: # start trailing buy trailing_buy['trailing_buy_order_started'] = True trailing_buy['trailing_buy_order_uplimit'] = last_candle['close'] trailing_buy['start_trailing_price'] = last_candle['close'] trailing_buy['enter_tag'] = last_candle['enter_tag'] trailing_buy['start_trailing_time'] = datetime.now(timezone.utc) trailing_buy['offset'] = 0 self.trailing_buy_info(pair, current_price) logger.info(f"start trailing buy for {pair} at {last_candle['close']}") elif trailing_buy['trailing_buy_order_started']: if trailing_buy_offset == 'forcebuy': # buy in custom conditions val = True ratio = '%.2f' % (self.current_trailing_buy_profit_ratio(pair, current_price) * 100) self.trailing_buy_info(pair, current_price) logger.info(f'price OK for {pair} ({ratio} %, {current_price}), order may not be triggered if all slots are full') elif trailing_buy_offset is None: # stop trailing buy custom conditions self.trailing_buy(pair, reinit=True) logger.info(f'STOP trailing buy for {pair} because "trailing buy offset" returned None') elif current_price < trailing_buy['trailing_buy_order_uplimit']: # update uplimit old_uplimit = trailing_buy['trailing_buy_order_uplimit'] self.custom_info_trail_buy[pair]['trailing_buy']['trailing_buy_order_uplimit'] = min(current_price * (1 + trailing_buy_offset), self.custom_info_trail_buy[pair]['trailing_buy']['trailing_buy_order_uplimit']) self.custom_info_trail_buy[pair]['trailing_buy']['offset'] = trailing_buy_offset self.trailing_buy_info(pair, current_price) logger.info(f"update trailing buy for {pair} at {old_uplimit} -> {self.custom_info_trail_buy[pair]['trailing_buy']['trailing_buy_order_uplimit']}") elif current_price < trailing_buy['start_trailing_price'] * (1 + self.trailing_buy_max_buy): # buy ! current price > uplimit && lower thant starting price val = True ratio = '%.2f' % (self.current_trailing_buy_profit_ratio(pair, current_price) * 100) self.trailing_buy_info(pair, current_price) logger.info(f"current price ({current_price}) > uplimit ({trailing_buy['trailing_buy_order_uplimit']}) and lower than starting price price ({trailing_buy['start_trailing_price'] * (1 + self.trailing_buy_max_buy)}). OK for {pair} ({ratio} %), order may not be triggered if all slots are full") elif current_price > trailing_buy['start_trailing_price'] * (1 + self.trailing_buy_max_stop): # stop trailing buy because price is too high self.trailing_buy(pair, reinit=True) self.trailing_buy_info(pair, current_price) logger.info(f'STOP trailing buy for {pair} because of the price is higher than starting price * {1 + self.trailing_buy_max_stop}') else: # uplimit > current_price > max_price, continue trailing and wait for the price to go down self.trailing_buy_info(pair, current_price) logger.info(f'price too high for {pair} !') else: logger.info(f'Wait for next buy signal for {pair}') if val == True: self.trailing_buy_info(pair, rate) self.trailing_buy(pair, reinit=True) logger.info(f'STOP trailing buy for {pair} because I buy it') return val def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float, rate: float, time_in_force: str, exit_reason: str, **kwargs) -> bool: val = super().confirm_trade_exit(pair, trade, order_type, amount, rate, time_in_force, exit_reason, **kwargs) if val: if self.trailing_sell_order_enabled and self.config['runmode'].value in ('live', 'dry_run'): val = False dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe) if len(dataframe) >= 1: last_candle = dataframe.iloc[-1].squeeze() current_price = rate trailing_sell = self.trailing_sell(pair) trailing_sell_offset = self.trailing_sell_offset(dataframe, pair, current_price) if trailing_sell['allow_sell_trailing']: if not trailing_sell['trailing_sell_order_started'] and last_candle['exit_long'] != 0: trailing_sell['trailing_sell_order_started'] = True trailing_sell['trailing_sell_order_downlimit'] = last_candle['close'] trailing_sell['start_trailing_sell_price'] = last_candle['close'] trailing_sell['sell_tag'] = last_candle['sell_tag'] trailing_sell['start_trailing_time'] = datetime.now(timezone.utc) trailing_sell['offset'] = 0 self.trailing_sell_info(pair, current_price) logger.info(f"start trailing sell for {pair} at {last_candle['close']}") elif trailing_sell['trailing_sell_order_started']: if trailing_sell_offset == 'forcesell': # sell in custom conditions val = True ratio = '%.2f' % (self.current_trailing_sell_profit_ratio(pair, current_price) * 100) self.trailing_sell_info(pair, current_price) logger.info(f'FORCESELL for {pair} ({ratio} %, {current_price})') elif trailing_sell_offset is None: # stop trailing sell custom conditions self.trailing_sell(pair, reinit=True) logger.info(f'STOP trailing sell for {pair} because "trailing sell offset" returned None') elif current_price > trailing_sell['trailing_sell_order_downlimit']: # update downlimit old_downlimit = trailing_sell['trailing_sell_order_downlimit'] self.custom_info_trail_sell[pair]['trailing_sell']['trailing_sell_order_downlimit'] = max(current_price * (1 - trailing_sell_offset), self.custom_info_trail_sell[pair]['trailing_sell']['trailing_sell_order_downlimit']) self.custom_info_trail_sell[pair]['trailing_sell']['offset'] = trailing_sell_offset self.trailing_sell_info(pair, current_price) logger.info(f"update trailing sell for {pair} at {old_downlimit} -> {self.custom_info_trail_sell[pair]['trailing_sell']['trailing_sell_order_downlimit']}") elif current_price > trailing_sell['start_trailing_sell_price'] * (1 - self.trailing_sell_max_sell): # sell! current price < downlimit && higher than starting price val = True ratio = '%.2f' % (self.current_trailing_sell_profit_ratio(pair, current_price) * 100) self.trailing_sell_info(pair, current_price) logger.info(f"current price ({current_price}) < downlimit ({trailing_sell['trailing_sell_order_downlimit']}) but higher than starting price ({trailing_sell['start_trailing_sell_price'] * (1 + self.trailing_sell_max_sell)}). OK for {pair} ({ratio} %)") elif current_price < trailing_sell['start_trailing_sell_price'] * (1 - self.trailing_sell_max_stop): # stop trailing, sell fast, price too low val = True self.trailing_sell_info(pair, current_price) logger.info(f'STOP trailing sell for {pair} because of the price is much lower than starting price * {1 + self.trailing_sell_max_stop}') else: # uplimit > current_price > max_price, continue trailing and wait for the price to go down self.trailing_sell_info(pair, current_price) logger.info(f'price too low for {pair} !') else: logger.info(f'Wait for next sell signal for {pair}') if val == True: self.trailing_sell_info(pair, rate) self.trailing_sell(pair, reinit=True) logger.info(f'STOP trailing sell for {pair} because I SOLD it') if exit_reason != 'exit_signal': val = True return val def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe = super().populate_entry_trend(dataframe, metadata) if self.trailing_buy_order_enabled and self.config['runmode'].value in ('live', 'dry_run'): last_candle = dataframe.iloc[-1].squeeze() trailing_buy = self.trailing_buy(metadata['pair']) if last_candle['enter_long'] == 1: if not trailing_buy['trailing_buy_order_started']: open_trades = Trade.get_trades([Trade.pair == metadata['pair'], Trade.is_open.is_(True)]).all() if not open_trades: logger.info(f"Set 'allow_trailing' to True for {metadata['pair']} to start trailing!!!") # self.custom_info_trail_buy[metadata['pair']]['trailing_buy']['allow_trailing'] = True trailing_buy['allow_trailing'] = True initial_buy_tag = last_candle['enter_tag'] if 'enter_tag' in last_candle else 'buy signal' dataframe.loc[:, 'enter_tag'] = f"{initial_buy_tag} (start trail price {last_candle['close']})" elif trailing_buy['trailing_buy_order_started'] == True: logger.info(f"Continue trailing for {metadata['pair']}. Manually trigger buy signal!!") dataframe.loc[:, 'enter_long'] = 1 dataframe.loc[:, 'enter_tag'] = trailing_buy['enter_tag'] return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe = super().populate_exit_trend(dataframe, metadata) if self.trailing_buy_order_enabled and self.abort_trailing_when_sell_signal_triggered and (self.config['runmode'].value in ('live', 'dry_run')): last_candle = dataframe.iloc[-1].squeeze() if last_candle['exit_long'] != 0: trailing_buy = self.trailing_buy(metadata['pair']) if trailing_buy['trailing_buy_order_started']: logger.info(f"Sell signal for {metadata['pair']} is triggered!!! Abort trailing") self.trailing_buy(metadata['pair'], reinit=True) if self.trailing_sell_order_enabled and self.config['runmode'].value in ('live', 'dry_run'): last_candle = dataframe.iloc[-1].squeeze() trailing_sell = self.trailing_sell(metadata['pair']) if last_candle['exit_long'] != 0: if not trailing_sell['trailing_sell_order_started']: open_trades = Trade.get_trades([Trade.pair == metadata['pair'], Trade.is_open.is_(True)]).all() #if not open_trades: if open_trades: logger.info(f"Set 'allow_SELL_trailing' to True for {metadata['pair']} to start *SELL* trailing") # self.custom_info_trail_buy[metadata['pair']]['trailing_buy']['allow_trailing'] = True trailing_sell['allow_sell_trailing'] = True initial_sell_tag = last_candle['sell_tag'] if 'sell_tag' in last_candle else 'sell signal' dataframe.loc[:, 'sell_tag'] = f"{initial_sell_tag} (start trail price {last_candle['close']})" elif trailing_sell['trailing_sell_order_started'] == True: logger.info(f"Continue trailing for {metadata['pair']}. Manually trigger sell signal!") dataframe.loc[:, 'exit_long'] = 1 dataframe.loc[:, 'sell_tag'] = trailing_sell['sell_tag'] return dataframe plot_config = {'main_plot': {'uc_up': {'color': 'gray'}, 'uc_mid': {'color': 'green'}, 'uc_low': {'color': 'gray'}}, 'subplots': {}} |
Strategy League — fixed backtest that feeds the ranking
The fixed-params backtest (33 pairs · 20210101-20260101) — the only run that feeds the Strategy League ranking.
Backtests — over a market period
Backtest this strategy over a chosen crypto-cycle period. These don't affect the League ranking, and need that period's candle data downloaded.
Log in or sign up to run backtests.
| Period | Range | Total % | Win % | Max DD | Trades | |
|---|---|---|---|---|---|---|
| 2020 · DeFi Summer & Pre-Halving Rally | 20200101-20210101 | not run | ||||
| 2021 · Institutional Bull Market | 20210101-20220101 | not run | ||||
| 2022 · Post-Bull Crash & Macro Tightening | 20220101-20230101 | not run | ||||
| 2023–2024 · Recovery & ETF Anticipation | 20230101-20250101 | not run | ||||
| 2025–2026 · Current Cycle | 20250101-20260101 | not run | ||||
Walk forward
Out-of-sample backtest on recent data · 33 pairs · 20260101-20260701.
Backtest trust check
Static source analysis — instant, does not run the strategy. Flags future-data leaks, backtest-realism problems, and indicators worth a second look.
Lookahead analysis
freqtrade lookahead-analysis: detects strategies peeking at future candles.