15 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 | # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # flake8: noqa: F401 # isort: skip_file # --- Do not remove these imports --- from freqtrade.constants import Config from freqtrade.persistence import Trade from freqtrade.strategy import IStrategy, informative, IntParameter, DecimalParameter from freqtrade.optimize.space import Categorical, Dimension, Integer, SKDecimal from datetime import datetime, timedelta from pandas import DataFrame from typing import Dict, List, Optional, Union, Tuple import talib.abstract as ta from technical import qtpylib class ZaratustraV14(IStrategy): # Parameters INTERFACE_VERSION = 3 timeframe = '5m' can_short = True use_exit_signal = False exit_profit_only = True # ROI table: minimal_roi = {} # Stoploss: stoploss = -0.16 # Trailing stop: trailing_stop = True trailing_stop_positive = 0.012 trailing_stop_positive_offset = 0.107 trailing_only_offset_is_reached = True # Max Open Trades: max_open_trades = 9 # Hyper Parameters base_atr = DecimalParameter(0.00, 1.00, default=0.2, decimals=2, space="buy") @property def plot_config(self): plot_config = {} plot_config['main_plot'] = {} plot_config['subplots'] = { "DI": { 'dx' : {'color': 'yellow'}, 'adx': {'color': 'orange'}, 'pdi': {'color': 'green'}, 'mdi': {'color': 'red'}, }, "ATR": { 'atr': {'color': 'red'} } } return plot_config def leverage(self, pair: str, current_time: "datetime", current_rate: float, proposed_leverage: float, max_leverage: float, side: str, **kwargs,) -> float: return 10 def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['atr'] = ta.ATR(dataframe) dataframe['dx'] = ta.DX(dataframe) dataframe['adx'] = ta.ADX(dataframe) dataframe['pdi'] = ta.PLUS_DI(dataframe) dataframe['mdi'] = ta.MINUS_DI(dataframe) bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) dataframe['bb_lowerband'] = bollinger['lower'] dataframe['bb_middleband'] = bollinger['mid'] dataframe['bb_upperband'] = bollinger['upper'] return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['dx'] > dataframe['mdi']) & (dataframe['adx'] > dataframe['mdi']) & (dataframe['pdi'] > dataframe['mdi']) & (dataframe['atr'] > self.base_atr.value) ), ['enter_long', 'enter_tag'] ] = (1, 'Long DI enter') dataframe.loc[ ( qtpylib.crossed_above(dataframe['close'], dataframe['bb_upperband']) ), ['enter_long', 'enter_tag'] ] = (1, 'Long Bollinger enter') dataframe.loc[ ( (dataframe['dx'] > dataframe['mdi']) & (dataframe['adx'] > dataframe['pdi']) & (dataframe['mdi'] > dataframe['pdi']) & (dataframe['atr'] > self.base_atr.value) ), ['enter_short', 'enter_tag'] ] = (1, 'Short DI enter') dataframe.loc[ ( qtpylib.crossed_below(dataframe['close'], dataframe['bb_lowerband']) ), ['enter_short', 'enter_tag'] ] = (1, 'Short Bollinger enter') return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: return dataframe |
Strategy League — fixed backtest that feeds the ranking
Export report Freqtrade logsRun finished · took 1215.5s
ℹ️ This strategy uses a trailing stop — freqtrade only
re-checks these once per 5m candle by default, not against the price movement within it.
For a more accurate read, re-run this backtest locally with --timeframe-detail 1m. Freqle doesn't do this for every check here: multiplying every
League/sweep backtest by a finer detail timeframe is more compute than the sandbox can sustain
across every indexed strategy. why this matters →
- statistically significant edge (p=0.00)
- 100% of resampled runs stayed profitable
- profitable across 100% of rolling 3-month windows
- comfortably beat buy-and-hold
Resampling the trade sequence 2,000× shows the spread of results this edge could plausibly produce — separating a dependable strategy from one that got lucky once.
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Monthly breakdown
| Month | Regime | Trades | Profit % | Avg % | Win | Loss | Win % | DD % | Avg dur |
|---|---|---|---|---|---|---|---|---|---|
| Jan 2026 | bullish trending low vol | 10 | -3.68 | -3.68 | 2 | 8 | 20.0 | -0.08 | 15h 52m |
| Dec 2025 | bearish trending low vol | 1748 | +381.25 | 2.18 | 1137 | 611 | 65.0 | -0.3 | 4h 12m |
| Nov 2025 | bearish trending high vol | 3001 | +307.02 | 1.02 | 1803 | 1198 | 60.1 | -0.36 | 2h 19m |
| Oct 2025 | bearish trending low vol | 2776 | +483.22 | 1.76 | 1689 | 1087 | 60.8 | -0.35 | 2h 39m |
| Sep 2025 | bullish choppy low vol | 1226 | +40.58 | 0.33 | 721 | 505 | 58.8 | -0.28 | 5h 50m |
| Aug 2025 | bearish choppy low vol | 2148 | +233.96 | 1.09 | 1333 | 815 | 62.1 | -0.21 | 3h 23m |
| Jul 2025 | bullish choppy low vol | 2309 | +249.95 | 1.08 | 1431 | 878 | 62.0 | -0.16 | 3h 15m |
| Jun 2025 | bearish choppy low vol | 1708 | +246.81 | 1.45 | 1066 | 642 | 62.4 | -0.16 | 4h 07m |
| May 2025 | bullish trending low vol | 2415 | +396.17 | 1.64 | 1537 | 878 | 63.6 | -0.24 | 3h 00m |
| Apr 2025 | bullish choppy low vol | 2863 | +469.78 | 1.64 | 1805 | 1058 | 63.0 | -0.34 | 2h 29m |
| Mar 2025 | bearish trending high vol | 3285 | +564.65 | 1.72 | 2047 | 1238 | 62.3 | -0.3 | 2h 12m |
| Feb 2025 | bearish trending low vol | 4073 | +781.98 | 1.93 | 2531 | 1542 | 62.1 | -0.27 | 1h 35m |
| Jan 2025 | bearish choppy low vol | 3724 | +567.35 | 1.53 | 2320 | 1404 | 62.3 | -0.3 | 1h 58m |
| Dec 2024 | bullish trending low vol | 5547 | +890.81 | 1.61 | 3398 | 2149 | 61.3 | -0.43 | 1h 18m |
| Nov 2024 | bullish trending low vol | 4757 | +496.53 | 1.04 | 2871 | 1886 | 60.4 | -0.42 | 1h 28m |
| Oct 2024 | bullish choppy low vol | 1539 | +130.97 | 0.85 | 939 | 600 | 61.0 | -0.18 | 4h 49m |
| Sep 2024 | bearish choppy low vol | 1482 | +311.79 | 2.11 | 969 | 513 | 65.4 | -0.11 | 4h 52m |
| Aug 2024 | bearish choppy high vol | 3165 | +675.30 | 2.14 | 1994 | 1171 | 63.0 | -0.33 | 2h 16m |
| Jul 2024 | bearish trending low vol | 2332 | +356.71 | 1.54 | 1448 | 884 | 62.1 | -0.22 | 3h 10m |
| Jun 2024 | bearish choppy low vol | 1511 | +357.15 | 2.37 | 909 | 602 | 60.2 | -0.43 | 4h 44m |
| May 2024 | bullish choppy high vol | 1732 | +165.17 | 0.95 | 1061 | 671 | 61.3 | -0.3 | 4h 14m |
| Apr 2024 | bearish choppy high vol | 3597 | +940.20 | 2.62 | 2233 | 1364 | 62.1 | -0.34 | 1h 59m |
| Mar 2024 | bullish trending high vol | 4891 | +608.50 | 1.25 | 2904 | 1987 | 59.4 | -0.34 | 1h 28m |
| Feb 2024 | bullish trending low vol | 1754 | +202.85 | 1.16 | 1055 | 699 | 60.1 | -0.2 | 3h 58m |
| Jan 2024 | bearish choppy high vol | 2790 | +561.21 | 2.02 | 1704 | 1086 | 61.1 | -0.35 | 2h 38m |
| Dec 2023 | bullish trending low vol | 2798 | +612.12 | 2.19 | 1752 | 1046 | 62.6 | -0.13 | 2h 44m |
| Nov 2023 | bullish trending low vol | 2727 | +575.20 | 2.11 | 1691 | 1036 | 62.0 | -0.16 | 2h 33m |
| Oct 2023 | bullish trending low vol | 1507 | +320.18 | 2.13 | 940 | 567 | 62.4 | -0.21 | 5h 00m |
| Sep 2023 | bearish choppy low vol | 821 | +76.25 | 0.93 | 490 | 331 | 59.7 | -0.26 | 8h 28m |
| Aug 2023 | bearish choppy low vol | 1165 | +526.16 | 4.52 | 746 | 419 | 64.0 | -0.2 | 6h 38m |
| Jul 2023 | bullish trending low vol | 1592 | +358.69 | 2.26 | 974 | 618 | 61.2 | -0.19 | 4h 25m |
| Jun 2023 | bullish trending low vol | 1956 | +719.99 | 3.68 | 1231 | 725 | 62.9 | -0.25 | 3h 41m |
| May 2023 | bearish choppy low vol | 935 | +164.09 | 1.76 | 574 | 361 | 61.4 | -0.2 | 7h 49m |
| Apr 2023 | bullish trending low vol | 1438 | +292.58 | 2.04 | 895 | 543 | 62.2 | -0.22 | 5h 00m |
| Mar 2023 | bullish trending high vol | 2631 | +495.60 | 1.89 | 1642 | 989 | 62.4 | -0.38 | 2h 45m |
| Feb 2023 | bullish trending low vol | 1905 | +366.99 | 1.93 | 1196 | 709 | 62.8 | -0.28 | 3h 28m |
| Jan 2023 | bullish trending low vol | 2495 | +405.06 | 1.63 | 1469 | 1026 | 58.9 | -0.55 | 2h 58m |
| Dec 2022 | bearish trending low vol | 1116 | +300.77 | 2.70 | 693 | 423 | 62.1 | -0.14 | 6h 31m |
| Nov 2022 | bearish trending high vol | 4466 | +767.29 | 1.72 | 2610 | 1856 | 58.4 | -0.56 | 1h 34m |
| Oct 2022 | bullish choppy low vol | 1501 | +375.83 | 2.51 | 978 | 523 | 65.2 | -0.22 | 4h 53m |
| Sep 2022 | bearish choppy high vol | 2661 | +361.59 | 1.36 | 1633 | 1028 | 61.4 | -0.54 | 2h 40m |
| Aug 2022 | bullish choppy high vol | 2861 | +589.83 | 2.06 | 1820 | 1041 | 63.6 | -0.31 | 2h 34m |
| Jul 2022 | bullish trending high vol | 4004 | +601.26 | 1.50 | 2447 | 1557 | 61.1 | -0.44 | 1h 49m |
| Jun 2022 | bearish trending high vol | 6669 | +1206.69 | 1.81 | 4028 | 2641 | 60.4 | -0.65 | 1h 01m |
| May 2022 | bearish trending high vol | 7217 | +1056.44 | 1.47 | 4286 | 2931 | 59.4 | -0.72 | 0h 57m |
| Apr 2022 | bearish choppy high vol | 2569 | +660.99 | 2.59 | 1680 | 889 | 65.4 | -0.66 | 2h 47m |
| Mar 2022 | bullish choppy high vol | 2917 | +348.88 | 1.21 | 1779 | 1138 | 61.0 | -0.71 | 2h 31m |
| Feb 2022 | bearish trending high vol | 3975 | +914.80 | 2.32 | 2557 | 1418 | 64.3 | -0.48 | 1h 40m |
| Jan 2022 | bearish trending high vol | 5023 | +1168.84 | 2.34 | 3178 | 1845 | 63.3 | -0.56 | 1h 25m |
| Dec 2021 | bearish trending high vol | 4489 | +854.72 | 1.92 | 2733 | 1756 | 60.9 | -1.63 | 1h 38m |
| Nov 2021 | bearish trending high vol | 3823 | +720.10 | 1.89 | 2365 | 1458 | 61.9 | -1.19 | 1h 51m |
| Oct 2021 | bullish trending high vol | 3488 | +552.24 | 1.59 | 2129 | 1359 | 61.0 | -1.01 | 2h 07m |
| Sep 2021 | bearish trending high vol | 6309 | +1067.46 | 1.70 | 3657 | 2652 | 58.0 | -2.02 | 1h 07m |
| Aug 2021 | bullish trending high vol | 4956 | +529.54 | 1.08 | 2979 | 1977 | 60.1 | -0.76 | 1h 28m |
| Jul 2021 | bullish trending high vol | 3982 | +669.68 | 1.69 | 2490 | 1492 | 62.5 | -0.98 | 1h 50m |
| Jun 2021 | bearish trending high vol | 7352 | +945.83 | 1.29 | 4429 | 2923 | 60.2 | -1.41 | 0h 55m |
| May 2021 | bearish trending high vol | 16436 | +2345.92 | 1.43 | 9258 | 7178 | 56.3 | -3.83 | 0h 24m |
| Apr 2021 | bearish choppy high vol | 9474 | +1080.76 | 1.14 | 5459 | 4015 | 57.6 | -4.37 | 0h 43m |
| Mar 2021 | bullish choppy high vol | 5323 | +612.21 | 1.16 | 3183 | 2140 | 59.8 | -2.59 | 1h 22m |
| Feb 2021 | bullish trending high vol | 11942 | +1657.51 | 1.39 | 6799 | 5143 | 56.9 | -6.68 | 0h 31m |
| Jan 2021 | bullish trending high vol | 10785 | +1525.55 | 1.42 | 6207 | 4578 | 57.6 | -14.89 | 0h 36m |
Yearly breakdown
| Year | Trades | Profit % | Avg % | Win | Loss | Win % | DD % | Avg dur |
|---|---|---|---|---|---|---|---|---|
| 2026 | 10 | -3.68 | -3.68 | 2 | 8 | 20.0 | -0.08 | 15h 52m |
| 2025 | 31276 | +4722.72 | 1.51 | 19420 | 11856 | 62.1 | -0.36 | 2h 45m |
| 2024 | 35097 | +5697.19 | 1.63 | 21485 | 13612 | 61.2 | -0.43 | 2h 28m |
| 2023 | 21970 | +4912.91 | 2.24 | 13600 | 8370 | 61.9 | -0.55 | 3h 57m |
| 2022 | 44979 | +8353.21 | 1.86 | 27689 | 17290 | 61.6 | -0.72 | 1h 54m |
| 2021 | 88359 | +12561.52 | 1.43 | 51688 | 36671 | 58.5 | -14.89 | 0h 57m |
Trade charts — best 2 and worst 2 performing pairs (full OHLC candles are expensive to render for every pair)
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
no lookahead patterns · 4 thing(s) worth reviewing before trusting the numbers
| Line | Pattern | Detail | |
|---|---|---|---|
| 22 | review | no_signal_exits | use_exit_signal is False, minimal_roi is empty and populate_exit_trend returns the dataframe untouched -- the ONLY way out of a trade is the stoploss or the trailing stop. freqtrade's own docs warn that trailing-stop backtests are optimistic (within a candle it assumes price reached the high, ratcheting the trail, before reversing to trigger), so re-run with --timeframe-detail 1m before trusting the result |
| 23 | review | dead_exit_config | exit_profit_only only applies to exit SIGNALS, but use_exit_signal is False -- this setting has no effect |
| 17 | review | missing_startup_candles | uses recursive indicators (ADX, ATR, DX, MINUS_DI) but startup_candle_count is not set (default 0). Their value at a bar depends on all bars before it, so freqtrade trims no warmup and the backtest opens with unwarmed values that can't occur live. The longest lookback visible here is bollinger_bands(window=20), so it needs at least that many. Set it to a few times the longest period and confirm with `freqtrade recursive-analysis` |
| 78 | review | enter_tag_overwrite | enter_tag/exit_tag is written by 4 separate assignments -- they share one column and run in source order, so a row matching more than one condition keeps only the LAST tag. Per-tag statistics won't mean what they appear to |
ran by Ron · took s
Lookahead analysis
Freqtrade logsno lookahead bias detected
20 signal(s) analysed · 0 biased entries · 0 biased exits
ran by Ron · took 478.7s