IchimokuStrategy
♡
Basics
mode: spot
timeframe: 3m
outdated
Settings
stoploss: -0.1
has minimal roi
Indicators
Ichimoku
talib
technical
Concepts
trend_following
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 | from freqtrade.strategy.interface import IStrategy from pandas import DataFrame from technical.indicators import accumulation_distribution from technical.util import resample_to_interval, resampled_merge import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib import numpy from technical.indicators import ichimoku class IchimokuStrategy(IStrategy): """ the Kijun Sen Cross signal occurs when the price crosses the Kijun Sen (Standard line). A bullish signal occurs when the price crosses from below to above the Kijun Sen and the cross is above the Kumo. A bearish signal occurs when the price crosses from above to below the Kijun Sen and the cross is below the Kumo. """ minimal_roi = { "0": 100 } stoploss = -0.10 ticker_interval = '3m' order_types = { 'entry': 'market', 'exit': 'market', 'stoploss': 'market', 'stoploss_on_exchange': False } order_time_in_force = { 'entry': 'gtc', 'exit': 'gtc' } def informative_pairs(self): return [] def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: ichi = ichimoku(dataframe, conversion_line_period=20, base_line_periods=60, laggin_span=120, displacement=30) dataframe['tenkan'] = ichi['tenkan_sen'] dataframe['kijun'] = ichi['kijun_sen'] dataframe['senkou_a'] = ichi['senkou_span_a'] dataframe['senkou_b'] = ichi['senkou_span_b'] dataframe['cloud_green'] = ichi['cloud_green'] dataframe['cloud_red'] = ichi['cloud_red'] return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (qtpylib.crossed_above(dataframe['close'], dataframe['kijun'])) & (dataframe['close'] > dataframe['senkou_a']) & (dataframe['close'] > dataframe['senkou_b']) & (dataframe['cloud_red'] == True) ), 'entry'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (qtpylib.crossed_above(dataframe['close'], dataframe['kijun'])) & (dataframe['close'] < dataframe['senkou_a']) & (dataframe['close'] < dataframe['senkou_b']) & (dataframe['cloud_green'] == True) ), 'exit'] = 1 return dataframe |
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.
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| 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.