MACD
♡
Basics
mode: spot
timeframe: 5m
interface version: 3
Settings
stoploss: -0.2741
has minimal roi
Indicators
CCI
MACD
talib
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 | from freqtrade.strategy.interface import IStrategy from typing import Dict, List from functools import reduce from pandas import DataFrame import talib.abstract as ta class MACD(IStrategy): INTERFACE_VERSION = 3 '\n\n author@: Gert Wohlgemuth\n\n idea:\n\n uptrend definition:\n MACD above MACD signal\n and CCI < -50\n\n downtrend definition:\n MACD below MACD signal\n and CCI > 100\n\n ' minimal_roi = {'0': 0.1858737982036954, '27': 0.02524445335072633, '80': 0.013912072159850514, '154': 0} stoploss = -0.27408960533563953 timeframe = '5m' def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: macd = ta.MACD(dataframe) dataframe['macd'] = macd['macd'] dataframe['macdsignal'] = macd['macdsignal'] dataframe['macdhist'] = macd['macdhist'] dataframe['cci'] = ta.CCI(dataframe) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Based on TA indicators, populates the buy signal for the given dataframe :param dataframe: DataFrame :return: DataFrame with buy column """ dataframe.loc[(dataframe['macd'] > dataframe['macdsignal']) & (dataframe['cci'] <= -205.0), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Based on TA indicators, populates the sell signal for the given dataframe :param dataframe: DataFrame :return: DataFrame with buy column """ dataframe.loc[(dataframe['macd'] < dataframe['macdsignal']) & (dataframe['cci'] >= 360.0), 'exit_long'] = 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.