| name | bollinger-reverter-4h |
| description | Use when writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter, range trader, chop strategy, ADX<25 mean reversion, band-fade with a minimal_roi ladder. Long-or-short on 2-sigma band touches with RSI confirmation. Validated on BTC/ETH/SOL/DOGE; numbers and the exact ROI ladder are in the body. |
| metadata | {"version":"0.1.0","updated":"2026-05-18T00:00:00.000Z"} |
Bollinger Reverter 4h
Symmetric mean-reversion strategy on the 4h timeframe. Long-or-short on band touches, gated to range regimes via ADX. Validated across BTC/ETH/SOL/DOGE over 162 days.
Searchable under: mean reversion, bollinger band, range trader, chop strategy, ADX filter.
Backtest evidence
| Config | Trades | Win rate | Profit | Max DD |
|---|
| BTC/USDC:USDC, 162d | 18 | 72.2% | +8.14% | 10% |
| BTC/USDC:USDC, second-half / chop (80d) | 8 | 100% | +9.88% | 0% |
| BTC/USDC:USDC, first-half / strong bear (82d) | 10 | 50% | -1.75% | 10% |
| Multi-pair (BTC/ETH/SOL/DOGE), 162d | 84 | 65.5% | +8.77% | 18.5% |
Per-pair breakdown (multi-pair 162d):
| Pair | Trades | Win | Profit |
|---|
| BTC/USDC:USDC | 29 | 72% | +3.76% |
| ETH/USDC:USDC | 19 | 74% | +4.39% |
| SOL/USDC:USDC | 15 | 60% | +1.27% |
| DOGE/USDC:USDC | 21 | 52% | -0.65% |
3 of 4 majors profitable, DOGE marginally negative. Generalizes well; not BTC-specific.
Thesis
When the market is range-bound (ADX < 25), price touching the upper or lower Bollinger Band is statistically likely to revert to the midline. Tight ROI ladder takes profit fast since mean-reversion targets are small; tight stop prevents the position from holding if the band touch turns into a trend break.
Mechanics
- Pair: validated on majors; extend to any pair with sustained 24h volume > $50M
- Timeframe: 4h
- Indicators: 20-bar Bollinger Bands (2σ), RSI(14), ADX(14)
- Entry short:
close > upper_band AND RSI > 65 AND ADX < 25
- Entry long:
close < lower_band AND RSI < 35 AND ADX < 25
- Exit short:
close < bb_mid
- Exit long:
close > bb_mid
- Stops: -2% hard stop
- ROI ladder: 2.5% immediate, 1.5% after 4h, 0.5% after 12h, breakeven after 24h
- No trailing stop (mean reversion targets are short — let ROI or signal-exit fire)
Full strategy code
from freqtrade.strategy import IStrategy
import pandas as pd
import talib.abstract as ta
class BollingerReverter4hStrategy(IStrategy):
INTERFACE_VERSION = 3
timeframe = "4h"
can_short = True
stoploss = -0.02
trailing_stop = False
minimal_roi = {
"0": 0.025,
"240": 0.015,
"720": 0.005,
"1440": 0,
}
process_only_new_candles = True
startup_candle_count = 60
use_exit_signal = True
def populate_indicators(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
bb = ta.BBANDS(dataframe, timeperiod=20, nbdevup=2.0, nbdevdn=2.0)
dataframe["bb_upper"] = bb["upperband"]
dataframe["bb_mid"] = bb["middleband"]
dataframe["bb_lower"] = bb["lowerband"]
dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
dataframe["adx"] = ta.ADX(dataframe, timeperiod=)
dataframe
() -> pd.DataFrame:
cond_short = (
(dataframe[] > dataframe[])
& (dataframe[] > )
& (dataframe[] < )
)
dataframe.loc[cond_short, ] =
dataframe.loc[cond_short, ] =
cond_long = (
(dataframe[] < dataframe[])
& (dataframe[] < )
& (dataframe[] < )
)
dataframe.loc[cond_long, ] =
dataframe.loc[cond_long, ] =
dataframe
() -> pd.DataFrame:
dataframe.loc[dataframe[] < dataframe[], ] =
dataframe.loc[dataframe[] > dataframe[], ] =
dataframe
Reference config (multi-pair)
{
"exchange": {
"name": "hyperliquid",
"pair_whitelist": ["BTC/USDC:USDC", "ETH/USDC:USDC", "SOL/USDC:USDC", "DOGE/USDC:USDC"]
},
"stake_currency": "USDC",
"stake_amount": 75,
"dry_run_wallet": {"USDC": 350},
"timeframe": "4h",
"max_open_trades": 4,
"minimal_roi": {"0": 100.0},
"stoploss": -0.02,
"trading_mode":
Strategy-level minimal_roi overrides config-level — the ROI ladder is what makes this work.
Honest framing
The 100% second-half BTC win rate is partly small sample (8 trades). The full-period multi-pair result (+8.77%, 84 trades, 65.5% win) is the more credible expectation. Range-bound regimes are when this prints; in strong trends it modestly loses (-1.75% on BTC during the first-half strong bear) because band touches keep continuing rather than reverting.
In any window with mixed regimes, the strategy should be net positive because the chop periods dominate by count.
The DOGE result (-0.65%) is the failure case — meme-coin volatility breaks more bands than reverts to them. Use this strategy on majors, not meme pairs.
Tunables
| Parameter | Range | Effect |
|---|
| BB period | 18 - 24 | Length of mean-reversion window |
| BB σ | 1.8 - 2.5 | Wider = rarer signals, deeper reversion |
| RSI confirmation | 60-70 / 30-40 | Confirms exhaustion at band edge |
| ADX cutoff | 20 - 30 | Below = range regime; above = trend (skip) |
| ROI tier 0 | 0.020 - 0.030 | Initial take-profit |
| Stop | -0.015 to -0.025 | Tight enough that one trend break doesn't erase the lifetime edge |
Known failure modes
- Regime transition: when chop turns into trend mid-trade, the band-touch-revert signal becomes a band-break-continuation. Stops should fire fast; this is what the -2% stop is for
- Meme/low-cap pairs: bands break more than they revert. Restrict to majors
- News spikes: a sudden 5%+ move blows through multiple bands; the stop will fire but execution slippage hurts. Consider pausing during scheduled macro events
Pairing
- Designed to coexist with
donchian-strong-regime — they fire on mutually exclusive regimes (ADX < 25 here, regime-strong gate there)
- Supersedes the prior 1h variant of
mean-reversion
Deployment recommendation
Run as its own sub-account with stake_amount sized so 4× max_open_trades fits within the wallet plus 1.5× buffer. Multi-pair allocation across BTC/ETH/SOL is the validated default.
