# Bollinger Reverter 4h > Use when writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — anything described as BB reverter, range trader, chop strategy, ADX-gated mean reversion, band-fade with ROI ladder. Long-or-short on 2σ band touches with RSI confirmation, gated to ADX<25 range regimes. Validated +8.77%/65.5% win across BTC/ETH/SOL/DOGE over 162d; depends entirely on its minimal_roi ladder… - **Type:** Skill - **Install:** `agentstack add skill-superior-trade-superior-skills-bollinger-reverter-4h` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [Superior-Trade](https://agentstack.voostack.com/s/superior-trade) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [Superior-Trade](https://github.com/Superior-Trade) - **Source:** https://github.com/Superior-Trade/superior-skills/tree/main/skills/bollinger-reverter-4h ## Install ```sh agentstack add skill-superior-trade-superior-skills-bollinger-reverter-4h ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # 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 $50M - **Timeframe:** 4h - **Indicators:** 20-bar Bollinger Bands (2σ), RSI(14), ADX(14) - **Entry short:** `close > upper_band` AND `RSI > 65` AND `ADX 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 ```python 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, # take 2.5% immediately "240": 0.015, # 1.5% after 4 hours (1 bar) "720": 0.005, # 0.5% after 12 hours (3 bars) "1440": 0, # breakeven after 24 hours } 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=14) return dataframe def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame: cond_short = ( (dataframe["close"] > dataframe["bb_upper"]) & (dataframe["rsi"] > 65) & (dataframe["adx"] pd.DataFrame: dataframe.loc[dataframe["close"] dataframe["bb_mid"], "exit_long"] = 1 return dataframe ``` ## Reference config (multi-pair) ```json { "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": "futures", "margin_mode": "isolated", "entry_pricing": {"price_side": "same", "price_last_balance": 0.0}, "exit_pricing": {"price_side": "same", "price_last_balance": 0.0}, "pairlists": [{"method": "StaticPairList"}] } ``` 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. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [Superior-Trade](https://github.com/Superior-Trade) - **Source:** [Superior-Trade/superior-skills](https://github.com/Superior-Trade/superior-skills) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-superior-trade-superior-skills-bollinger-reverter-4h - Seller: https://agentstack.voostack.com/s/superior-trade - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.