Strategy Thesis
Bollinger Reversion is a textbook mean-reversion system: buy when price closes below the lower Bollinger Band, sell when it closes above the upper band. The underlying assumption is that large-cap equities revert to their moving average after short-term dislocations. The universe is deliberately blue-chip — 24 names spanning tech (AAPL, MSFT, NVDA, GOOGL), financials (JPM, BAC, V, MA), healthcare (JNJ, UNH, PFE, ABBV), consumer staples/discretionary (PG, KO, WMT, COST, MCD, NKE, HD), and energy/industrials (XOM, CVX, CAT, HON, DIS). The narrow, liquid universe limits slippage and keeps the strategy tractable.
Recent Activity
Over the past week, the strategy has been cautious. Of six daily scheduled runs (June 3–10), only two resulted in executed trades. On June 10 it bought 25 shares of DIS at $99.18, and on June 9 it closed a PG position — selling 17 shares at $148.40 for a clean round-trip on the PG buy from June 1 at $140.03 (roughly a 6% gross gain in eight days). Two runs saw rejected signals (June 4 and June 8), and one run found no qualifying setups at all. Portfolio value has ranged from $9,956 to $10,206 this week, with cash currently sitting at ~$1,002 — indicating most capital is deployed.
Earlier in the period (late May / June 1), the strategy was more active: WMT, COST, GOOGL, and PG were all entered, suggesting a cluster of band-breaks across the consumer and tech names.
Backtest Performance
Over 451 days the strategy returned 17.55% (9.46% CAGR) on a starting equity of $10,000, finishing at $11,755. The 63.89% win rate across 76 trades is solid for a mean-reversion system, confirming that the band-break trigger does select entries that frequently close profitably. The Sharpe of 0.66 is modest but positive. The main sore spot is a 20.57% maximum drawdown — nearly matching the full-period return — which reflects the strategy's vulnerability during trending or volatile regimes when prices walk away from the bands rather than snap back.
Turnover of 1,720% annualised is high, though the $1-per-trade flat fee structure keeps friction manageable at the current paper-trading scale.
Validation: Where the Concern Lies
The walk-forward validation did not pass, and the fold breakdown tells the story clearly:
| Fold | Period | Return | Sharpe | Max DD |
|---|---|---|---|---|
| 1 | Aug 2024 – Jan 2025 | 7.67% | 1.78 | 7.06% |
| 2 | Jan – Jul 2025 | 1.42% | 0.25 | 20.56% |
| 3 | Jul – Dec 2025 | 0.77% | 0.20 | 6.66% |
| 4 | Dec 2025 – May 2026 | 0.40% | 0.14 | 11.19% |
All four folds are positive — that part is encouraging. But the performance has degraded monotonically: the most recent out-of-sample fold (the most predictive of future live behaviour) returned just 0.40% with a Sharpe of 0.14. The Deflated Sharpe Ratio of 0.342 — adjusted for the number of parameter trials (6) — sits well below the conventional 0.95 acceptance threshold, and the PSR of 0.814 means there is roughly an 18% probability the true Sharpe is negative. In short, the headline numbers flatter the strategy; the validated edge is thin.
Outlook
Bollinger Reversion has genuine structural logic and a clean win rate, but the validation evidence suggests the bulk of its in-sample return was concentrated in a favourable early regime (Fold 1) that has not repeated. Before treating live signals as high-conviction, two things would strengthen the case: (1) running the strategy through additional market regimes without refitting parameters to confirm Fold 1 was not an outlier, and (2) testing tighter drawdown controls — perhaps a stop-loss per trade — to reduce the 20% drawdown profile. As it stands, this strategy is best treated as paper-trading / observation mode until the most recent fold's Sharpe recovers toward 0.5 or above.