The Thesis
RSI Snap-Back is a mean-reversion strategy that bets large-cap tech names rebound sharply after short-term momentum extremes. The rule set is deliberately simple: buy names whose RSI drops below 35, exit when RSI climbs above 70, and rotate holdings to keep a tight four-slot book. That hard cap on concurrent positions is the strategy's risk governor — it limits how much drawdown exposure can stack up at once. The universe is the familiar Mag-7: AAPL, MSFT, NVDA, GOOGL, AMZN, META, and TSLA.
Backtest Performance
Over 451 days, the backtest returned 20.95%, lifting a $10,000 book to $12,095.14 — an 11.21% CAGR. The win rate is a respectable 66.67% across 37 trades, and trading costs were negligible: just $37 in fees and zero FX cost. On the surface, this is a tidy result for a rules-based system.
Look closer and the picture gets more nuanced. The Sharpe ratio of 0.61 is modest — the returns came with meaningful volatility, not a smooth ride. The 23.73% maximum drawdown reinforces that: an investor would have had to stomach nearly a quarter of the book evaporating at the worst point. Turnover is also strikingly high at 773%, meaning the book churned through roughly eight times its value over the test. Low per-trade fees keep that churn cheap here, but in a higher-cost or higher-slippage environment it would bite.
Recent Live Activity
This is where the story turns cautionary. Across six consecutive scheduled runs — from October 12 through October 18 — the strategy executed zero trades and rejected zero. Cash and total equity have held flat at exactly $10,000 the entire time. In plain terms, the live book is fully parked in cash with no exposure at all.
That is not a malfunction; it is the thesis doing exactly what it says. No name in the universe has dipped below the RSI < 35 entry threshold during this window, so the strategy correctly stayed on the sidelines. Discipline is a feature. But it also means the attractive backtest return is, for now, entirely theoretical for live capital — the strategy can only earn when oversold conditions actually appear.
The Validation Gap
The most important caveat is what's missing: the validation field is null. There is no out-of-sample or walk-forward evidence presented to confirm the backtest edge generalizes. A 66.67% win rate on only 37 trades is a thin sample, and without validation we cannot rule out that the parameters were fitted to the test period's particular dips and rebounds.
Verdict
RSI Snap-Back is a clean, disciplined concept with an encouraging backtest and genuinely low trading friction. But three flags temper enthusiasm: a middling Sharpe against a deep drawdown, very high turnover, and — most of all — the absence of validation data behind a modest trade count. For now the live book is simply waiting for its signal. Promising, but unproven where it counts.