The thesis
RSI Snap-Back is a tidy expression of a well-worn idea: large-cap tech names overshoot in the short term and revert. The rules are refreshingly literal — buy when RSI falls below 35, sell when it climbs above 70, and never hold more than four names at once. That hard four-slot book is the part worth praising. It caps concurrent exposure, forces the strategy to rank its convictions, and keeps the Mag-7 universe (AAPL, MSFT, NVDA, GOOGL, AMZN, META, TSLA) from quietly becoming an undiversified bet on a single theme.
Recent activity
Here the story gets quieter. The last six scheduled runs — spanning 2026-10-13 through 2026-10-19 — each report the same line: 0 executed, 0 rejected, cash $10,000, total $10,000. No trades, no rejections, full cash. The strategy isn't broken; it's simply waiting. With every name in its universe sitting in the 35–70 RSI band, there's nothing oversold to buy and nothing overbought to sell. That's the strategy behaving as designed, but it's also a reminder that a mean-reversion system spends a lot of time on the bench, earning nothing while fully in cash.
Backtest and validation
Over 451 days the backtest grew $10,000 to $12,095 — a 20.95% total return and an 11.21% CAGR, with a 66.67% win rate across 37 trades. Those are encouraging headline numbers, and fees were trivial ($37 total, no FX cost).
The fine print is more sobering. The Sharpe of 0.61 is middling — the returns came with real volatility, not smooth compounding. The 23.73% maximum drawdown is the figure that should give any allocator pause: a strategy that can bleed nearly a quarter of its equity demands conviction to hold through. And turnover of 773% means the book churns roughly eight times over the test window, so execution quality and slippage matter more than the clean $37 fee line suggests.
Most importantly, the validation block is null. There is no out-of-sample or holdout result reported here. A 66.67% win rate over just 37 trades is a thin sample, and without validation we can't distinguish a genuine edge from an in-sample fit. For a live strategy, that gap is the single biggest open question.
The balance
Strengths: a clear, falsifiable thesis; genuine risk discipline via the four-slot cap; low trading costs; and a positive backtest with a healthy win rate. Risks: an unremarkable Sharpe, a deep drawdown, heavy turnover, a small trade count, and — critically — no validation data to confirm the edge is real.
Takeaway
RSI Snap-Back is a thoughtfully constructed strategy that is currently doing exactly what it should when conditions are neutral: nothing. The backtest earns it a seat at the table, but until validation numbers land and we see how it behaves through a live oversold signal, treat the 20.95% as a promising hypothesis rather than a settled result.