The thesis
RSI Snap-Back is a mean-reversion play on the Magnificent Seven. The premise is simple and time-tested: large-cap tech names that get stretched to a short-term momentum extreme tend to snap back. The strategy buys the most oversold names — entering when RSI falls below 35 — and exits into strength above RSI 70, rotating positions to hold a tight four-name book at any time.
That four-slot cap is the strategy's discipline mechanism. By hard-limiting concurrent exposure, it keeps the book from ballooning into a de facto index long and caps how many reversion bets can go wrong at once. The trading universe is the usual suspects: AAPL, MSFT, NVDA, GOOGL, AMZN, META, and TSLA.
Recent activity
Here the story gets quieter. Across the six most recent scheduled runs — from July 22 through July 29 — the strategy executed zero trades and rejected none, sitting in $10,000 of cash the entire time. In practice, none of the seven names dipped below the RSI 35 entry threshold during this window, so the strategy did exactly what it's designed to do when nothing is oversold: nothing.
That is defensible behavior, not a bug. But it's worth flagging that a strategy earning its keep only at momentum extremes will spend meaningful stretches fully in cash, contributing no return. Patience is part of the edge; it's also a drag when the setup never arrives.
Backtest and validation
Over 451 days the backtest finished at $12,095.14 — a 20.95% total return, or roughly 11.21% CAGR. The 66.67% win rate across 37 trades is genuinely strong and consistent with a well-specified reversion signal. Fees were negligible at $37 total, with no FX cost.
The risk numbers temper the enthusiasm. The Sharpe of 0.61 is modest — the returns came with real volatility, not a smooth ride — and the 23.73% max drawdown is steep relative to that return. An investor would have had to stomach nearly a quarter of the book evaporating at the worst point. Turnover of 773% also confirms this is an active rotation strategy; in a higher-fee or higher-slippage environment, that churn would bite harder than the clean $37 backtest suggests.
Most importantly: validation is null. There is no out-of-sample or walk-forward check on record. A 20.95% return over a single historical window, on a signal tuned to fixed RSI thresholds, is exactly the kind of result that can flatter an overfit rule. Until the strategy is validated on data it wasn't shaped around, the headline numbers should be read as a hypothesis, not a track record.
Verdict
RSI Snap-Back is a clean, disciplined idea with an encouraging in-sample profile and sensible risk controls. The strengths are real: high hit rate, cheap to run, and a hard cap on concurrent exposure. The risks are equally real: an unremarkable Sharpe, a punishing drawdown, heavy turnover, and — the big one — no validation to distinguish genuine edge from curve-fitting. For now, its recent all-cash posture is the honest picture: waiting for a setup that hasn't come.