The Thesis
RSI Snap-Back is a mean-reversion play on the Magnificent Seven — AAPL, MSFT, NVDA, GOOGL, AMZN, META, and TSLA. The wager is simple and well-worn: large-cap tech tends to overshoot on short-term momentum, then snap back. The strategy buys names when RSI drops below 35 (oversold) and exits when RSI pushes above 70 (overbought), rotating positions to hold a tight four-slot book. That four-name cap is doing double duty here — it enforces discipline and deliberately limits how much concurrent drawdown the book can carry at once.
It's a clean, legible idea. There's no black box: you can read the rules and know exactly why a trade fired.
Recent Activity
Here's the honest headline — nothing is happening. The last six scheduled runs (7 October through 14 October) each closed with 0 executed, 0 rejected, the book sitting in $10,000 of cash and a $10,000 total. No live trades are on record.
That isn't a malfunction; it's the strategy behaving as designed. If no Mag-7 name has been oversold enough to clear the RSI < 35 trigger, there's simply nothing to buy. A mean-reverter that refuses to force trades in a rangebound or grinding-higher tape is arguably doing its job. The flip side: there is no live P&L yet, so every performance figure below is backtest, not battle-tested.
Backtest & Validation
Over 451 days, the backtest grew $10,000 to $12,095 — a 20.95% total return, an 11.21% CAGR, and a 66.67% win rate across 37 trades. Fees were a negligible $37 and FX costs zero. On the surface, encouraging.
Look closer and the picture gets more mixed. The Sharpe of 0.61 is modest — this is return earned with meaningful volatility, not a smooth ride. The 23.73% max drawdown is the figure that should give pause: it's only a shade below the total return, meaning an investor had to stomach a near-24% peak-to-trough dip to collect that 21%. Turnover of 773% also shows the book churns hard; it survives on the cheap fee assumption, and any slippage in live conditions would eat into results.
Most importantly, no validation data is available — there's no out-of-sample or walk-forward record attached. A high in-sample win rate on a seven-name universe is exactly the kind of result that can flatter an over-fit rule set. Until there's live track record or a proper holdout test, treat the backtest as a hypothesis, not a verdict.
The Balance
RSI Snap-Back is a transparent, disciplined strategy with a respectable backtest and a sensible reluctance to overtrade. But the drawdown is heavy relative to the gain, the Sharpe is unremarkable, validation is missing, and the live account has yet to take a single position. Promising on paper — unproven in the wild.