The Thesis
RSI Snap-Back is a disciplined mean-reversion play on the seven largest US tech names — AAPL, MSFT, NVDA, GOOGL, AMZN, META, and TSLA. The logic is simple and testable: large-caps that get stretched to a short-term momentum extreme tend to snap back. The strategy buys the most oversold names when RSI drops below 35 and exits into strength when RSI climbs above 70. A hard four-slot book caps concurrent exposure, forcing the strategy to rotate rather than pile on, and limiting how much drawdown can accumulate across positions at once.
It's a coherent, well-scoped idea. Mean reversion is a well-documented short-horizon effect in liquid large-caps, and constraining the universe to seven high-volume names keeps execution realistic.
Recent Activity
Here is where the story turns quiet. Across every scheduled run from 2026-09-01 through 2026-09-08, the strategy executed zero trades and rejected none. Cash and total equity have both sat flat at $10,000, meaning the book is currently empty and entirely in cash.
This isn't a malfunction — it's the thesis working as designed. If none of the Mag-7 names have been oversold enough to trigger the RSI-below-35 entry, the strategy correctly does nothing. Patience is a feature of contrarian systems. The flip side: an idle strategy earns nothing, and a full week without a single signal underlines how selective — and potentially opportunity-starved — this setup can be in a calm or trending tape.
Backtest and Validation
Over 451 days, the backtest returned 20.95% (final equity $12,095), an 11.21% CAGR, on 37 trades with a 66.67% win rate. Fees were negligible at $37 and FX cost was zero. Those are respectable headline numbers.
The risk profile deserves equal attention. The Sharpe ratio of 0.61 is modest — returns came with meaningful volatility rather than smooth compounding. More striking, the maximum drawdown of 23.73% actually exceeds the annualized return, so an investor entering at the wrong moment could have endured a drop larger than a typical year's gain before recovering. Turnover of 773% confirms this is an active, high-churn strategy; the low realized fees flatter it, and any real-world slippage or wider spreads would eat into the edge.
The most important caveat: there is no validation record on file. Without out-of-sample or walk-forward testing, the 20.95% figure should be read as in-sample performance, which is always prone to overfitting. A 66.67% win rate across only 37 trades is a small sample, and the absence of a robustness check is the single biggest gap in the case for this strategy.
Verdict
RSI Snap-Back pairs a sensible thesis with disciplined risk controls, and its backtest is genuinely positive. But a sub-1 Sharpe, a drawdown deeper than its yearly return, high turnover, and — critically — no validation data mean the numbers should be treated as promising rather than proven. Its current all-cash stance is honest behavior from a picky system. The next real test is whether it deploys well when a genuine oversold signal finally arrives.