The thesis
RSI Snap-Back is a mean-reversion play on the seven largest US tech names — AAPL, MSFT, NVDA, GOOGL, AMZN, META, and TSLA. The idea is simple and well-worn: large-caps that get stretched to a short-term momentum extreme tend to snap back. The strategy buys the most oversold names when their RSI falls below 35, exits when RSI climbs above 70, and enforces a hard four-slot book to cap how many positions — and how much drawdown — it can carry at once.
That discipline is the strategy's philosophical core. Rather than chase every oversold ticker, it rotates capital to keep a tight, concentrated book. In principle, that limits concurrent exposure; in practice, concentration in four correlated mega-caps is its own kind of risk.
Backtest performance
Over 451 days, the backtest returned 20.95%, closing at $12,095 on a $10k base — an 11.21% CAGR. The win rate is a healthy 66.67% across 37 trades, and fees were negligible at $37 with zero FX cost.
The risk picture is more sobering. The Sharpe ratio of 0.61 is modest — this is return earned with meaningful volatility, not smooth compounding. More striking is the 23.73% max drawdown, which is larger than the total return itself. An investor would have had to stomach losing nearly a quarter of peak equity to collect that 21%. Turnover of 773% also signals a lot of churn; the four-slot rotation keeps the book busy, and while fees stayed low here, that intensity would bite harder against real-world spreads and slippage.
Recent live activity
The live book tells a quieter story. Across six scheduled runs between September 16 and 23, the strategy executed zero trades every single day, holding $10,000 in cash with no positions. No RSI reading in the universe crossed the entry threshold, so the strategy did exactly what it should: nothing.
That is a feature, not a bug — a mean-reverter with no signal should sit in cash rather than force a trade. But it means the live track record is currently a flat line, and the compelling backtest numbers remain unproven in production.
The verdict
The strengths are real: a coherent thesis, a two-thirds win rate, and rules-based discipline that keeps costs down. The risks are equally real. A Sharpe below 1 paired with a drawdown that exceeds total return is a demanding trade-off, and the strategy carries no out-of-sample validation — the validation field is empty, so we have a backtest and a week of idle live runs, nothing more.
RSI Snap-Back looks like a sensible, well-disciplined idea that has yet to prove itself when it matters. Until the entry signal actually fires in live conditions and the drawdown behaviour holds up outside the backtest window, treat these numbers as a promising hypothesis rather than a track record.