The Thesis
RSI Snap-Back is a clean, legible idea: large-cap tech names overshoot in the short term and snap back. The strategy buys the most oversold Mag-7 constituents (RSI below 35) and exits into strength (RSI above 70), rotating to hold a tight four-name book. That hard slot cap is the discipline mechanism — it forces the strategy to concentrate on its best signals and caps how much concurrent drawdown exposure it can carry. The universe is the usual suspects: AAPL, MSFT, NVDA, GOOGL, AMZN, META, and TSLA.
It's a coherent premise. Mean reversion on liquid mega-caps is a well-trodden factor, and RSI is a transparent, auditable trigger — no black-box scoring here.
Backtest Performance
Over 451 days the strategy returned 20.95%, lifting a $10,000 book to $12,095. That works out to an 11.21% CAGR with a 66.67% win rate across 37 trades. Fees were a negligible $37 and FX cost was zero, so the returns are essentially frictionless-clean.
The caveats live in the risk column. A Sharpe of 0.61 is modest — this is not a smooth ride, and the return-per-unit-risk is mediocre. The 23.73% max drawdown confirms it: an investor would have had to stomach nearly a quarter of the book evaporating at the worst point. Turnover of 773% is also high, meaning the book churns roughly eight times over the period; the strategy leans hard on trading frequency, which raises real-world slippage risk that a backtest tends to understate.
The Validation Gap
The single most important line in the data is validation: null. There is no out-of-sample or walk-forward record attached to this strategy. A 66.67% win rate and 20.95% return look attractive, but without validation we can't distinguish genuine edge from curve-fit. For a mean-reversion rule with tunable RSI thresholds, that distinction matters enormously — overfitting is the default failure mode here, not the exception.
Recent Activity: Dormant
Despite a live status, the strategy has done nothing. The last six scheduled runs — from July 9 through July 16 — each report the same line: 0 executed, 0 rejected, cash $10,000, total $10,000. The book is 100% cash, the four slots are empty, and no trade signals have fired in over a week.
This isn't necessarily a fault. A mean-reversion strategy that only acts on RSI extremes should stay flat when nothing is oversold — patience is part of the design. But it does mean the live track record is currently empty, and the entire case for RSI Snap-Back rests on that unvalidated backtest.
Verdict
Strengths: a transparent thesis, a disciplined four-slot risk cap, a solid win rate, and low frictional cost. Risks: a soft Sharpe, a deep drawdown, heavy turnover, and — most critically — no validation to confirm the backtest generalizes. Right now it's a well-designed idea waiting for a signal. The next real test is whether live entries, when they finally come, echo the backtest or expose the gap that a null validation record leaves wide open.