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 premise is simple and well-worn: large-cap tech tends to overshoot on short-term momentum, then revert. The rules encode that directly — buy names with RSI below 35, exit above 70, and cap the book at four concurrent slots to force discipline and limit how much drawdown can pile up at once.
It's a clean, legible strategy. The 4-slot constraint is the part worth respecting: it turns a potentially sprawling watchlist into a tight, rotational book and keeps concentration risk bounded.
Backtest performance
Over 451 days the strategy returned 20.95%, ending at $12,095 on a $10,000 base — roughly an 11.21% CAGR. The win rate is a healthy 66.67% across 37 trades, and fee drag is negligible ($37 total, no FX cost).
The less flattering numbers sit right next to those. The Sharpe ratio is 0.61 — modest, indicating the returns came with meaningful volatility rather than smooth compounding. More striking is the maximum drawdown of 23.73%, which is actually larger than the total return itself. An investor holding this book had to stomach a peak-to-trough loss bigger than the profit they eventually walked away with. That's an uncomfortable ratio, and it's the single most important risk flag here.
Turnover is also high at 773%, consistent with a mean-reversion engine that rotates frequently. Fees stayed low in the backtest, but that level of churn leaves the strategy more exposed to slippage and real-world execution friction than the clean simulation suggests.
Live activity
Here the picture gets quieter — arguably too quiet. The strategy is marked live, but across its six most recent scheduled runs (22–29 September), every single one executed 0 trades and rejected 0, with the book sitting entirely in cash at $10,000. In other words, the live deployment has done nothing for at least a week.
That isn't necessarily a fault. If no Mag-7 name has printed RSI below 35 during a period of grinding, low-volatility strength, a disciplined mean-reversion system should stay in cash rather than force a trade. Patience is a feature. But it does mean the headline 20.95% is a backtest figure, not a live result — the live book has yet to put capital to work, and we have no out-of-sample evidence that the edge survives contact with the market.
The validation gap
One notable absence: the validation field is null. There's no walk-forward or holdout confirmation attached to these numbers, so the backtest should be read as in-sample until proven otherwise — especially given how much of the return the drawdown consumes.
Verdict
RSI Snap-Back is a well-constructed, disciplined idea with a decent win rate and trivial costs. The concerns are real, though: a drawdown that exceeds the return, a middling Sharpe, high turnover, no formal validation, and a live book that has yet to trade. Promising on paper — but unproven where it counts.