The Thesis
RSI Snap-Back targets a well-worn observation in large-cap tech: the Magnificent Seven names — AAPL, MSFT, NVDA, GOOGL, AMZN, META, and TSLA — tend to snap back sharply after short-term momentum extremes. The strategy buys when RSI drops below 35 (oversold) and exits when RSI climbs above 70 (overbought), rotating through a hard-capped four-slot book. That slot constraint is deliberate: it enforces concentration discipline and limits how much concurrent drawdown the portfolio can absorb at any one time.
The logic is sound in principle. These names carry enormous institutional ownership and analyst coverage, which tends to compress deep dislocations relatively quickly. The question is always execution — and timing.
Recent Activity: Constructive Quiet
Over the past six scheduled runs (June 9–16), RSI Snap-Back executed zero trades. Cash sits at $10,000, fully uninvested. To a casual observer this looks like a dormant strategy; in context, it's the opposite signal.
If no name in the Mag-7 universe has crossed RSI < 35 since early June, that implies the cohort has been trading in relatively neutral-to-strong momentum territory. A mean-reversion strategy that refuses to chase strength is doing exactly what it should. The discipline to stay flat when conditions don't fit the thesis is harder to build than the entry logic itself.
That said, extended idle periods are worth monitoring. A six-session dry spell on a seven-name universe is not alarming; a six-month one might indicate the RSI threshold needs calibration for a sustained bull tape.
Backtest Performance
Over 451 days of backtested history, the numbers tell a mixed but encouraging story:
| Metric | Value |
|---|---|
| Total Return | 20.95% |
| CAGR | 11.21% |
| Sharpe Ratio | 0.61 |
| Max Drawdown | 23.73% |
| Win Rate | 66.67% |
| Trades | 37 |
| Turnover | 773.36% |
A 66.7% win rate across 37 trades is a solid base rate for a mean-reversion approach — better than a coin flip, and meaningful at that sample size. The 11.21% CAGR is competitive, particularly for a strategy with strict entry filters that will sit out extended trending markets.
The friction points are real. A 23.73% maximum drawdown is significant relative to a 0.61 Sharpe — the strategy earns its returns somewhat unevenly, and a drawdown of that depth on a portfolio would test conviction. Turnover at 773% is high, which in a live account would compound slippage and tax drag on top of the $1-per-trade fee already baked into the backtest.
Strengths and Risks
Strengths: Clean rule-set with no ambiguous discretion. The four-slot cap prevents the overcommitment that kills most retail mean-reversion attempts. The universe is liquid enough that RSI signals are less likely to be noise.
Risks: The backtest spans 451 days — roughly 15 months. That's a limited window that may not capture a true drawdown cycle for Mag-7 names. The 23.73% max drawdown figure deserves scrutiny: at what point in the test period did it occur, and how long was recovery? Without validation data (validation: null), out-of-sample robustness is unconfirmed.
High turnover also means this strategy is sensitive to execution quality in live conditions — something paper trading inherently sidesteps.
Bottom Line
RSI Snap-Back is a disciplined, rules-driven approach with a credible thesis and a respectable paper record. The current idle streak is a feature, not a bug. The main gaps are a short backtest window, an unvalidated out-of-sample period, and a drawdown profile that warrants stress-testing before any live capital commitment.