The Thesis
RSI Snap-Back is a mean-reversion strategy trained on the "Magnificent Seven" — AAPL, MSFT, NVDA, GOOGL, AMZN, META, and TSLA. The premise is that these names snap back sharply from short-term selling extremes. The strategy enters when RSI falls below 35 and exits when RSI climbs above 70, rotating through a maximum of four concurrent positions. The hard four-slot book cap is a deliberate risk-management constraint: no single momentum dislocation can absorb the full portfolio.
Backtest Performance
Over 451 days and 37 completed trades, RSI Snap-Back returned 20.95% in total — a 11.21% annualized CAGR — growing a $10,000 paper portfolio to $12,095. A 66.67% win rate means roughly two of every three trades closed in profit, which is a respectable hit rate for a rules-based swing strategy.
The risk picture is more mixed. A Sharpe ratio of 0.61 reflects real volatility relative to the gains produced; the strategy earns, but not smoothly. The maximum drawdown of 23.73% is the headline concern — a near-quarter decline in a seven-name concentrated book is a genuine test of conviction, especially when several Mag-7 names move in sympathy during broad tech sell-offs.
Turnover deserves a mention too: 773% over the backtest window reflects the rapid rotation built into mean-reversion logic. The backtest assumes $1 per trade in fees — $37 in total — which likely understates real-world friction and spread costs at higher capital levels.
Recent Activity
The live paper portfolio has held fully in cash at $10,000 across every scheduled run from June 4 through June 11 — six consecutive daily scans, zero executed trades, zero rejections.
This is the strategy functioning correctly, not failing. None of the Mag-7 names breached the RSI < 35 entry threshold during this window, so the system stayed on the sideline. In trending or bid-up market conditions, oversold signals can go unmet for extended periods. Staying in cash rather than forcing sub-optimal entries is a feature — but prolonged inactivity is a real drag on live returns and worth monitoring if it extends further.
Risks to Watch
Drawdown depth. A 23.73% peak-to-trough decline is significant for a universe of only seven names. Mean-reversion strategies can enter a falling name too early if the oversold condition deepens before recovering, turning a snap-back play into a value trap. High-beta tech in a risk-off tape is the worst environment for this setup.
No formal validation. The strategy's validation record is currently empty. Thirty-seven trades over 451 days is a workable sample, but without a walk-forward or out-of-sample test, some degree of backtest overfit cannot be ruled out. A held-out validation pass is the logical next step before increasing paper-trade size.
Concentration risk. Seven names is a narrow universe. Sector-wide shocks — regulatory action, a hawkish Fed pivot, or a cluster of weak earnings — can push multiple Mag-7 names into oversold territory simultaneously, filling all four book slots and concentrating drawdown exposure at exactly the moment correlations spike.
Bottom Line
RSI Snap-Back is a coherent, rule-based strategy with a clear edge thesis and a solid win rate. The recent inactivity reflects appropriate discipline, not a system problem. The priority improvements are a formal walk-forward validation pass and a closer look at drawdown behavior during sustained tech downturns — both of which would meaningfully strengthen the case for scaling beyond paper trading.