The Thesis
RSI Snap-Back is a disciplined mean-reversion play on the seven largest U.S. tech names — Apple, Microsoft, Nvidia, Alphabet, Amazon, Meta, and Tesla. The logic is straightforward: when any of these names gets oversold enough to push RSI below 35, the strategy enters; when RSI climbs back above 70, it exits. A hard cap of four simultaneous positions enforces concentration discipline and prevents the book from sprawling across every name in a sector-wide sell-off.
The universe choice matters. These are companies with deep liquidity, persistent institutional demand, and a history of recovering from short-term momentum extremes relatively quickly. Mean reversion works best where fundamentals provide a floor — and Mag-7 names tend to have that.
Backtest Performance
Over 451 days and 37 completed trades, the strategy returned 20.95% on a $10,000 starting book, finishing at $12,095. That translates to an annualised CAGR of 11.21% — a respectable result for a strategy that is often in cash.
The Sharpe ratio of 0.61 is modest. It reflects the strategy's tolerance for volatility: a maximum drawdown of 23.73% is meaningful, and any investor running this live would need conviction to hold through those periods. The win rate of 66.67% (two wins in every three trades) is encouraging and consistent with a well-calibrated entry threshold — RSI < 35 is not a hair-trigger.
Turnover of 773% across the window sounds high but is largely a function of the tight 4-slot book rotating actively when signals fire. Total fees across all 37 trades came to $37 — a flat-fee assumption that keeps the cost picture clean.
Recent Activity: A Quiet Stretch
The strategy has run daily since at least June 25, and every scheduled run through July 2 has returned the same result: zero trades executed, zero rejected, full $10,000 in cash. That is not a malfunction — it is the strategy doing exactly what it was designed to do.
When none of the Mag-7 names breach RSI < 35, there is nothing to buy. Given that large-cap tech has broadly been in recovery or consolidation mode recently, the lack of oversold readings makes sense. The strategy is waiting for its pitch.
Strengths
- Rule-based discipline: hard entry/exit thresholds and a slot cap remove discretionary drift.
- Universe quality: anchoring to seven highly liquid names limits gap risk and slippage.
- Positive win rate: two-thirds of historical trades closed profitable, suggesting the RSI < 35 entry level is genuinely useful as a reversal signal in this universe.
Risks to Watch
- Drawdown depth: a 23.73% max drawdown is significant for a paper book. In a live account, that would test most investors' resolve.
- Trend-break risk: mean reversion fails when a name is in genuine secular decline rather than a short-term dip. A Mag-7 name losing its fundamental story (regulatory action, competitive disruption) could turn a reversion trade into a value trap.
- Missing validation: the
validationfield is currently null. Until walk-forward or out-of-sample testing is complete, the backtest return figures carry overfitting risk — 37 trades across 451 days is a limited sample. - Extended dormancy: prolonged cash-only periods (like the current one) can erode relative performance against a simple index-hold benchmark.
Outlook
RSI Snap-Back is a structurally sound strategy with a clear edge hypothesis and a clean execution framework. The quiet patch it is navigating right now is feature, not bug — it simply has no signal. The next meaningful test will be how it responds when volatility returns and RSI readings compress across the Mag-7 simultaneously. That is when the 4-slot discipline will matter most.