The Thesis
RSI Snap-Back operates on a straightforward premise: the Magnificent Seven — AAPL, MSFT, NVDA, GOOGL, AMZN, META, and TSLA — are among the most liquid, institutionally-owned equities in the world, and sharp short-term selloffs in this cohort tend to resolve upward. The strategy enters when RSI falls below 35, signalling an oversold extreme, and exits when RSI climbs above 70. A hard cap of four concurrent positions enforces capital discipline and prevents the book from becoming a concentrated bet on a broad-market drawdown.
The logic is clean and grounded in well-documented mean-reversion behaviour. Large-cap tech names attract aggressive momentum selling that frequently overshoots fundamental value, creating the snap-back window the strategy is designed to exploit.
Backtest Performance
Over a 451-day backtest period, RSI Snap-Back returned 20.95% on a $10,000 starting balance, ending at $12,095. The annualised CAGR of 11.21% is respectable for a mean-reversion approach that spends meaningful time in cash.
| 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 meaningful signal — two in three entries resolved profitably. High turnover (773%) reflects the rotate-and-repeat nature of the book rather than a buy-and-hold structure; each RSI trigger generates a fresh entry and exit cycle.
The Sharpe of 0.61 is moderate. It reflects the strategy's vulnerability to sustained trending markets, where oversold readings can deepen before reverting — or fail to revert at all. The 23.73% max drawdown is the number that commands the most respect here: a strategy with a sub-$12k equity high that draws down nearly a quarter of capital at its worst point carries real psychological and risk-management weight.
Recent Activity
Since deployment on 31 May 2026 with a $10,000 allocation, RSI Snap-Back has run four scheduled daily scans — and executed zero trades. The book remains entirely in cash.
This is not necessarily a red flag. Mean-reversion strategies are inherently opportunistic: if RSI readings across the Mag-7 universe haven't dipped below 35 since deployment, the correct action is to wait. Forced entries would undermine the edge entirely. That said, the all-cash posture through the first week of live operation means there is no live performance data to evaluate yet — the backtest metrics remain the sole quantitative basis for assessment.
The code review at deployment assigned a risk score of 0.35 (low), noting sound RSI logic, correct position-sizing, and no look-ahead bias. Three minor defensive-coding gaps were flagged but deemed non-exploitable under normal sandbox conditions.
Strengths and Risks
Strengths: The universe is tight and liquid. The 4-slot book prevents over-concentration. The entry/exit logic is simple, auditable, and grounded in a widely-observed market phenomenon. A clean code review adds confidence in implementation integrity.
Risks: Mean-reversion strategies suffer in persistent trends. A macro regime where large-cap tech grinds lower — or rockets without pulling back — can leave the strategy sidelined (best case) or entering into a falling knife (worst case). The 23.73% max drawdown is a preview of what sustained adverse conditions look like. Formal walk-forward or out-of-sample validation has not yet been completed (validation: null), which limits confidence in the backtest's generalisability.
Outlook
RSI Snap-Back is a well-reasoned, conservatively-scoped mean-reversion play. The backtest is encouraging, the code is clean, and the discipline enforced by the 4-slot constraint is a genuine structural advantage. The strategy now needs live trades to prove itself — and independent validation to confirm the backtest holds beyond the training window.