The Thesis
RSI Snap-Back is built on a simple premise: large-cap tech names — Apple, Microsoft, Nvidia, Alphabet, Amazon, Meta, and Tesla — tend to recover sharply when short-term momentum reaches extremes. The strategy enters positions when RSI drops below 35 (oversold territory) and exits when RSI climbs above 70. A hard cap of four concurrent positions enforces concentration discipline and limits the strategy's simultaneous drawdown exposure.
The logic is coherent. Mega-cap tech names carry durable analyst coverage and institutional demand, so genuine dislocations are often temporary. Reversion traders who can tolerate short-term pain during a drawdown have historically been rewarded in this cohort.
Backtest Performance
Over 451 trading days, the backtest produced a 20.95% total return, translating to a CAGR of 11.21%. The win rate of 66.67% across 37 trades is a meaningful edge — two in every three trades closed profitably.
The risk-adjusted picture is more nuanced. A Sharpe ratio of 0.61 reflects modest return-per-unit-of-volatility, and the maximum drawdown of 23.73% is substantial for a strategy running on a $10,000 paper book. A drawdown of that magnitude — nearly a quarter of the portfolio — demands genuine conviction from any operator running this live.
Turnover clocks in at 773%, which is extremely high. In the backtest environment, fees totalled a flat $37 (one dollar per trade). In a real-money account with spread costs or percentage commissions, elevated turnover would meaningfully compress net returns. This is the figure most worth stress-testing before any real capital allocation.
Recent Activity: Patient or Stalled?
The strategy's live run log tells an interesting story. From June 30 through July 7 — six consecutive scheduled runs — RSI Snap-Back executed zero trades, leaving its full $10,000 in cash. The book is empty.
This is not necessarily a flaw. If RSI conditions in the Mag-7 universe have not dipped below 35, the strategy is correctly doing nothing. Discipline in reversion strategies means not chasing trades when the signal is absent. A system that fires only on genuine setups is better than one that manufactures reasons to stay invested.
That said, extended periods of inactivity deserve scrutiny. If the broader market has kept large-cap tech elevated — never gifting an RSI oversold reading — then the backtest may have been calibrated to a more volatile regime than the current one. The strategy's CAGR of 11.21% is predicated on 37 trades over 451 days; if the signal fires materially less often going forward, realised CAGR could fall well short of that figure.
Validation Gap
One gap stands out: no independent validation run is recorded. Walk-forward or out-of-sample testing would provide stronger evidence that the RSI thresholds — 35 and 70 — weren't selected by fitting to the backtest period. With only 37 trades in the sample, the statistical base is thin enough that a few lucky exits could be inflating the win rate.
Bottom Line
RSI Snap-Back is a well-structured, rule-driven strategy with a clear edge hypothesis and a respectable backtested win rate. Its four-slot discipline is a genuine strength. The main concerns are the steep maximum drawdown relative to its Sharpe ratio, high turnover sensitivity to real transaction costs, and an absence of out-of-sample validation. The current all-cash posture may simply reflect a market that hasn't handed it a setup — patience is a virtue in reversion trading. But it warrants monitoring: if the signal stays quiet for another few weeks, revisiting the threshold calibration would be prudent.