DeployQuant20-Day Momentum + Trailing Stop vs RSI(2) Dip Snapback
Two rule sets, 59 ETFs, one engine and one window.
| momentum breakout | RSI(2) snapback | |
|---|---|---|
| Median CAGR (59 ETFs) | 0.0% | 4.7% |
| Median max drawdown | −20.1% | −17.5% |
| ETFs won (by CAGR) | 4 | 55 |
| Style | high-momentum assets where trends extend, such as semiconductor and leveraged tech ETFs | liquid index ETFs with strong long-term drift; turnover is high so per-trade edges are small |
Where the gap was biggest
| ETF | momentum breakout | RSI(2) snapback | gap |
|---|---|---|---|
| TQQQ | 0.6% | 39.3% | 38.7% |
| SOXL | 19.1% | 39.2% | 20.2% |
| TECL | 10.2% | 30.2% | 20.0% |
| SOXS | −13.6% | −29.9% | 16.3% |
| VIXM | −15.9% | 0.1% | 16.0% |
| FAS | 3.9% | 18.7% | 14.8% |
| TBF | −2.3% | 9.7% | 12.0% |
| RINF | −2.3% | 8.5% | 10.8% |
| VXZ | −17.3% | −7.0% | 10.3% |
| XLP | −1.9% | 8.2% | 10.1% |
Build it from blocks (or type it in English), backtest it on 5.7 years of minute data in seconds, tweak any parameter, then paper trade it on live data. No card, no broker needed to start.
Frequently asked questions
Which is better: momentum breakout or RSI(2) snapback?
On this 2021-01-04 to 2026-10-02 window, RSI(2) snapback produced the higher CAGR on 55 of 59 ETFs. Median CAGR: momentum breakout 0.0% vs RSI(2) snapback 4.7%; median max drawdown: 20.1% vs 17.5%. Which is better depends on the asset and what you optimize for. The per-ETF table shows where each wins.
Dig deeper
Backtests are hypothetical, computed by DeployQuant's engine on minute-resolution consolidated US market data (2021-01-04 to 2026-10-02, $10,000 starting capital, no margin, no fees or slippage in the headline run; buy-and-hold puts 98% of the account in at the first open, as the templates do) and do not guarantee future results. Nothing on this page is investment advice. Live trading involves risk of loss.