DeployQuantFirst-to-Last Day of Month vs 200-Day SMA Regime Filter
Two rule sets, 59 ETFs, one engine and one window.
| monthly cycle | 200-day regime filter | |
|---|---|---|
| Median CAGR (59 ETFs) | 5.5% | 1.8% |
| Median max drawdown | −36.6% | −22.2% |
| ETFs won (by CAGR) | 28 | 31 |
| Style | measuring how much of an asset's return accrues inside the month versus across month boundaries | a first systematic strategy, simple enough to audit every trade |
Where the gap was biggest
| ETF | monthly cycle | 200-day regime filter | gap |
|---|---|---|---|
| SOXS | −77.5% | −19.7% | 57.7% |
| TECS | −55.6% | −13.9% | 41.8% |
| UVXY | −68.7% | −29.8% | 38.9% |
| SQQQ | −44.6% | −10.5% | 34.1% |
| TECL | 36.0% | 11.5% | 24.4% |
| REW | −37.2% | −13.0% | 24.2% |
| TMF | −32.2% | −10.5% | 21.7% |
| FAS | 17.0% | −2.7% | 19.7% |
| QID | −28.8% | −10.5% | 18.3% |
| CTA | 13.3% | −3.0% | 16.3% |
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: monthly cycle or 200-day regime filter?
On this 2021-01-04 to 2026-10-02 window, 200-day regime filter produced the higher CAGR on 31 of 59 ETFs. Median CAGR: monthly cycle 5.5% vs 200-day regime filter 1.8%; median max drawdown: 36.6% vs 22.2%. 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.