Drawdown Dip Buyer + 8% Target vs 200-Day SMA Regime Filter
Two rule sets, 59 ETFs, one engine and window — a genuinely like-for-like comparison.
| dip buyer | 200-day regime filter | |
|---|---|---|
| Median CAGR (59 ETFs) | 1.4% | 1.6% |
| Median max drawdown | −26.2% | −22.7% |
| ETFs won (by CAGR) | 19 | 40 |
| Style | assets that sell off hard and recover — it monetizes volatility without chasing strength | a first systematic strategy — it's simple enough to fully understand and audit every trade |
Where the gap was biggest
| ETF | dip buyer | 200-day regime filter | gap |
|---|---|---|---|
| CLSE | 5.6% | −100.0% | 105.6% |
| FAS | 28.5% | −0.5% | 29.0% |
| SOXS | −30.7% | −2.9% | 27.8% |
| REW | −33.1% | −13.5% | 19.6% |
| SOXL | 13.3% | 31.6% | 18.3% |
| TMF | −29.2% | −10.9% | 18.3% |
| SQQQ | −28.9% | −10.6% | 18.3% |
| QID | −26.6% | −10.8% | 15.8% |
| IAU | −1.4% | 13.6% | 15.0% |
| TQQQ | 8.8% | 23.6% | 14.8% |
Build it from blocks (or type it in English), backtest it on 5.5 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: dip buyer or 200-day regime filter?
On this 2021-01-04–2026-07-17 window, 200-day regime filter produced the higher CAGR on 40 of 59 ETFs. Median CAGR: dip buyer 1.4% vs 200-day regime filter 1.6%; median max drawdown: 26.2% vs 22.7%. "Better" depends on the asset and what you optimize — 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 2026-07-17, $10,000 starting capital, no margin, fees and slippage not modeled) and do not guarantee future results. Nothing on this page is investment advice. Live trading involves risk of loss.