Drawdown Dip Buyer + 8% Target vs SMA-200 Trend + 15% Trailing Stop
Two rule sets, 59 ETFs, one engine and window — a genuinely like-for-like comparison.
| dip buyer | trend + trailing stop | |
|---|---|---|
| Median CAGR (59 ETFs) | 1.4% | 3.2% |
| Median max drawdown | −26.2% | −30.0% |
| ETFs won (by CAGR) | 20 | 39 |
| Style | assets that sell off hard and recover — it monetizes volatility without chasing strength | long trends with tolerable pullbacks; the 15% trail is wide enough to survive normal corrections |
Where the gap was biggest
| ETF | dip buyer | trend + trailing stop | gap |
|---|---|---|---|
| SOXS | −30.7% | 9.2% | 39.9% |
| FAS | 28.5% | −8.1% | 36.5% |
| REW | −33.1% | −7.4% | 25.7% |
| QID | −26.6% | −7.9% | 18.7% |
| SQQQ | −28.9% | −12.1% | 16.7% |
| IAU | −1.4% | 15.2% | 16.5% |
| TMF | −29.2% | −13.4% | 15.8% |
| UVXY | −38.0% | −23.3% | 14.7% |
| CLSE | 5.6% | 19.3% | 13.7% |
| TQQQ | 8.8% | 22.1% | 13.3% |
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 trend + trailing stop?
On this 2021-01-04–2026-07-17 window, trend + trailing stop produced the higher CAGR on 39 of 59 ETFs. Median CAGR: dip buyer 1.4% vs trend + trailing stop 3.2%; median max drawdown: 26.2% vs 30.0%. "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.