Two US stocks & ETFs strategies from the top of the return-to-drawdown ranking, compared on the same measures: how far each fell, how fast each grew, and how much return each bought per unit of risk.
| Dynamic Factor Strength Strategy | Tactical Leveraged Trend Rotation | |
|---|---|---|
| Worst drop (max drawdown) | -24.1% | -29.4% |
| Yearly growth (CAGR) | +18.0% | +18.2% |
| Calmar (CAGR ÷ drawdown) | 0.75 | 0.62 |
| Return per unit of risk (Sharpe) | 0.97 | 0.84 |
| Total return | +417.8% | +428.1% |
| Risk tier | Moderate drawdown | High drawdown |
| Strategy type | Factor | Momentum rotation |
| Period | 2016-10-24 – 2026-10-05 | 2016-10-26 – 2026-10-07 |
Backtest = historical simulation on past prices, not real trading.
Dynamic Factor Strength Strategy had the shallower worst fall (-24.1%). Tactical Leveraged Trend Rotation compounded faster (+18.2% a year). On return per unit of drawdown Dynamic Factor Strength Strategy leads, 0.75 against 0.62; the two backtests cover different periods, so read the comparison with that in mind.
$10,000 start, 2016-10-24 – 2026-10-05, SPY dashed.
$10,000 start, 2016-10-26 – 2026-10-07, SPY dashed.
Dynamic Factor Strength Strategy, at -24.1%.
Dynamic Factor Strength Strategy on the Calmar ratio (0.75 vs 0.62); Dynamic Factor Strength Strategy on the Sharpe ratio (0.97).
Both are US stocks & ETFs strategies re-run with their current code on historical prices, over 2016-10-24 – 2026-10-05 and 2016-10-26 – 2026-10-07.
All strategy backtests, lowest drawdown first
Disclosure. Backtests are hypothetical simulations on historical data. They do not include every real-world cost, are not live results, and do not guarantee future returns. Educational research only, not investment advice.