These strategies control risk by sizing rather than by picking: they scale exposure down when realised volatility rises, or cap the downside of the position with an option collar. The goal is a steadier equity curve, so judge them on drawdown and Sharpe before CAGR.
3 strategies. Median max drawdown 19.6%, median CAGR 17.8%. Shallowest drawdown: Tsallis Entropy Weight Optimization (-19.0%). Highest return per unit of drawdown: Tsallis Entropy Weight Optimization (0.94).
By asset class: US stocks & ETFs 3.
Each dot is one strategy: further left is a shallower worst fall, higher up is a higher annual rate. The upper-left corner is where return came with the least drawdown.
| # | Strategy | Max drawdown | Risk tier | CAGR | Sharpe | Return ÷ drawdown | Period |
|---|---|---|---|---|---|---|---|
| 1 | Tsallis Entropy Weight Optimization | -19.0% | Moderate drawdown | +17.8% | 1.02 | 0.94 | 2016–2026 |
| 2 | Volatility Managed Index Portfolio | -19.6% | Moderate drawdown | +11.9% | 0.82 | 0.61 | 2016–2026 |
| 3 | Systematic Option Collar | -21.5% | Moderate drawdown | +18.3% | 1.06 | 0.85 | 2016–2026 |
Re-run 2026-10-04.
Tsallis Entropy Weight Optimization, with a worst fall of -19.0% and a CAGR of +17.8% from 2016-10-21 to 2026-10-02.
Tsallis Entropy Weight Optimization: +17.8% CAGR against a -19.0% max drawdown, a return-to-drawdown (Calmar) ratio of 0.94.
No. Each number comes from re-running the strategy's current code on historical prices. Backtests leave out some real costs and do not predict future returns.
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.