Matching the market’s return with smaller drawdowns is a real, risk‑adjusted win, and it is harder than it sounds. Here is what lower‑risk strategies actually did over the last decade, what cushioned the falls, and the levers that improve return per unit of risk.
On a risk-adjusted basis it is possible, but rare, and it rarely means a higher raw return. Beating the market “with less risk” means earning more return per unit of risk than the S&P 500 index: a higher Sharpe ratio, or the same return with a shallower worst fall. A portfolio that returns 10% a year and falls 20% in a crash is better built than one that returns 10% and falls 35%, even though both “tied”.
The honest starting point is that most investors and funds do not beat the S&P 500 even before adjusting for risk. A narrower goal is more achievable: measure your portfolio correctly, then improve the return you get for the risk you take.
Exent’s strategy backtests, July 2016 to September 2026 (hypothetical, monthly, dividends included):
| Backtest | Annual return | Volatility | Sharpe | Max drawdown | 2022 |
|---|---|---|---|---|---|
| S&P 500 (SPY) | 15.2% | 15.2% | 0.88 | 23.9% | −18.2% |
| Dividend growth (VIG) | 12.6% | 13.4% | 0.80 | 20.2% | −9.8% |
| High-dividend equity (SCHD) | 12.2% | 15.2% | 0.70 | 21.6% | −3.2% |
| Minimum volatility (USMV) | 9.4% | 12.2% | 0.63 | 19.1% | −9.4% |
| 60/40 stocks and bonds | 9.5% | 10.1% | 0.75 | 20.0% | −15.8% |
| Risk parity (from Jul 2017) | 8.7% | 10.4% | 0.65 | 23.0% | −18.2% |
| 10-month trend filter | 9.4% | 11.6% | 0.66 | 21.9% | −20.1% |
Every one of them had lower volatility than the index and a smaller worst drawdown. None had a higher Sharpe ratio over this decade, which was an unusually strong one for large US stocks. Dividend growth came closest: about 90% of the index’s return per unit of risk, with a shallower worst fall and a much milder 2022. In a different decade, with a longer or deeper bear market, the ranking could look different; a single backtest window cannot settle it.
Because losses and gains are not symmetric, and because people sell at the bottom.
| Fall from peak | Gain needed to get back to even |
|---|---|
| −10% | +11.1% |
| −20% | +25.0% |
| −35% | +53.8% |
| −50% | +100.0% |
A smaller fall is easier to recover from and easier to sit through. The second effect is often bigger than the first: a portfolio that drops further than its owner expected is the one most likely to be sold near the low, turning a temporary loss into a permanent one. See loss recovery math and how much drawdown you can tolerate.
Fewer than most investors assume. We looked at the 16 months since mid-2016 in which the S&P 500 (SPY) fell more than 4%. SPY’s average return in those months was −6.7%.
| Asset | Average return in the 16 stress months | Correlation with SPY | 2022 |
|---|---|---|---|
| T-bills (BIL) | +0.2% | 0.00 | +1.4% |
| Gold (GLD) | −0.4% | 0.14 | −0.8% |
| 7–10 year Treasuries (IEF) | −0.9% | 0.18 | −15.2% |
| 20+ year Treasuries (TLT) | −1.9% | 0.19 | −31.2% |
| Minimum volatility (USMV) | −4.9% | 0.87 | −9.4% |
| High dividend (SCHD) | −5.5% | 0.82 | −3.2% |
| Nasdaq-100 (QQQ) | −7.6% | 0.91 | −32.6% |
Defensive stocks are still stocks: they fell less, but they fell. Long bonds helped in sudden crashes and hurt badly in the 2022 rate shock. Cash and gold were the steadiest cushions in this sample. More in what actually diversifies a portfolio.
It helps you see the trade-off, but it does not guarantee a better result. An optimizer finds the mix with the best historical return per unit of risk, which is only as good as the history it learns from. In Exent’s backtests from July 2019, a max-Sharpe mix re-optimized every month on the trailing 36 months matched the S&P 500’s Sharpe ratio (0.83 each) but fell 30.5% at its worst against 23.9%. A minimum-variance mix returned just 0.7% a year. The value of the efficient frontier is diagnostic: it shows whether your current portfolio sits well below what the same holdings could have done. See the portfolio optimization guide and common optimization pitfalls.
To compare a result fairly, read how to measure risk-adjusted outperformance.
On a risk-adjusted basis, sometimes: a portfolio can earn a similar return with smaller drawdowns, or a higher Sharpe ratio than the index. In Exent’s 2016–2026 backtests, though, none of the lower-volatility strategies tested beat the S&P 500’s Sharpe ratio.
There is no single best one, and the ranking changes by period. In Exent’s 2016–2026 backtests, dividend growth came closest to the S&P 500’s return per unit of risk, while T-bills and gold held up best in months when stocks fell sharply.
Over 2016–2026 they did not: a US minimum-volatility fund returned 9.4% a year vs 15.2% for the S&P 500, with a lower Sharpe ratio. They did fall less in 2022 and in most stress months.
It can be, if it keeps you invested through crashes and you would otherwise sell at the bottom. Judge it by return per unit of risk and by whether you could live with the worst drawdown.
Usually they reduce volatility, but not always when it matters: long Treasuries rose in some sudden crashes and fell 31.2% in 2022 in Exent’s data, when stocks also fell.
Upload a screenshot of your holdings and get concentration, overlap, crash exposure and a risk-matched benchmark in about a minute.
Educational content, not investment advice. Examples are illustrative; past performance does not guarantee future results.