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The most-cited risk-adjusted return ratio in finance — and the one most often misunderstood.
Sharpe ratio measures how much excess return you earn per unit of total volatility. It is calculated as (portfolio return minus the risk-free rate) divided by the standard deviation of the portfolio. A Sharpe above 1.0 is good, above 2.0 is excellent, and most diversified equity portfolios sit between 0.4 and 0.7 long-term.
Sharpe = (Rp − Rf) / σp · above 1.0 = good · above 2.0 = excellentSharpe = (Rp − Rf) / σpYou subtract the risk-free rate from your portfolio return to get the part of the return you earned for taking risk. Then you divide by the size of the swings (standard deviation) to get reward per unit of pain. Both numerator and denominator are annualized — daily returns scale by 252, monthly by 12.
Sharpe is the answer to "is this actually a good portfolio, or did you just turn up the leverage?" A portfolio that returned 30% with 40% volatility and a portfolio that returned 8% with 10% volatility have nearly identical Sharpe ratios (both around 0.6) — they would compound to roughly the same long-run wealth if you levered or de-levered to match risk levels.
Sharpe penalizes upside volatility the same as downside, which is its main critique. That is why the Sortino ratio and Calmar ratio exist — they only count the kind of volatility that actually hurts.
Your portfolio earned 12% annualized. The 3-month T-bill paid 4.3% over the same period. Your annualized volatility was 15%.
Sharpe = (12% − 4.3%) / 15% = 7.7% / 15% = 0.51
That is right in the middle of the long-run S&P 500 historical band (about 0.4–0.7). Adequate, not exceptional — you earned about half a percentage point of excess return for every percentage point of volatility you ate.
Sharpe is unitless, so absolute scale matters. Context: the S&P 500 has produced Sharpe of roughly 0.4–0.7 over rolling 10-year windows since 1928. Anything sustained above 1.0 over a decade-plus is rare; above 2.0 over decades is essentially Renaissance Technologies territory.
| Sharpe | Verdict | What it usually means |
|---|---|---|
| < 0 | Bad | You underperformed sitting in T-bills. The risk you took was uncompensated. |
| 0 – 0.5 | Weak | Below the long-run market. Often signals undiversified bets or a bad regime. |
| 0.5 – 1.0 | Adequate | Where most diversified equity portfolios live over long periods. |
| 1.0 – 2.0 | Strong | Real risk-adjusted skill or a great regime. Hedge funds aim for this. |
| 2.0 – 3.0 | Exceptional | Rarely sustained. Verify the calculation window — small samples mislead. |
| > 3.0 | Suspicious | Almost always overfitting, look-ahead bias, or a tiny sample. Audit before believing. |
Look at the Probabilistic Sharpe Ratio before celebrating any Sharpe above 1.0 on less than five years of data — Sharpe is statistically noisy at small sample sizes.
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Open the Sharpe Ratio Calculator →Sortino Ratio · Treynor Ratio · Information Ratio · Lo-Adjusted Sharpe · Probabilistic Sharpe Ratio
Above 1.0 is good, above 2.0 is excellent. Most diversified equity portfolios sit between 0.4 and 0.7 over long periods. The S&P 500 has averaged roughly 0.5 since 1928.
Subtract the risk-free rate (typically the 3-month Treasury bill yield) from your portfolio return, then divide by the annualized standard deviation of the portfolio. Foliolytic uses actual daily T-bill yields from FRED rather than a fixed assumption.
Sharpe divides by total standard deviation; Sortino divides only by downside deviation (returns below a threshold). Sortino does not penalize upside volatility, which most investors actually like. For portfolios with positive skew, Sortino is higher.
Small sample size (less than 3 years), non-normal returns (fat tails, skew), and serial autocorrelation can all inflate Sharpe. The Probabilistic Sharpe Ratio and Lo-adjusted Sharpe correct for these.
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