What Is the Sharpe Ratio?

How the Sharpe Ratio Is Calculated

Sharpe Ratio = (Portfolio Return − Risk-Free Rate) ÷ Portfolio Standard Deviation. The risk-free rate is typically the 3-month US Treasury bill yield. If a stock returned 12% when T-bills yielded 4%, and had annualised volatility of 20%, the Sharpe ratio is (12% − 4%) ÷ 20% = 0.40. The ratio tells you that for every 1% of risk (volatility) taken, the investor earned 0.40% of excess return above the risk-free rate.

What Makes a "Good" Sharpe Ratio?

There are no universal benchmarks, but practical reference points:

• Below 0 — the investment returned less than the risk-free rate; not worth the risk
• 0.0–0.5 — acceptable but not great; marginal risk-adjusted return
• 0.5–1.0 — reasonable; typical for diversified equity portfolios over long periods
• 1.0–2.0 — strong; well above average for individual stocks or funds
• Above 2.0 — exceptional; often seen only in specific periods or strategies with low volatility
• The S&P 500's long-run Sharpe ratio is approximately 0.4–0.6

Sharpe Ratio vs Sortino Ratio

The Sharpe ratio penalises both upside and downside volatility equally. The Sortino ratio is a refinement that only counts downside deviation in the denominator — volatility below the target return. This is arguably more logical because investors do not usually mind upside surprises. A stock with large upside moves but controlled drawdowns will have a better Sortino than Sharpe ratio, which may be the fairer picture for growth-oriented investors.

Limitations and Misuses

The Sharpe ratio assumes returns are normally distributed — they are not. Stocks exhibit "fat tails," meaning extreme events happen more often than a bell curve predicts. Strategies that look excellent on Sharpe ratio can still blow up in tail events (as happened to many quantitative hedge funds in 2007–2008). Also, Sharpe ratios are backwards-looking; a high Sharpe ratio in one period offers no guarantee of the same in the next. Use it as a comparative ranking tool, not an absolute predictor.