Sharpe Ratio

risk-adjusted returnreward-to-variability ratio

A measure of risk-adjusted return, calculated as the excess return of a portfolio over the risk-free rate divided by the portfolio's standard deviation. Higher is better.

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Analysis from Apr 2, 2026

What Is the Sharpe Ratio?

Developed by Nobel laureate William Sharpe, the Sharpe ratio measures how much excess return an investment delivers per unit of risk taken:

Sharpe Ratio = (Portfolio Return − Risk-Free Rate) ÷ Standard Deviation

A Sharpe ratio of 1.0 means you earn one unit of excess return for each unit of risk. Above 2.0 is considered excellent; below 0 means you are being paid less than a risk-free asset while taking on volatility.

Interpreting the Ratio

< 0: Worse than holding cash — avoid
0–0.5: Poor risk-adjusted return
0.5–1.0: Acceptable but not compelling
1.0–2.0: Good — competitive with the best long-only managers
> 2.0: Excellent — typical of well-run quant funds or strategies with genuine edge

Key Limitations

The Sharpe ratio penalises upside volatility equally with downside. A strategy that spikes dramatically upward looks "risky" even if investors would welcome that outcome. The Sortino ratio addresses this by using only downside deviation in the denominator.

Sharpe ratios also break down when return distributions are fat-tailed — options strategies that collect small premiums and occasionally blow up can show high Sharpe ratios until the blow-up event arrives.

Frequently Asked Questions

▶What is a good Sharpe ratio for a trading strategy?

A Sharpe ratio above 1.0 is generally considered good for an active trading strategy, while ratios above 2.0 are excellent and difficult to sustain at scale. Most institutional allocators require a minimum of 0.5–1.0 on a live track record before making an allocation, and ratios above 3.0 in backtests should be scrutinized for overfitting or data-mining bias.

▶What is the difference between the Sharpe ratio and the Sortino ratio?

The Sharpe ratio divides excess returns by total standard deviation, penalizing both upside and downside volatility equally, while the Sortino ratio uses only downside deviation in the denominator. This makes the Sortino ratio more appropriate for strategies with positively skewed return distributions, such as long-volatility or momentum programs, where upside outliers should not be treated as a liability.

▶Can the Sharpe ratio be manipulated or misleading?

Yes — strategies that sell options premium or exhibit smoothed, autocorrelated returns can produce artificially high Sharpe ratios that overstate true risk-adjusted quality. Short-volatility strategies, for example, posted Sharpe ratios above 2.0 for several years before catastrophic losses in events like the February 2018 volatility spike, because standard deviation fails to capture the fat-tailed risk embedded in their payoff structures.

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