Sharpe Ratio

What is the Sharpe Ratio?

The Sharpe ratio, introduced by William F. Sharpe in 1966 as the reward-to-variability ratio, measures return per unit of risk: the average return earned in excess of the risk-free rate, divided by the standard deviation of those excess returns. It is conventionally annualized; a ratio computed from daily returns is typically scaled by the square root of 252, the usual count of trading days in a year. The result puts portfolios and strategies with different volatilities on one axis: how much excess return each unit of volatility bought.

Its weaknesses are as well documented as its ubiquity. Standard deviation penalizes upside and downside moves equally, so a strategy with volatile gains scores worse than it deserves (the Sortino ratio answers this by using downside deviation only). More seriously, the ratio compresses risk into a single volatility number, a summary that is only adequate when returns are roughly normal: strategies with heavy negative skew, the kind that collect small steady gains against rare large losses, can print a high Sharpe for years before a single tail event erases it. Reading the ratio alongside the distribution's higher moments and the drawdown history is the honest use.

How traders use it

• Ranking strategies and portfolios on a risk-adjusted basis, where a smooth equity curve with moderate returns can legitimately outrank a volatile one with higher raw returns.
• As a backtest quality gate alongside win rate and maximum drawdown, with the caveat that an implausibly high in-sample Sharpe is more often an overfitting alarm than a discovery; the out-of-sample figure is the one that counts.
• In allocation and sizing frameworks: because the ratio is built on realized volatility, it pairs naturally with volatility-targeted position sizing when weighting multiple systems.