Sharpe Ratio Calculator

The Sharpe Ratio is the most widely used measure of risk-adjusted return. It answers a critical investing question: “How much excess return am I earning per unit of risk taken?” A higher Sharpe ratio means better return for the same level of volatility.

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

Where:

• Portfolio Return (Rp): the annualized return of the investment or strategy
• Risk-Free Rate (Rf): the return of a risk-free asset (typically 3-month US Treasury bills; ~5% in 2024)
• Standard Deviation (σ): the annualized volatility of the portfolio’s returns; measures how wildly returns fluctuate

Annualizing standard deviation from daily returns: Annual σ = Daily σ × √252 (252 trading days per year)

Interpreting the Sharpe Ratio:

• Below 0: Portfolio returns less than the risk-free rate: losing money on a risk-adjusted basis
• 0.0–0.5: Poor
• 0.5–1.0: Acceptable
• 1.0–2.0: Good: institutional benchmarks typically target this range
• 2.0–3.0: Very good (top-tier funds)
• Above 3.0: Exceptional (hedge funds rarely sustain this)

What each variable means:

• Excess return (Rp − Rf): the return above what you could earn with zero risk; this is the “alpha” component
• Standard deviation: both upside and downside volatility are penalized equally; the Sortino Ratio, a close cousin, penalizes only downside deviation
• Annualization: always compare Sharpe ratios calculated on the same time frequency; mixing monthly and daily σ produces incomparable results

Worked example: Strategy annual return: 18% Risk-free rate (T-bill): 5% Annual standard deviation of returns: 12%

Sharpe Ratio = (18% − 5%) ÷ 12% = 13% ÷ 12% = 1.08

Interpretation: For every 1% of volatility accepted, the strategy earns 1.08% of excess return. This is a good result — comfortably above the 1.0 threshold used by most institutional allocators.

Limitation: The Sharpe Ratio assumes returns are normally distributed and penalizes all volatility equally. A strategy with large, consistent gains but occasional volatility may be penalized unfairly. Always use Sharpe alongside Sortino and max-drawdown metrics.

A bit of history. William F. Sharpe published the ratio in 1966 while at Stanford, originally calling it the “reward-to-variability ratio”. He won the 1990 Nobel Prize in Economics for his broader work on the Capital Asset Pricing Model and portfolio theory. The Sharpe ratio became the de facto industry standard for fund performance measurement, despite its known limitations around fat tails and the asymmetric treatment of upside vs downside volatility.

The fat-tail problem. Real market returns have fatter tails than the normal distribution assumes. Extreme events (2008, March 2020, 2022) happen more often than a normal model predicts. A strategy that looks great on Sharpe may still blow up because the standard deviation in the denominator under-prices tail risk. This is why hedge fund due diligence pairs Sharpe with maximum drawdown, Sortino ratio (downside deviation only), and tail-risk metrics like CVaR. None of those individually replaces Sharpe; they correct for what it misses.