Sharpe Ratio Calculator
Measure the excess return a portfolio earned over the risk-free rate for each unit of volatility it took.
Sharpe Ratio Calculator
Commas, spaces or new lines. At least 3 values, e.g. 2.5 for +2.5%.
Annualised Sharpe Ratio
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Sharpe per Period
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Excess Return per Period
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Approx. Annual Return
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Approx. Annual Volatility
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Where it sits on common rule-of-thumb bands
Assumptions & method
- Sharpe ratio per period = (average return − risk-free rate per period) ÷ standard deviation of returns.
- Annualised Sharpe = per-period Sharpe × √N, where N is the annualisation factor: monthly 12, weekly 52, daily 252, quarterly 4, annual 1. This assumes returns are independent from period to period.
- The risk-free rate is entered as an annual percentage and converted to per-period by dividing by N (a simple approximation).
- Mode A: the average return and standard deviation must be per period of the periodicity you pick. Mode B: periodic returns in percent are pasted and the mean and sample standard deviation (n − 1) are computed for you.
- Annualised return and volatility shown are approximations: mean × N and standard deviation × √N.
- The ratio treats upside and downside swings alike, assumes roughly symmetric returns and is unreliable on short samples. Bands shown are common rules of thumb, not ratings.
Results are estimates based on the figures you enter. They are not guarantees and not financial advice.
What is the Sharpe ratio?
The Sharpe ratio asks how much extra return a portfolio earned above a risk-free rate for each unit of volatility. The numerator is the average return minus the risk-free rate, and the denominator is the standard deviation of returns, so both must be measured over the same period. Because volatility grows with the square root of time while average return grows linearly, a monthly ratio is scaled by the square root of 12 to compare it with an annual one. A higher value means more excess return per unit of volatility, and a negative value means the average return fell short of the risk-free rate. It is a summary of past data, it penalises large gains as well as large losses, and it can look flattering for strategies with rare but severe losses.