How Precision of the Sharpe Ratio Improves With Monthly Data

42 Pages Posted: 27 Apr 2017 Last revised: 24 Jan 2018

See all articles by Thomas Coleman

Thomas Coleman

University of Chicago - Harris School of Public Policy; Close Mountain Advisors LLC

Date Written: January 21, 2018


Practitioners often estimate the Sharpe ratio using annualized monthly data. This paper demonstrates how the bias and precision of the Sharpe improves with monthly versus annual data. I provide small-sample and large-sample formulae for the distribution, highlighting the distinction between the annual and annualized monthly estimators. With more than two years of monthly data the large-sample distributions generally provide a good approximation, simplifying the calculation of confidence intervals; this applies for both normal and non-normal returns. Although these results apply to iid returns they are of practical use, since independence for monthly returns is a good description for many financial assets.

Keywords: Sharpe, Sharpe Ratio, sampling distribution, non-central Student-t, small-sample distribution, large-sample distribution, asymptotic distribution, confidence interval

JEL Classification: G10, G11

Suggested Citation

Coleman, Thomas, How Precision of the Sharpe Ratio Improves With Monthly Data (January 21, 2018). Available at SSRN: or

Thomas Coleman (Contact Author)

University of Chicago - Harris School of Public Policy ( email )

1155 East 60th Street
Chicago, IL 60637
United States

Close Mountain Advisors LLC ( email )

19 Davenport Ave.
Unit B
Greenwich, CT 06830
United States

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