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

Abstract

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: https://ssrn.com/abstract=2959632 or http://dx.doi.org/10.2139/ssrn.2959632

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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