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How Precision of the Sharpe Ratio Improves With Monthly Data
SSRN eLibrary, (2018)
DOI: 10.2139/ssrn.2959632
Аннотация
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.
