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Robust Performance Hypothesis Testing with the Sharpe Ratio

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  • Oliver Ledoit
  • Michael Wolf

Abstract

Applied researchers often test for the difference of the Sharpe ratios of two investment strategies. A very popular tool to this end is the test of Jobson and Korkie (1981), which has been corrected by Memmel (2003). Unfortunately, this test is not valid when returns have tails heavier than the normal distribution or are of time series nature. Instead, we propose the use of robust inference methods. In particular, we suggest to construct a studentized time series bootstrap confidence interval for the difference of the Sharpe ratios and to declare the two ratios different if zero is not contained in the obtained interval. This approach has the advantage that one can simply resample from the observed data as opposed to some null-restricted data. A simulation study demonstrates the improved finite sample performance compared to existing methods. In addition, two applications to real data are provided.

Suggested Citation

  • Oliver Ledoit & Michael Wolf, 2008. "Robust Performance Hypothesis Testing with the Sharpe Ratio," IEW - Working Papers 320, Institute for Empirical Research in Economics - University of Zurich.
    • Handle: RePEc:zur:iewwpx:320
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    File URL: https://www.zora.uzh.ch/id/eprint/52275/1/iewwp320.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Bootstrap; HAC inference; Sharpe ratio;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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