Prospect Performance Evaluation: Making a Case for a Non-Asymptotic UMPU Test
Hong Kong Baptist University (HKBU)
University of Western Ontario - Department of Statistical and Actuarial Sciences
Northeast Normal University
affiliation not provided to SSRN
December 16, 2011
We propose and develop a mean-variance-ratio (MVR) statistics for comparing the performance of prospects (e.g., investment portfolios, assets, etc.) after the effect of the background risk has been mitigated. We investigate the performance of the statistics in large and small samples, and show that in the non-asymptotic framework, the MVR statistic produces a uniformly most powerful unbiased (UMPU) test. We discuss the applicability of the MVR test in the case of large samples and illustrate its superiority in the case of small samples by analyzing Korea and Singapore stock returns after the impact of the American stock returns (which we view as the risk) has been deducted. We find, in particular, that when samples are small, the MVR statistic can detect differences in asset performances while the Sharpe ratio test, which is the mean-standard-deviation-ratio statistic, may not be able to do so.
Number of Pages in PDF File: 31working papers series
Date posted: December 16, 2011
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