The mean-variance ratio test-A complement to the coefficient of variation test and the Sharpe ratio test

Zhidong Bai; Keyan Wang; Wing-Keung Wong

doi:10.1016/j.spl.2011.02.035

The mean-variance ratio test-A complement to the coefficient of variation test and the Sharpe ratio test

Zhidong Bai, Keyan Wang, Wing-Keung Wong^*

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › peer-review

32 Citations (Scopus)

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Abstract

To circumvent the limitations of the tests for coefficients of variation and Sharpe ratios, we develop the mean-variance ratio statistic for testing the equality of mean-variance ratios, and prove that our proposed statistic is the uniformly most powerful unbiased statistic. In addition, we illustrate the applicability of our proposed test for comparing the performances of stock indices.

Original language	English
Pages (from-to)	1078-1085
Number of pages	8
Journal	Statistics and Probability Letters
Volume	81
Issue number	8
Early online date	2 Mar 2011
DOIs	https://doi.org/10.1016/j.spl.2011.02.035
Publication status	Published - Aug 2011

Scopus Subject Areas

Statistics and Probability
Statistics, Probability and Uncertainty

User-Defined Keywords

Coefficient of variation
Sharpe ratio
Mean–variance ratio
Hypothesis testing
Uniformly most powerful unbiased test

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10.1016/j.spl.2011.02.035

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title = "The mean-variance ratio test-A complement to the coefficient of variation test and the Sharpe ratio test",

abstract = "To circumvent the limitations of the tests for coefficients of variation and Sharpe ratios, we develop the mean-variance ratio statistic for testing the equality of mean-variance ratios, and prove that our proposed statistic is the uniformly most powerful unbiased statistic. In addition, we illustrate the applicability of our proposed test for comparing the performances of stock indices.",

keywords = "Coefficient of variation, Sharpe ratio, Mean–variance ratio, Hypothesis testing, Uniformly most powerful unbiased test",

author = "Zhidong Bai and Keyan Wang and Wing-Keung Wong",

note = "Funding Information: The authors are grateful to Professor Hira Koul and the anonymous associate editor for substantive comments that have significantly improved this manuscript. The third author would also like to thank Professors Robert B. Miller and Howard E. Thompson for their continuous guidance and encouragement. This research is partially supported by NSF China #10871036 , Research Grants Council of Hong Kong #202809 , and NUS grant R-155-000-096-720 , and Hong Kong Baptist University . ",

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AU - Wong, Wing-Keung

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N2 - To circumvent the limitations of the tests for coefficients of variation and Sharpe ratios, we develop the mean-variance ratio statistic for testing the equality of mean-variance ratios, and prove that our proposed statistic is the uniformly most powerful unbiased statistic. In addition, we illustrate the applicability of our proposed test for comparing the performances of stock indices.

AB - To circumvent the limitations of the tests for coefficients of variation and Sharpe ratios, we develop the mean-variance ratio statistic for testing the equality of mean-variance ratios, and prove that our proposed statistic is the uniformly most powerful unbiased statistic. In addition, we illustrate the applicability of our proposed test for comparing the performances of stock indices.

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KW - Sharpe ratio

KW - Mean–variance ratio

KW - Hypothesis testing

KW - Uniformly most powerful unbiased test

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JF - Statistics and Probability Letters

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ER -

The mean-variance ratio test-A complement to the coefficient of variation test and the Sharpe ratio test

Abstract

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