Prospect Performance Evaluation: Making a Case for a Non-Asymptotic UMPU Test

31 Pages Posted: 16 Dec 2011

See all articles by Wing-Keung Wong

Wing-Keung Wong

Asia University, Department of Finance

Ricardas Zitikis

University of Western Ontario

Zhidong Bai

Northeast Normal University

Yongchang Hui

affiliation not provided to SSRN

Date Written: December 16, 2011

Abstract

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.

Suggested Citation

Wong, Wing-Keung and Zitikis, Ricardas and Bai, Zhidong and Hui, Yongchang, Prospect Performance Evaluation: Making a Case for a Non-Asymptotic UMPU Test (December 16, 2011). Available at SSRN: https://ssrn.com/abstract=1973440 or http://dx.doi.org/10.2139/ssrn.1973440

Wing-Keung Wong (Contact Author)

Asia University, Department of Finance ( email )

Taiwan
Taiwan

Ricardas Zitikis

University of Western Ontario ( email )

1151 Richmond Street
Suite 2
London, Ontario N6A 5B8
Canada

Zhidong Bai

Northeast Normal University ( email )

Changchun
China

Yongchang Hui

affiliation not provided to SSRN

No Address Available

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