Department of Economics
Prospect performance evaluation: Making a case for a non-asymptotic UMPU test
We propose and develop 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 background 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. © The Author, 2012. Published by Oxford University Press. All rights reserved.
Asset, Fund management, Hypothesis test, Investment portfolio, Mean-variance ratio, Sharpe ratio, Uniformly most powerful unbiased test
Source Publication Title
Journal of Financial Econometrics
Oxford University Press
Link to Publisher's Edition
Bai, Zhidong, Yongchang Hui, Wing-Keung Wong, and Ričardas Zitikis. "Prospect performance evaluation: Making a case for a non-asymptotic UMPU test." Journal of Financial Econometrics 3.4 (2012): 703-732.