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Journal of Financial Econometrics 2005 3(3):315-343; doi:10.1093/jjfinec/nbi015
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© The Author 2005. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oupjournals.org.

Asymptotic and Bayesian Confidence Intervals for Sharpe-Style Weights

Tae-Hwan Kim
     Yonsei University and University of Nottingham

Halbert White
     University of California, San Diego

Douglas Stone
     Nicholas Applegate Capital Management

Address correspondence to Tae-Hwan Kim, Department of Economics, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul, 120-749, Korea, or e-mail: tae-hwan.kim{at}yonsei.ac.kr.

Received March 16, 2001; revised February 23, 2005; accepted March 3, 2005.

Sharpe-style regression has become a widely used analytic tool in the financial community. The style regression allows one to investigate such interesting issues as style composition, style sensitivity, and style change over time. All previous methods to obtain the distribution and confidence intervals of the style coefficients are statistically valid only in the special case in which none of the true style weights are zero or one. In practice, it is quite plausible to have zero or one for the values of some style weights. In this article we apply new results and develop a comparable Bayesian method to obtain statistically valid distributions and confidence intervals regardless of the true values of style weights.

KEYWORDS: Bayesian highest posterior density interval, linear-quadratic optimization, nonnegativity, Sharpe-style regression


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