Skip Navigation


RFS Advance Access originally published online on February 10, 2005
Review of Financial Studies 2005 18(2):673-705; doi:10.1093/rfs/hhi014
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
18/2/673    most recent
hhi014v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (4)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Wang, Z.
Right arrow Search for Related Content
Related Collections
Right arrow G12 - Asset Pricing; Trading volume; Bond Interest Rates
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

The Review of Financial Studies Vol. 18, No. 2 © 2005 The Society for Financial Studies; all rights reserved.

A Shrinkage Approach to Model Uncertainty and Asset Allocation

Zhenyu Wang
University of Texas at Austin

Address correspondence to: Department of Finance, School of Business, University of Texas at Austin, Austin, TX 78712-1179, or e-mail: zw274{at}mail.utexas.edu

This article takes a shrinkage approach to examine the empirical implications of aversion to model uncertainty. The shrinkage approach explicitly shows how predictive distributions incorporate data and prior beliefs. It enables us to solve the optimal portfolios for uncertainty-averse investors. Aversion to uncertainty about the capital asset pricing model leads investors to hold a portfolio that is not mean-variance efficient for any predictive distribution. However, mean-variance efficient portfolios corresponding to extremely strong beliefs in the Fama–French model are approximately optimal for uncertainty-averse investors. The empirical Bayes approach does not result in optimal portfolios for investors who are averse to model uncertainty.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Review of FinanceHome page
F. Lutgens and P. C. Schotman
Robust Portfolio Optimisation with Multiple Experts
Review of Finance, December 25, 2008; (2008) rfn028v1.
[Abstract] [Full Text] [PDF]

Home page
 REV FINANC STUDHome page
L. Garlappi, R. Uppal, and T. Wang
Portfolio Selection with Parameter and Model Uncertainty: A Multi-Prior Approach
Rev. Financ. Stud., January 1, 2007; 20(1): 41 - 81.
[Abstract] [Full Text] [PDF]

Home page
 REV FINANC STUDHome page
H. H. Cao, T. Wang, and H. H. Zhang
Model Uncertainty, Limited Market Participation, and Asset Prices
Rev. Financ. Stud., December 1, 2005; 18(4): 1219 - 1251.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.