SSRN Home Search and Download Papers Browse Abstract and Paper Submission Subscribe to Networks View Briefcase Top Papers Top Authors Top Institutions

 

Abstract

 
 

References (19)

Beta

 
 

Citations (1)

Beta

 


 



Robust Portfolio Optimisation with Multiple Experts

Frank Lutgens
Maastricht University - Faculty of Economics & Business Administration

Peter C. Schotman
Maastricht University


March 2007

CEPR Discussion Paper No. DP6161

Abstract:     
We consider mean-variance portfolio choice of a robust investor. The investor receives advice from J experts, each with a different prior for the distribution of returns. Confronted with these multiple priors the investor follows a min-max portfolio strategy. We study the structure of the robust mean-variance portfolio and empirically compare its performance with a variety of alternative portfolio strategies. The empirical tests are based on bootstrap simulations on the 25 Fama-French portfolios and on 81 European country and value portfolios. We find that the robust portfolio performs well in both settings. Robust portfolios do not exhibit the extreme weights typically observed in naive mean-variance portfolios. Robust portfolios are also better diversified than portfolios that impose short-sell constraints to suppress the symptoms of extreme weights.

Keywords: Mean-variance, model uncertainty, portfolio choice

JEL Classifications: C11, D80

Working Paper Series

Date posted: May 19, 2008 ; Last revised: May 19, 2008

Suggested Citation

Lutgens, Frank and Schotman, Peter C., Robust Portfolio Optimisation with Multiple Experts (March 2007). CEPR Discussion Paper No. DP6161. Available at SSRN: http://ssrn.com/abstract=1133805


Export to: Export Citation What's this?

Contact Information

Frank Lutgens (Contact Author)
Maastricht University - Faculty of Economics & Business Administration ( email )
P.O. Box 616
Maastricht NL 6200 MD Netherlands
Peter C. Schotman
Maastricht University ( email )
P.O. Box 616
6200 MD Maastricht Netherlands
+31 43 388 3862 (Phone)
+31 43 388 4875 (Fax)
Feedback to SSRN (Beta)


Paper statistics
Abstract Views: 106
Downloads: 2
References: 19
Citations: 1

© 2009 Social Science Electronic Publishing, Inc. All Rights Reserved. Terms of Use  Privacy Policy
This page was served by apollo 4 in 1.672 seconds.