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

 

Abstract

 
 

References (11)

Beta

 


 



What Likely Range of My Wealth Will Be?

Raymond Kan
University of Toronto - Joseph L. Rotman School of Management

Guofu Zhou
Washington University, St. Louis - John M. Olin School of Business


February 6, 2009


Abstract:     
The median is often a better measure than the mean in evaluating the long-term value of a portfolio. However, the standard plug-in estimate of the median is too optimistic. It has a substantial upward bias that can easily exceed a factor of two. In this paper, we provide an unbiased forecast of the median of the long-term value of a portfolio. In addition, we also provide an unbiased forecast of an arbitrary percentile of the long-term portfolio value distribution. This allows us to construct the likely range of the long-term portfolio value for any given confidence level. Finally, we provide an unbiased forecast of the probability for the long-term portfolio value falling into a given interval. Our unbiased estimators provide a more accurate assessment of the long-term value of a portfolio than the traditional estimators, and are useful for long-term planning and investment.

Keywords: long-term investment, median, quantiles

JEL Classifications: C22, C53, G11, G12

Working Paper Series

Date posted: October 19, 2008 ; Last revised: February 07, 2009

Suggested Citation

Kan, Raymond and Zhou, Guofu, What Likely Range of My Wealth Will Be? (February 6, 2009). Available at SSRN: http://ssrn.com/abstract=1285745


Export to: Export Citation What's this?

Contact Information

Guofu Zhou (Contact Author)
Washington University, St. Louis - John M. Olin School of Business ( email )
Washington University
Campus Box 1133
St. Louis, MO 63130-4899
United States
314-935-6384 (Phone)
314-658-6359 (Fax)
Raymond Kan
University of Toronto - Joseph L. Rotman School of Management ( email )
105 St. George Street
Toronto, Ontario M5S 3E6 Canada
416-978-4291 (Phone)
416-971-3048 (Fax)
Feedback to SSRN (Beta)


Paper statistics
Abstract Views: 329
Downloads: 109
Download Rank: 77,696
References: 11
Paper comments
No comments have been made on this paper

© 2010 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright
This page was served by apollo1 in 0.171 seconds.