Abstract

 
 

References (16)



 


 



Asset Allocation and Long-Term Returns: An Empirical Approach


Stephen Coggeshall


Morgan Stanley

Guowei Wu


Morgan Stanley

July 2005


Abstract:     
We present a discussion of the standard approaches to asset allocation, generally falling into two camps: Mean Variance Optimization and the maximization of the final value of a wealth utility function. After describing shortcomings in both of these standard approaches, we describe a heuristic, empirical approach that uses concepts of Shortfall Risk as an objective and actual data as a direct model of the stochastic market evolution. This empirical approach leads to fundamentally different conclusions than the standard approaches, and by definition fits the past data much better. Among other observations, we find that (1) for holding periods of about 15 years and greater, bonds are riskier than stocks in the practical sense that bonds are almost always expected to under perform stocks over 15-year or higher time horizons, (2) while short-term stock returns show fat tails, long-term stock returns show skinny tails, and (3) while stocks show mean reversion, bonds exhibit mean aversion.

Number of Pages in PDF File: 53

Keywords: asset allocation, long term returns, stock return distributions, mean variance optimization, random walk, skinny tails, mean reversion, mean aversion, reversion to the mean

JEL Classification: C13, C14, C15, C61, C82

working papers series


Download This Paper

Date posted: January 2, 2006  

Suggested Citation

Coggeshall, Stephen and Wu, Guowei, Asset Allocation and Long-Term Returns: An Empirical Approach (July 2005). Available at SSRN: http://ssrn.com/abstract=873184 or http://dx.doi.org/10.2139/ssrn.873184

Contact Information

Stephen Coggeshall (Contact Author)
Morgan Stanley ( email )
1585 Broadway
New York, NY 10036
United States
Guowei Wu
Morgan Stanley ( email )
1585 Broadway
New York, NY 10036
United States
Feedback to SSRN (Beta)


Paper statistics
Abstract Views: 4,682
Downloads: 1,602
Download Rank: 4,153
References:  16

© 2013 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright
This page was processed by apollo4 in 0.375 seconds