Extreme mean-variance solutions: Estimation error versus modeling error

Robert R. Grauer

doi:10.1108/S0276-8976(2009)0000013004

Login

Welcome:
Guest

Search for:

Browse:

Product Information:

Resources:

Applications of Management Science

ISSN: 0276-8976
Series editor(s): Professor Kenneth D. Lawrence

Subject Area: Management Science/Management Studies

Content: Series Volumes | Current Volume RSS

Options: To add Favourites and Table of Contents Alerts please take a Emerald profile

Document request:
Extreme mean-variance solutions: Estimation error versus modeling error

Document Information:
Title:	Extreme mean-variance solutions: Estimation error versus modeling error
Author(s):	Robert R. Grauer
Volume:	13 Editor(s): Kenneth D. Lawrence, Gary Kleinman ISBN: 978-1-84855-878-6 eISBN: 978-1-84855-879-3
Citation:	Robert R. Grauer (2009), Extreme mean-variance solutions: Estimation error versus modeling error, in Kenneth D. Lawrence, Gary Kleinman (ed.) Financial Modeling Applications and Data Envelopment Applications (Applications of Management Science, Volume 13), Emerald Group Publishing Limited, pp.19-51
DOI:	10.1108/S0276-8976(2009)0000013004 (Permanent URL)
Publisher:	Emerald Group Publishing Limited
Article type:	Chapter Item
Abstract:	Without short-sales constraints, mean-variance (MV) and power-utility portfolios generated from historical data are often characterized by extreme expected returns, standard deviations, and weights. The result is usually attributed to estimation error. I argue that modeling error, that is, modeling the portfolio problem with just a budget constraint, plays a more fundamental role in determining the extreme solutions and that a more complete analysis of MV problems should include realistic constraints, estimates of the means based on predictive variables, and specific values of investors’ risk tolerances. Empirical evidence shows that investors who utilize MV analysis without imposing short-sales constraints, without employing estimates of the means based on predictive variables, and without specifying their risk tolerance miss out on remarkably remunerative investment opportunities.