Estimation Risk in Portfolio Selection: The Mean Variance Model Versus the Mean Absolute Deviation Model

Yusif Simaan
Additional contact information
Yusif Simaan: Graduate School of Business Administration, Fordham University at Lincoln Center, 113 West 60th Street, New York, New York 10023

Management Science, 1997, vol. 43, issue 10, 1437-1446

Abstract: Konno and Yamazaki (Konno, H., K. Yamazaki. 1992. Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market. Management Sci. 39 519--531.) propose the mean absolute deviation (MAD) model as an alternative to the mean variance (MV) model. They claim it retains all the positive features of the MV model, saves the investor computing time, and does not require the covariance matrix. This paper shows that ignoring the covariance matrix results in greater estimation risk that outweighs the benefits. In both models, estimation error is more severe in small samples (small observations relative to the number of assets) and for investors with high risk tolerance. The MV model's lower estimation risk is most striking in small samples and for investors with a low risk tolerance.

Keywords: portfolio analysis; estimation risk; mean-variance portfolio analysis; investment analysis (search for similar items in EconPapers)
Date: 1997
References: Add references at CitEc
Citations: View citations in EconPapers (53)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.43.10.1437 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:43:y:1997:i:10:p:1437-1446

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().