Parametric Portfolio Policies: Exploiting Characteristics in the Cross Section of Equity Returns

Michael W Brandt, Pedro Santa-Clara and Rossen Valkanov

University of California at Los Angeles, Anderson Graduate School of Management from Anderson Graduate School of Management, UCLA

Abstract: We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset’s characteristics. The coefficients of this function are found by optimizing the investor’s average utility of the portfolio’s return over the sample period. Our approach is computationally simple, easily modified and extended, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only diffcult to implement for a large number of assets but also yields notoriously noisy and unstable results. Our approach also provides a new test of the portfolio choice implications of equilibrium asset pricing models. We present an empirical implementation for the universe of all stocks in the CRSP-Compustat dataset, exploiting the size, value, and momentum anomalies.

Date: 2005-03-08
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.escholarship.org/uc/item/4ft420b6.pdf;origin=repeccitec (application/pdf)

Related works:
Journal Article: Parametric Portfolio Policies: Exploiting Characteristics in the Cross-Section of Equity Returns (2009)
Working Paper: Parametric Portfolio Policies: Exploiting Characteristics in the Cross Section of Equity Returns (2004)
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:cdl:anderf:qt4ft420b6

Access Statistics for this paper

More papers in University of California at Los Angeles, Anderson Graduate School of Management from Anderson Graduate School of Management, UCLA Contact information at EDIRC.
Bibliographic data for series maintained by Lisa Schiff ().