Optimal Characteristic Portfolios

56 Pages Posted: 13 Jul 2020 Last revised: 20 Jul 2020

See all articles by Richard McGee

Richard McGee

University College Dublin (UCD), College of Business and Law, UCD School of Business, Michael Smurfit Graduate School of Business, Students; Smurfit Business School

Jose Olmo

Universidad de Zaragoza; University of Southampton

Date Written: June 29, 2020

Abstract

Characteristic-sorted portfolios are the workhorses of modern empirical finance, deployed widely to evaluate anomalies and construct asset pricing models. We propose a new method for their estimation that is simple to compute; makes no ex-ante assumption on the nature of the relationship between the characteristic and returns; and does not require ad hoc selections of percentile breakpoints or portfolio weighting schemes. Characteristic portfolio weights are implied directly from data, through maximizing the expected value of a mean-variance utility function estimated non-parametrically over the cross section of the assets. To illustrate the method we use it to evaluate the size, value and momentum anomalies.

Keywords: anomalies, portfolio sorts, size effect, value effect, momentum

JEL Classification: G11, G12

Suggested Citation

McGee, Richard and Olmo, Jose, Optimal Characteristic Portfolios (June 29, 2020). Michael J. Brennan Irish Finance Working Paper Series Research Paper No. 20-6, Available at SSRN: https://ssrn.com/abstract=3638177 or http://dx.doi.org/10.2139/ssrn.3638177

Richard McGee (Contact Author)

University College Dublin (UCD), College of Business and Law, UCD School of Business, Michael Smurfit Graduate School of Business, Students ( email )

Blackrock
Ireland

Smurfit Business School ( email )

Blackrock, Co. Dublin
Ireland

Jose Olmo

Universidad de Zaragoza ( email )

Gran Via, 2
50005 Zaragoza, Zaragoza 50005
Spain

University of Southampton ( email )

Southampton
United Kingdom

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