Linear-Betas in the Cross-Section of Returns

52 Pages Posted: 16 Feb 2020 Last revised: 10 Nov 2022

See all articles by Reed Douglas

Reed Douglas

University of Southern California, Department of Finance and Business Economics

Date Written: January 10, 2022

Abstract

This paper evaluates the in-sample, out-of-sample, and subperiod characteristics of cross-sectional conditional beta models following Fama and French (2020) and Fama and MacBeth (1973). This class of model generally assumes that risk-premiums are linear in the characteristics used to generate them, but I explore the performance of risk-premiums generated using characteristics as inputs to a simple function. In-sample, I reject the linear Fama and French model that assumes characteristics are conditional betas in favor of a linear conditional beta model following Shanken (1990) which provides a significantly lower zero-beta rate. Out-of-sample, I find the linear-beta model has a lower bias and Clark and West (2007)-adjusted MSPE, but comes at the cost of a larger variance than the Fama and French model.

Keywords: Fama-MacBeth, Cross-Section, Time-Varying Beta, Linear-Beta Model

JEL Classification: G10, G12, G19

Suggested Citation

Douglas, Reed, Linear-Betas in the Cross-Section of Returns (January 10, 2022). Available at SSRN: https://ssrn.com/abstract=3522641 or http://dx.doi.org/10.2139/ssrn.3522641

Reed Douglas (Contact Author)

University of Southern California, Department of Finance and Business Economics ( email )

CA
United States

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