Estimating and Testing Beta Pricing Models: Alternative Methods and Their Performance in Simulations

59 Pages Posted: 8 May 2006 Last revised: 11 Jun 2022

See all articles by Jay A. Shanken

Jay A. Shanken

Emory University - Goizueta Business School; National Bureau of Economic Research (NBER)

Guofu Zhou

Washington University in St. Louis - John M. Olin Business School

Multiple version iconThere are 2 versions of this paper

Date Written: February 2006

Abstract

In this paper, we conduct a simulation analysis of the Fama and MacBeth (1973) two-pass procedure, as well as maximum likelihood (ML) and generalized method of moments estimators of cross-sectional expected return models. We also provide some new analytical results on computational issues, the relations between estimators, and asymptotic distributions under model misspecification. The GLS estimator is often much more precise than the usual OLS estimator, but it displays more bias as well. A "truncated" form of ML performs quite well overall in terms of bias and precision, but produces less reliable inferences than the OLS estimator.

Suggested Citation

Shanken, Jay A. and Zhou, Guofu, Estimating and Testing Beta Pricing Models: Alternative Methods and Their Performance in Simulations (February 2006). NBER Working Paper No. w12055, Available at SSRN: https://ssrn.com/abstract=885652

Jay A. Shanken (Contact Author)

Emory University - Goizueta Business School ( email )

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Guofu Zhou

Washington University in St. Louis - John M. Olin Business School ( email )

Washington University
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United States
314-935-6384 (Phone)
314-658-6359 (Fax)

HOME PAGE: http://apps.olin.wustl.edu/faculty/zhou/

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