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Capital Asset Pricing with a Stochastic Horizon

Published online by Cambridge University Press:  24 October 2018

Michael J. Brennan  and
Yuzhao Zhang
Michael J. Brennan
Affiliation:
Brennan, michaelbrennan830@gmail.com, University of California–Los Angeles Anderson School and Manchester University
Yuzhao Zhang*
Affiliation:
Zhang, yzhang@business.rutgers.edu, Rutgers University Business School
*
Zhang (corresponding author), yzhang@business.rutgers.edu
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Abstract

In this paper we present empirical tests of an extended version of the capital asset pricing model (CAPM) that replaces the single-period horizon with a probability distribution over different horizons. Adopting a simple parameterization of the probability distribution of the length of the horizon, we estimate the parameters of the distribution as well as the parameters of the CAPM. We find that the extended model is not rejected for several different samples of common stocks, and for these samples it outperforms not only the standard CAPM but also the Fama–French (1993) 3-factor model. The probability distribution over horizon dates varies over time with the New York Stock Exchange (NYSE) turnover rate. We also find that returns satisfy the Euler equation of a representative financial institution that holds the market portfolio and has horizon probabilities estimated from 13F filings.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 55 , Issue 3 , May 2020 , pp. 783 - 827
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2018

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Footnotes

This paper has benefited greatly from the comments and suggestions of Jennifer Conrad (the editor) and Joost Driessen (the referee). We also thank John Campbell, Jay Shanken, William Sharpe, Grigor Vilkov, Yan Xu, and participants in seminars at Tilburg University, Erasmus University, and the Stockholm School of Economics, as well as Jonathan Lewellen, our discussant at the Western Finance Association, for comments and suggestions on an earlier version of this paper.

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