Empirical Tests of Asset Pricing Models with Individual Assets: Resolving the Errors-in-Variables Bias in Risk Premium Estimation
Abstract
To attenuate an inherent errors-in-variables bias, portfolios are widely employed to test asset pricing models; but portfolios might mask relevant risk- or return-related features of individual stocks. We propose an instrumental variables approach that allows the use of individual stocks as test assets, yet delivers consistent estimates of ex post risk premiums. This estimator also yields well-specified tests in small samples. The market risk premium under the capital asset pricing model (CAPM) and the liquidity-adjusted CAPM, premiums on risk factors under the Fama-French three- and five-factor models, and the Hou, Xue, and Zhang (2015) four-factor model are all insignificant after controlling for asset characteristics.
Additional Information
© 2019 Elsevier B.V. Received 28 September 2015, Revised 26 April 2018, Accepted 8 May 2018, Available online 14 February 2019. For insightful and constructive comments, we thank the referee, Bill Schwert (the editor), Yakov Amihud, Francisco Barillas, Hank Bessembinder, Michael Brennan, Tarun Chordia, John Cochrane, Wayne Ferson, Chris Jones, Raymond Kan, Cheng-Few Lee, Jay Shanken, Georgios Skoulakis, Avanidhar Subrahmanyam, Guofu Zhou, and seminar participants at Caltech, Case Western Reserve University, Emory University, KAIST, UCLA, University of Melbourne, University of Missouri, University of New South Wales, University of South Florida, University of Technology at Sydney, Yonsei University, York University, Financial Management Association Meetings 2014, Northern Finance Association Meetings 2017, and American Finance Association Meetings 2018.Attached Files
Submitted - SSRN-id2897821.pdf
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Additional details
- Eprint ID
- 92938
- Resolver ID
- CaltechAUTHORS:20190214-123253711
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2019-02-15Created from EPrint's datestamp field
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2021-11-16Created from EPrint's last_modified field