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Empirical tests of asset pricing models with individual assets: Resolving the errors-in-variables bias in risk premium estimation

Narasimhan Jegadeesh, Joonki Noh, Kuntara Pukthuanthong, Richard Roll and Junbo Wang

Journal of Financial Economics, 2019, vol. 133, issue 2, 273-298

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 et al. (2015) four-factor model are all insignificant after controlling for asset characteristics.

Keywords: Risk premium estimation; Errors-in-variables bias; Instrumental variables; Individual stocks; Asset pricing models (search for similar items in EconPapers)
JEL-codes: G11 G12 (search for similar items in EconPapers)
Date: 2019
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Handle: RePEc:eee:jfinec:v:133:y:2019:i:2:p:273-298