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Ex-post risk premia estimation and asset pricing tests using large cross sections: The regression-calibration approach

Soohun Kim and Georgios Skoulakis

Journal of Econometrics, 2018, vol. 204, issue 2, 159-188

Abstract: We propose a modification of the two-pass cross-sectional regression approach for estimating ex-post risk premia in linear asset pricing models, suitable for the case of large cross sections and short time series. Employing the regression-calibration method, we provide a beta correction method, which deals with the error-in-variables problem, based on which we construct an N-consistent estimator of ex-post risk premia and develop associated novel asset pricing tests. Empirically, we reject the implications of the CAPM and the Fama–French three-factor and five-factor models but also offer new evidence on the relevance of the HML factor for pricing large cross sections of individual stocks.

Keywords: Large cross section; N-consistent ex-post risk premia estimator; Asset pricing tests (search for similar items in EconPapers)
Date: 2018
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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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Handle: RePEc:eee:econom:v:204:y:2018:i:2:p:159-188