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A note on the estimation of asset pricing models using simple regression betas

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  • Raymond Kan
  • Cesare Robotti

Abstract

Since Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973), the two-pass cross-sectional regression (CSR) methodology has become the most popular tool for estimating and testing beta asset pricing models. In this paper, we focus on the case in which simple regression betas are used as regressors in the second-pass CSR. Under general distributional assumptions, we derive asymptotic standard errors of the risk premia estimates that are robust to model misspecification. When testing whether the beta risk of a given factor is priced, our misspecification robust standard error and the Jagannathan and Wang (1998) standard error (which is derived under the correctly specified model) can lead to different conclusions.

Suggested Citation

  • Raymond Kan & Cesare Robotti, 2009. "A note on the estimation of asset pricing models using simple regression betas," FRB Atlanta Working Paper 2009-12, Federal Reserve Bank of Atlanta.
    • Handle: RePEc:fip:fedawp:2009-12
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    References listed on IDEAS

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    1. Raymond Kan & Cesare Robotti & Jay Shanken, 2013. "Pricing Model Performance and the Two‐Pass Cross‐Sectional Regression Methodology," Journal of Finance, American Finance Association, vol. 68(6), pages 2617-2649, December.
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    Cited by:

    1. Raymond Kan & Cesare Robotti & Jay Shanken, 2013. "Pricing Model Performance and the Two‐Pass Cross‐Sectional Regression Methodology," Journal of Finance, American Finance Association, vol. 68(6), pages 2617-2649, December.
    2. Massimo Guidolin & Martin Lozano & Juan Arismendi Zambrano, "undated". "Multifactor Empirical Asset Pricing Under Higher-Order Moment Variations," Economics Department Working Paper Series n304-20.pdf, Department of Economics, National University of Ireland - Maynooth.

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    Keywords

    Asset pricing; Econometric models;

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