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An Asymptotic Theory for Estimating Beta-Pricing Models Using Cross-Sectional Regression

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Author Info
Ravi Jagannathan (Kellogg Graduate School of Management, Northwestern University and Carlson School of Management, University of Minnesota,)
Zhenyu Wang (Graduate School of Business, Columbia University)

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Abstract

Without the assumption of conditional homoskedasticity, a general asymptotic distribution theory for the two-stage cross-sectional regression method shows that the standard errors produced by the Fama-MacBeth procedure do not necessarily overstate the precision of the risk premium estimates. When factors are misspecified, estimators for risk premiums can be biased, and the "t"-value of a premium may converge to infinity in probability even when the true premium is zero. However, when a beta-pricing model is misspecified, the "t"-values for firm characteristics generally converge to infinity in probability, which supports the use of firm characteristics in cross-sectional regressions for detecting model misspecification. Copyright The American Finance Association 1998.

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Publisher Info
Article provided by American Finance Association in its journal The Journal of Finance.

Volume (Year): 53 (1998)
Issue (Month): 4 (08)
Pages: 1285-1309
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Handle: RePEc:bla:jfinan:v:53:y:1998:i:4:p:1285-1309

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