An asymptotic theory for estimating beta-pricing models using cross-sectional regression

Ravi Jagannathan, Zhenyu Wang

Research output: Contribution to journalArticlepeer-review

113 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1285-1309
Number of pages25
JournalJournal of Finance
Volume53
Issue number4
DOIs
StatePublished - Aug 1998

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics

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