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Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach

Author

Listed:
  • Keith Vorkink

    (Mariott School of Management, Brigham Young University, Provo UT 84602, USA)

  • Douglas J. Hodgson

    (Department of Economics, University of Rochester, NY 14627-0156, USA)

  • Oliver Linton

    (Department of Economics, London School of Economics, Houghton Street, London WC2A 2AE, UK)

Abstract

We develop new tests of the capital asset pricing model that take account of and are valid under the assumption that the distribution generating returns is elliptically symmetric; this assumption is necessary and sufficient for the validity of the CAPM. Our test is based on semiparametric efficient estimation procedures for a seemingly unrelated regression model where the multivariate error density is elliptically symmetric, but otherwise unrestricted. The elliptical symmetry assumption allows us to avoid the curse of dimensionality problem that typically arises in multivariate semiparametric estimation procedures, because the multivariate elliptically symmetric density function can be written as a function of a scalar transformation of the observed multivariate data. The elliptically symmetric family includes a number of thick-tailed distributions and so is potentially relevant in financial applications. Our estimated betas are lower than the OLS estimates, and our parameter estimates are much less consistent with the CAPM restrictions than the corresponding OLS estimates. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • Keith Vorkink & Douglas J. Hodgson & Oliver Linton, 2002. "Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 617-639.
    • Handle: RePEc:jae:japmet:v:17:y:2002:i:6:p:617-639
    DOI: 10.1002/jae.646
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    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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