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Efficient Estimation of Conditional Asset-Pricing Models

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  • Hodgson, Douglas J
  • Vorkink, Keith P

Abstract

A semiparametric efficient estimation procedure is developed for the parameters of multivariate generalized autoregressive conditional heteroscedasticity-in-mean models when the disturbances have a conditional distribution assumed to be elliptically symmetric but otherwise unrestricted. Under high-level assumptions, the resulting estimator achieves the asymptotic semiparametric efficiency bound. The elliptical symmetry assumption allows us to avert the curse of dimensionality problem that would otherwise arise in estimating the unknown error distribution. This framework is suitable for the estimation and testing of conditional asset-pricing models, such as the conditional capital asset-pricing model. We apply our procedure in an empirical study of stock prices, with Monte Carlo simulation results also reported.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 21 (2003)
Issue (Month): 2 (April)
Pages: 269-83

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Handle: RePEc:bes:jnlbes:v:21:y:2003:i:2:p:269-83

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Citations

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Cited by:
  1. BEAULIEU, Marie-Claude & DUFOUR, Jean-Marie & KHALAF, Lynda, 2005. "Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions," Cahiers de recherche 2005-04, Universite de Montreal, Departement de sciences economiques.
  2. Douglas J Hodgson & Oliver Linton & Keith Vorkink, 2000. "Testing the capital asset pricing model efficiently under elliptical symmetry : a semiparametric approach," LSE Research Online Documents on Economics 2197, London School of Economics and Political Science, LSE Library.
  3. Enrique Sentana & Gabriele Fiorentini, 2007. "On The Efficiency And Consistency Of Likelihood Estimation In Multivariate Conditionally Heteroskedastic Dynamic Regression Models," Working Papers wp2007_0713, CEMFI.
  4. Douglas Hodgson & Barrett Slade & Keith Vorkink, 2006. "Constructing Commercial Indices: A Semiparametric Adaptive Estimator Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 32(2), pages 151-168, March.
  5. Alexeev, Vitali & Maynard, Alex, 2012. "Localized level crossing random walk test robust to the presence of structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3322-3344.
  6. Rombouts, Jeroen V. K. & Hafner, Christian M., 2004. "Semiparametric multivariate volatility models," Papers 2004,14, Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE).
  7. Huffer, Fred W. & Park, Cheolyong, 2007. "A test for elliptical symmetry," Journal of Multivariate Analysis, Elsevier, vol. 98(2), pages 256-281, February.
  8. Bent Jesper Christensen & Christian M. Dahl & Emma M. Iglesias, 2008. "Semiparametric Inference in a GARCH-in-Mean Model," CREATES Research Papers 2008-46, School of Economics and Management, University of Aarhus.
  9. Gabriele Fiorentini & Enrique Sentana, 2010. "Dynamic Specification Tests for Static Factor Models," Working Paper Series 04_10, The Rimini Centre for Economic Analysis.
  10. Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2013. "Sequential estimation of shape parameters in multivariate dynamic models," Journal of Econometrics, Elsevier, vol. 177(2), pages 233-249.
  11. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2010. "Asset-pricing anomalies and spanning: Multivariate and multifactor tests with heavy-tailed distributions," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 763-782, September.
  12. Gabriele Fiorentini & Enrique Sentana, 2012. "Tests For Serial Dependence In Static, Non-Gaussian Factor Models," Working Papers wp2012_1211, CEMFI.

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