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Multivariate residual-based finite-sample tests for serial dependence and ARCH effects with applications to asset pricing models

  • Jean-Marie Dufour

    (Department of Economics, McGill University, Montréal, Québec, Canada)

  • Lynda Khalaf

    (Economics Department, Carleton University, Ottawa, Ontario, Canada)

  • Marie-Claude Beaulieu

    (Département de finance et assurance, Université Laval, Québec City, Québec, Canada)

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR). We focus on tests for serial dependence and ARCH effects with possibly non-Gaussian errors. The tests are based on properly standardized multivariate residuals to ensure invariance to error covariances. The procedures proposed provide: (i) exact variants of standard multivariate portmanteau tests for serial correlation as well as ARCH effects, and (ii) exact versions of the diagnostics presented by Shanken (1990) which are based on combining univariate specification tests. Specifically, we combine tests across equations using a Monte Carlo (MC) test method so that Bonferroni-type bounds can be avoided. The procedures considered are evaluated in a simulation experiment: the latter shows that standard asymptotic procedures suffer from serious size problems, while the MC tests suggested display excellent size and power properties, even when the sample size is small relative to the number of equations, with normal or Student-t errors. The tests proposed are applied to the Fama-French three-factor model. Our findings suggest that the i.i.d. error assumption provides an acceptable working framework once we allow for non-Gaussian errors within 5-year sub-periods, whereas temporal instabilities clearly plague the full-sample dataset. Copyright © 2009 John Wiley & Sons, Ltd.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 25 (2010)
Issue (Month): 2 ()
Pages: 263-285

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  2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
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  6. Dufour, Jean-Marie & Kiviet, Jan F., 1996. "Exact tests for structural change in first-order dynamic models," Journal of Econometrics, Elsevier, vol. 70(1), pages 39-68, January.
  7. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-44.
  8. DUFOUR, Jean-Marie & KHALAF, Lynda & BEAULIEU, Marie-Claude, 2003. "Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-Fit in Multivariate Regressions with Application to Asset Pricing Models," Cahiers de recherche 07-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  9. Dufour, J.M. & Khalaf, L., 2000. "Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions," Cahiers de recherche 2000-11, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  10. Savin, N.E., 1984. "Multiple hypothesis testing," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 14, pages 827-879 Elsevier.
  11. Jean-Marie Dufour, 2005. "Monte Carlo tests with nuisance parameters: a general approach to finite-sample inference and non-standard asymptotics," CIRANO Working Papers 2005s-02, CIRANO.
  12. Dufour, Jean-Marie, 1989. "Nonlinear Hypotheses, Inequality Restrictions, and Non-nested Hypotheses: Exact Simultaneous Tests in Linear Regressions," Econometrica, Econometric Society, vol. 57(2), pages 335-55, March.
  13. Shanken, Jay, 1990. "Intertemporal asset pricing : An Empirical Investigation," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 99-120.
  14. Dufour, J.M. & Khalaf, L. & Bernard, J.T. & Genest, I., 2001. "Simulation-Based Finite-Sample Tests for Heteroskedasticity and ARCH Effects," Cahiers de recherche 2001-08, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  15. Kenneth Stewart, 1997. "Exact testing in multivariate regression," Econometric Reviews, Taylor & Francis Journals, vol. 16(3), pages 321-352.
  16. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2007. "Multivariate Tests of MeanVariance Efficiency With Possibly Non-Gaussian Errors: An Exact Simulation-Based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 398-410, October.
  17. Shanken, Jay, 1986. " Testing Portfolio Efficiency When the Zero-Beta Rate Is Unknown: A Note," Journal of Finance, American Finance Association, vol. 41(1), pages 269-76, March.
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  19. Richardson, Matthew & Smith, Tom, 1993. "A Test for Multivariate Normality in Stock Returns," The Journal of Business, University of Chicago Press, vol. 66(2), pages 295-321, April.
  20. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-31, February.
  21. DeRoon, Frans A. & Nijman, Theo E., 2001. "Testing for mean-variance spanning: a survey," Journal of Empirical Finance, Elsevier, vol. 8(2), pages 111-155, May.
  22. Nijman, T.E. & de Roon, F.A., 2001. "Testing for mean-variance spanning : A survey," Other publications TiSEM 0159f80a-c61b-4519-b004-a, Tilburg University, School of Economics and Management.
  23. Dufour, J.-M., 1986. "Exact tests and confidence sets in linear regressions with autocorrelated errors," CORE Discussion Papers 1986037, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  24. John J. Binder, 1985. "Measuring the Effects of Regulation with Stock Price Data," RAND Journal of Economics, The RAND Corporation, vol. 16(2), pages 167-183, Summer.
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