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

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Author Info

  • 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)

Abstract

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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Bibliographic Info

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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Handle: RePEc:jae:japmet:v:25:y:2010:i:2:p:263-285

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References

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  5. 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.
  6. 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.
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  10. Jean-Marie Dufour & Lynda Khalaf & Marie-Claude Beaulieu, 2003. "Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-Fit in Multivariate Regressions with Application to Asset Pricing Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 891-906, December.
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Cited by:
  1. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests For Static Factor Models," Working Papers wp2009_0912, CEMFI.
  2. Barrera, Carlos R., 2011. "Impacto amplificador del ajuste de inventarios ante choques de demanda según especificaciones flexibles," Working Papers 2011-009, Banco Central de Reserva del Perú.
  3. Grier, Kevin B. & Smallwood, Aaron D., 2013. "Exchange rate shocks and trade: A multivariate GARCH-M approach," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 282-305.

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