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Finite-sample resampling-based combined hypothesis tests, with applications to serial correlation and predictability

  • Jean-Marie Dufour
  • Lynda Khalaf
  • Marcel Voia

This paper suggests Monte Carlo multiple test procedures which are provably valid in finite samples. These include combination methods originally proposed for independent statistics and further improvements which formalize statistical practice. We also adapt the Monte Carlo test method to non-continuous combined statistics. The methods suggested are applied to test serial dependence and predictability. In particular, we introduce and analyze new procedures that account for endogenous lag selection. A simulation study illustrates the properties of the proposed methods. Results show that concrete and non-spurious power gains (over standard combination methods) can be achieved through the combined Monte Carlo test approach, and confirm arguments in favour of variance-ratio type criteria.

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File URL: http://www.cirano.qc.ca/files/publications/2013s-40.pdf
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Paper provided by CIRANO in its series CIRANO Working Papers with number 2013s-40.

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Length: 24 pages
Date of creation: 01 Oct 2013
Date of revision:
Handle: RePEc:cir:cirwor:2013s-40
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  1. Jean-Marie Dufour & Abdeljelil Farhat & Lucien Gardiol & Lynda Khalaf, 1998. "Simulation-based finite sample normality tests in linear regressions," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C154-C173.
  2. Zhou, Guofu, 1993. " Asset-Pricing Tests under Alternative Distributions," Journal of Finance, American Finance Association, vol. 48(5), pages 1927-42, December.
  3. Fong, Wai Mun & Koh, Seng Kee & Ouliaris, Sam, 1997. "Joint Variance-Ratio Tests of the Martingale Hypothesis for Exchange Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 51-59, January.
  4. Chow, K. Victor & Denning, Karen C., 1993. "A simple multiple variance ratio test," Journal of Econometrics, Elsevier, vol. 58(3), pages 385-401, August.
  5. Dezhbakhsh, Hashem, 1990. "The Inappropriate Use of Serial Correlation Tests in Dynamic Linear Models," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 126-32, February.
  6. Bernard, Jean-Thomas & Idoudi, Nadhem & Khalaf, Lynda & Yelou, Clement, 2007. "Finite sample multivariate structural change tests with application to energy demand models," Journal of Econometrics, Elsevier, vol. 141(2), pages 1219-1244, December.
  7. 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," CIRANO Working Papers 2003s-33, CIRANO.
  8. Dufour, Jean-Marie & Farhat, Abdeljelil & Khalaf, Lynda & Dufour, Jean-Marie, 2004. "Tests multiples simulés et tests de normalité basés sur plusieurs moments dans les modèles de régression," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 501-522, Juin-Sept.
  9. Deschamps, P. J., . "Monte Carlo methodology for LM and LR autocorrelation tests in multivariate regression," CORE Discussion Papers RP -1234, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  10. Yilmaz, Kamil, 2003. "Martingale Property of Exchange Rates and Central Bank Interventions," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 383-95, July.
  11. Politis, D. N. & Romano, Joseph P. & Wolf, Michael, 1997. "Subsampling for heteroskedastic time series," Journal of Econometrics, Elsevier, vol. 81(2), pages 281-317, December.
  12. Kim, Jae H., 2006. "Wild bootstrapping variance ratio tests," Economics Letters, Elsevier, vol. 92(1), pages 38-43, July.
  13. 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.
  14. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
  15. Andrew W. Lo & A. Craig MacKinlay, 1987. "Stock Market Prices Do Not Follow Random Walks: Evidence From a Simple Specification Test," NBER Working Papers 2168, National Bureau of Economic Research, Inc.
  16. Wright, Jonathan H, 2000. "Alternative Variance-Ratio Tests Using Ranks and Signs," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 1-9, January.
  17. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
  18. Whang, Yoon-Jae & Kim, Jinho, 2003. "A multiple variance ratio test using subsampling," Economics Letters, Elsevier, vol. 79(2), pages 225-230, May.
  19. 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.
  20. Amélie Charles & Olivier Darne, 2009. "Variance ratio tests of random walk: An overview," Post-Print hal-00771078, HAL.
  21. 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.
  22. Kilian, Lutz & Demiroglu, Ufuk, 2000. "Residual-Based Tests for Normality in Autoregressions: Asymptotic Theory and Simulation Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 40-50, January.
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