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Specification tests of parametric dynamic conditional quantiles

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  • J. Carlos Escanciano

    ()
    (Economics Department - Indiana University)

  • Carlos Velasco

    ()
    (Departamento de Economía. Universidad Carlos III de Madrid. Calle Madrid 126 - Departamento de Economía. Universidad Carlos III de Madrid. Calle Madrid 126)

Abstract

This article proposes omnibus specification tests of parametric dynamic quantile models. Contrary to the existing procedures, we allow for a flexible specification, where a possibly continuum of quantiles are simultaneously specified under fairly weak conditions on the serial dependence in the underlying data generating process. Since the null limit distribution of tests is not pivotal, we propose a subsampling approximation of the asymptotic critical values. A Monte Carlo study shows that the asymptotic results provide good approximations for small sample sizes. Finally, an application suggests that our methodology is a powerful alternative to standard backtesting procedures in evaluating market risk.

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Bibliographic Info

Paper provided by HAL in its series Post-Print with number peer-00732534.

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Date of creation: 15 Sep 2010
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Publication status: Published, Journal of Econometrics, 2010, 159, 1, 209
Handle: RePEc:hal:journl:peer-00732534

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Related research

Keywords: C12; C22; Omnibus tests; Conditional quantiles; Nonlinear time series; Empirical processes; Quantile processes; Subsampling; Value-at-risk; Tail risk;

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References

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Citations

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Cited by:
  1. Antonio Galvao & Kengo Kato & Gabriel Montes-Rojas & Jose Olmo, 2014. "Testing linearity against threshold effects: uniform inference in quantile regression," Annals of the Institute of Statistical Mathematics, Springer, Springer, vol. 66(2), pages 413-439, April.
  2. Francesco Bravo, 2013. "Partially linear varying coefficient models with missing at random responses," Annals of the Institute of Statistical Mathematics, Springer, Springer, vol. 65(4), pages 721-762, August.
  3. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, Springer, vol. 22(3), pages 361-411, September.
  4. Escanciano, J.C. & Goh, S.C., 2014. "Specification analysis of linear quantile models," Journal of Econometrics, Elsevier, Elsevier, vol. 178(P3), pages 495-507.
  5. Song Xi Chen & Jiti Gao, 2010. "Simultaneous Testing of Mean and Variance Structures in Nonlinear Time Series Models," School of Economics Working Papers, University of Adelaide, School of Economics 2010-28, University of Adelaide, School of Economics.
  6. Juan Carlos Escanciano & Chuan Goh, 2010. "Specification Analysis of Structural Quantile Regression Models," Working Papers tecipa-415, University of Toronto, Department of Economics.
  7. Christoph Rothe & Dominik Wied, 2013. "Misspecification Testing in a Class of Conditional Distributional Models," Journal of the American Statistical Association, Taylor & Francis Journals, Taylor & Francis Journals, vol. 108(501), pages 314-324, March.

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