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Marginal quantiles for stationary processes

Author

Listed:
  • Yves Dominicy

    (Université libre de Bruxelles)

  • Siegfried Hörmann

    (Université libre de Bruxelles)

  • David Veredas

    (Université libre de Bruxelles)

  • Hiroaki Ogata

    (Waseda University)

Abstract

We establish the asymptotic normality of marginal sample quantiles for S-mixing vector stationary processes. S-mixing is a recently introduced and widely applicable notion of dependence. Results of some Monte Carlo simulations are given

Suggested Citation

  • Yves Dominicy & Siegfried Hörmann & David Veredas & Hiroaki Ogata, 2012. "Marginal quantiles for stationary processes," Working Papers 1228, Banco de España.
    • Handle: RePEc:bde:wpaper:1228
    as

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    File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/12/Fich/dt1228e.pdf
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    References listed on IDEAS

    as
    1. Babu, G. Jogesh & Rao, C. Radhakrishna, 1988. "Joint asymptotic distribution of marginal quantiles and quantile functions in samples from a multivariate population," Journal of Multivariate Analysis, Elsevier, vol. 27(1), pages 15-23, October.
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    Cited by:

    1. Christian Francq & Jean-Michel Zakoian, 2014. "Multi-level Conditional VaR Estimation in Dynamic Models," Working Papers 2014-01, Center for Research in Economics and Statistics.
    2. Lajos Horváth & Gregory Rice, 2014. "Extensions of some classical methods in change point analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 219-255, June.

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    More about this item

    Keywords

    Quantiles; S-mixing;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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