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On sample marginal quantiles for stationary processes

Author

Listed:
  • Yves Dominicy
  • Siegfried Hörmann
  • Hiroaki Ogata
  • David Veredas

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.
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Suggested Citation

  • Yves Dominicy & Siegfried Hörmann & Hiroaki Ogata & David Veredas, 2013. "On sample marginal quantiles for stationary processes," ULB Institutional Repository 2013/136283, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:ulb:ulbeco:2013/136283
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    References listed on IDEAS

    as
    1. Sen, Pranab Kumar, 1972. "On the Bahadur representation of sample quantiles for sequences of [phi]-mixing random variables," Journal of Multivariate Analysis, Elsevier, vol. 2(1), pages 77-95, March.
    2. Jean-David FERMANIAN & Olivier SCAILLET, 2003. "Nonparametric Estimation of Copulas for Time Series," FAME Research Paper Series rp57, International Center for Financial Asset Management and Engineering.
    3. Oberhofer, Walter & Haupt, Harry, 2005. "The asymptotic distribution of the unconditional quantile estimator under dependence," Statistics & Probability Letters, Elsevier, vol. 73(3), pages 243-250, July.
    4. Jean-David Fermanian & Olivier Scaillet, . "Nonparametric estimation of copulas for time series," Journal of Risk, Journal of Risk.
    5. 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.
    6. Dutta, Kalyan & Sen, Pranab Kumar, 1971. "On the Bahadur representation of sample quantiles in some stationary multivariate autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 1(2), pages 186-198, June.
    7. Berkes, István & Hörmann, Siegfried & Schauer, Johannes, 2009. "Asymptotic results for the empirical process of stationary sequences," Stochastic Processes and their Applications, Elsevier, vol. 119(4), pages 1298-1324, April.
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    Cited by:

    1. Laurent, Sébastien & Shi, Shuping, 2020. "Volatility estimation and jump detection for drift–diffusion processes," Journal of Econometrics, Elsevier, vol. 217(2), pages 259-290.
    2. Lorenzo Ricci & David Veredas, 2012. "TailCoR," Working Papers 1227, Banco de España.
      • Sla{dj}ana Babi'c & Christophe Ley & Lorenzo Ricci & David Veredas, 2020. "TailCoR," Papers 2011.14817, arXiv.org.
    3. 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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