Bayesian inference for a semi-parametric copula-based Markov chain

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Azam, Kazim ; Pitt, Michael K. (2014)
  • Publisher: University of Warwick. Department of Economics
  • Subject: QA

This paper presents a method to specify a strictly stationary univariate time series model with particular emphasis on the marginal characteristics (fat tailedness, skewness etc.). It is the first time in time series models with specified marginal distribution, a non-parametric specification is used. Through a Copula distribution, the\ud marginal aspect are separated and the information contained within the order statistics allow to efficiently model a discretely-varied time series. The estimation is done through Bayesian method. The method is invariant to any copula family and for any level of heterogeneity in the random variable. Using count times series of weekly rearm homicides in Cape Town, South Africa, we show our method efficiently estimates the copula parameter representing the first-order Markov chain transition density.
  • References (34)
    34 references, page 1 of 4

    Al-Osh, M. A. and Alzaid, A. A. First-order integer-valued autoregressive (inar(1)) process. Journal of Time Series Analysis, 8(3):261{275, 1987.

    Baillie, Richard T.; Bollerslev, Tim, and Mikkelsen, Hans Ole. Fractionally integrated generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 74(1):3{30, September 1996.

    Beare, Brendan K. Copulas and temporal dependence. Econometrica, 78(1):395{410, 2010a.

    Beare, Brendan K. Archimedean copulas and temporal dependence. University of california at san diego, economics working paper series, Department of Economics, UC San Diego, Sep 2010b.

    Bollerslev, Tim. Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3): 307{327, April 1986.

    Bouye, Eric; Durrleman, Valdo; Nikeghbali, Ashkan; Riboulet, Gael, and Roncalli, Thierry. Copulas for nance - a reading guide and some applications. Social Science Research Network Working Paper Series, November 2007.

    Chen, Xiaohong and Fan, Yanqin. Estimation of copula-based semiparametric time series models. Working Papers 0226, Department of Economics, Vanderbilt University, October 2002.

    Chen, Xiaohong; Wu, Wei Biao, and Yi, Yanping. E cient estimation of copula-based semiparametric markov models. Cowles Foundation Discussion Papers 1691, Cowles Foundation for Research in Economics, Yale University, February 2009.

    Cherubini, U. and Luciano, E. Value-at-risk trade-o and capital allocation with copulas. Economic Notes, 30 (2), 2001.

    Chib, Siddhartha and Greenberg, Edward. Analysis of multivariate probit models. Biometrika, pages 347{361, 1998.

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