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Copula–GARCH Time-Varying Tail Dependence

In: 30th Anniversary Edition

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  • Jiaqi Chen
  • Jeffery W. Gunther

Abstract

Tail-dependence evolution for the symmetrized Joe–Clayton copula is proposed to depend on an exponentially weighted moving average (EWMA) of the absolute difference in probability integral transforms. Using these dynamics, time-varying tail dependence between bank and insurance equity prices is assessed in a parametric copula, generalized autoregressive conditional heteroscedastic framework. The results suggest a relatively long lag and support the EWMA lag structure as an effective estimation vehicle. Tail dependence is shown often to tend higher during periods of market stress.

Suggested Citation

  • Jiaqi Chen & Jeffery W. Gunther, 2012. "Copula–GARCH Time-Varying Tail Dependence," Advances in Econometrics, in: 30th Anniversary Edition, pages 411-425, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(2012)0000030018
    DOI: 10.1108/S0731-9053(2012)0000030018
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    Keywords

    Copula; dependence; time-varying;
    All these keywords.

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