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Empirical and sequential empirical copula processes under serial dependence

Author

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  • Bücher, Axel
  • Volgushev, Stanislav
Abstract
Empirical and sequential empirical copula processes play a central role for statistical inference on copulas. However, as pointed out by Johan Segers [J. Segers, Asymptotics of empirical copula processes under non-restrictive smoothness assumptions, Bernoulli 18 (3) (2012) 764–782] the usual assumptions under which these processes have been studied so far are too restrictive. In this paper, we provide a unified approach to the analysis of empirical and sequential empirical copula processes that circumvents those restrictive assumptions in a very general setting. In particular, our methods allow for an easy analysis of copula processes and appropriate bootstrap approximations in the setting of sequentially dependent data. One particularly useful finding is that certain sequential empirical copula processes converge without any smoothness assumptions on the copula.

Suggested Citation

  • Bücher, Axel & Volgushev, Stanislav, 2013. "Empirical and sequential empirical copula processes under serial dependence," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 61-70.
    • Handle: RePEc:eee:jmvana:v:119:y:2013:i:c:p:61-70
    DOI: 10.1016/j.jmva.2013.04.003
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    References listed on IDEAS

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    6. Segers, Johan, 2012. "Asymptotics of empirical copula processes under non-restrictive smoothness assumptions," LIDAM Reprints ISBA 2012009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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