Tails of correlation mixtures of elliptical copulas

By H. Manner, Johan Segers. 2009

59 citations recorded by the source corpus.

Correlation mixtures of elliptical copulas arise when the correlation parameter is driven itself by a latent random process. For such copulas, both penultimate and asymptotic tail dependence are much larger than for ordinary elliptical copulas with the same unconditional correlation. Furthermore, for Gaussian and Student t-copulas, tail dependence at sub-asymptotic levels is generally larger than in the limit, which can have serious consequences for estimation and evaluation of extreme risk. Finally, although correlation mixtures of Gaussian copulas inherit the property of asymptotic independence, at the same time they fall in the newly defined category of near asymptotic dependence. The consequences of these findings for modeling are assessed by means of a simulation study and a case study involving financial time series.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/3c829673ae2e0755c3bc81a026f658c5fe14e8ca

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In Finance

  1. D. Oh
  2. Andrew J. Patton
  3. S. J. Koopman
  4. André Lucas
  5. Tim Bollerslev
  6. Kevin Sheppard
  7. Brendan K. Beare
  8. Gregor Kastner

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