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Characterization of dependence of multidimensional Lévy processes using Lévy copulas

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  • Kallsen, Jan
  • Tankov, Peter

Abstract

This paper suggests Lévy copulas in order to characterize the dependence among components of multidimensional Lévy processes. This concept parallels the notion of a copula on the level of Lévy measures. As for random vectors, a version of Sklar's theorem states that the law of a general multivariate Lévy process is obtained by combining arbitrary univariate Lévy processes with an arbitrary Lévy copula. We construct parametric families of Lévy copulas and prove a limit theorem, which indicates how to obtain the Lévy copula of a multivariate Lévy process X from the ordinary copula of the random vector Xt for small t.

Suggested Citation

  • Kallsen, Jan & Tankov, Peter, 2006. "Characterization of dependence of multidimensional Lévy processes using Lévy copulas," Journal of Multivariate Analysis, Elsevier, vol. 97(7), pages 1551-1572, August.
    • Handle: RePEc:eee:jmvana:v:97:y:2006:i:7:p:1551-1572
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    References listed on IDEAS

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    1. Dilip B. Madan & Peter P. Carr & Eric C. Chang, 1998. "The Variance Gamma Process and Option Pricing," Review of Finance, European Finance Association, vol. 2(1), pages 79-105.
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    3. Sato, Ken-iti, 2001. "Subordination and self-decomposability," Statistics & Probability Letters, Elsevier, vol. 54(3), pages 317-324, October.
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    Keywords

    Lévy process Copula Limit theorems;

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