Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1147304 | Journal of Multivariate Analysis | 2006 | 22 Pages |
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis