Multivariate Variance Gamma and Gaussian dependence: a study with copulas

Elisa Luciano and Patrizia Semeraro

No 96, Carlo Alberto Notebooks from Collegio Carlo Alberto

Abstract: This paper explores the dynamic dependence properties of a Levy process, the Variance Gamma, which has non Gaussian marginal features and non Gaussian dependence. In a static context, such a non Gaussian dependence should be represented via copulas. Copulas, however, are not able to capture the dynamics of dependence. By computing the distance between the Gaussian copula and the actual one, we show that even a non Gaussian process, such as the Variance Gamma, can "converge" to linear dependence over time. Empirical versions of different dependence measures confirm the result.

JEL-codes: C16 G12 (search for similar items in EconPapers)
Pages: 11 pages
Date: 2008
New Economics Papers: this item is included in nep-ecm
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.carloalberto.org/wp-content/uploads/2018/11/no.96.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cca:wpaper:96

Access Statistics for this paper

More papers in Carlo Alberto Notebooks from Collegio Carlo Alberto Contact information at EDIRC.
Bibliographic data for series maintained by Giovanni Bert ().