Bayesian Inference in Multivariate Stable Distributions Using Copulae

12 Pages Posted: 10 Feb 2013

See all articles by Efthymios G. Tsionas

Efthymios G. Tsionas

Athens University of Economics and Business - Department of Economics

Date Written: February 10, 2013

Abstract

In this paper we take up Bayesian inference in multivariate stable distributions through innovative multivariate stable copulae. The problem that the characteristic function is defined through a difficult object, the spectral measure is completely bypassed by our approach. The new methods are applied to major exchange rates with encouraging results. The copula-based technique is based on non-parametric margins (both data-estimated as well as Dirichlet process priors) and we compare with a multivariate stable copula whose margins can be normal, Student-t or univariate stable.

Keywords: Multivariate Stable Distributions, Bayesian inference, spectral measure, copula

JEL Classification: C11, C13

Suggested Citation

Tsionas, Efthymios (Efthymios) G., Bayesian Inference in Multivariate Stable Distributions Using Copulae (February 10, 2013). Available at SSRN: https://ssrn.com/abstract=2214612 or http://dx.doi.org/10.2139/ssrn.2214612

Efthymios (Efthymios) G. Tsionas (Contact Author)

Athens University of Economics and Business - Department of Economics ( email )

76 Patission Street
GR-10434 Athens
Greece
+301 8203 (Phone)
+301 8203 301 (Fax)

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