This paper suggests a goodness-of-fit test for parametric families of Archimedean copulas for high dimensional distributions. The test statistic is based on the classical chi-square-statistic but has a nonstandard asymptotic distribution. Monte-Carlo simulations show that the test keeps the...

We introduce the notion of realized copula. Based on assumptions of the marginal distributions of daily stock returns and a copula family, realized copula is defined as the copula structure materialized in realized covariance estimated from within-day high-frequency data. Copula parameters are...

In this paper we propose a new pricing methodology for European multi-asset options based on the family of normal mean-variance mixture copulas. The goal is to develop a copula-based method with the flexibility to reproduce the correlation skew, and at the same time efficient enough to be used...

Grouped normal variance mixtures are a class of multivariate distributions that generalize classical normal variance mixtures such as the multivariate t distribution, by allowing different groups to have different (comonotone) mixing distributions. This allows one to better model risk factors...