structure is modeled through a Gaussian copula function. Markov chain Monte Carlo methods are used to simulate from the …

Purpose – In this chapter, copula theory is used to model dependence structure between hedge fund returns series …” copula. After estimating the parametric copula that best fits the used data, we apply previous results to construct the … cumulative distribution functions of the equally weighted portfolios. Findings – The empirical validation shows that copula …

Gaussian copula is by far the most popular copula used in the financial industry in default dependency modeling …. However, it has a major drawback – it does not exhibit tail dependence, a very important property for copula. The essence of … that some tail dependence can be restored by introducing stochastic volatility on a Gaussian copula. Using perturbation …

We have developed a new family of Archimedean copula processes for modeling the dynamic dependence between default … constructing these processes, we focus on a specific one with lower tail dependence as in the Clayton copula. Using CDS data as on …

(CDO) tranches in the market-standard, single-factor, Gaussian copula model with base correlation. We introduce a novel …

. The copula approach allows marginal models to be constructed for each variable separately and joined with a dependence … structure characterized by a copula. The class of multivariate copulas was limited for a long time to elliptical (including the … Gaussian and t-copula) and Archimedean families (such as Clayton and Gumbel copulas). Both classes are rather restrictive with …

observations of network nodes are correlated, an optimal copula-based fusion (termed CBF) rule is designed for correlated binary … nodes. In this paper, we propose a fast copula-based fusion (F-CBF) algorithm for a multi-node radar system. The correlation …