On Modelling Human Population Characteristics with Copulas

Modelling Copulas: An Overview

Modelling Sample Selection Using Copulas

By a theorem due to Sklar, a multivariate distribution can be represented in terms of its underlying margins by binding them together using a copula function. By exploiting this representation, the “copula approach” to modelling proceeds by specifying distributions for each margin, and a copula function. In this article, a number of copula functions are given, with attention focusing on members...

Modelling Dependence in High Dimensions with Factor Copulas

This paper presents new models for the dependence structure, or copula, of economic variables, and asymptotic results for new simulation-based estimators of these models. The proposed models are based on a factor structure for the copula and are particularly attractive for high dimensional applications, involving …fty or more variables. Estimation of this class of models is complicated by the l...

Multivariate Operational Risk: Dependence Modelling with Lévy Copulas

Simultaneous modelling of operational risks occurring in different event type/business line cells poses the challenge for operational risk quantification. Invoking the new concept of Lévy copulas for dependence modelling yields simple approximations of high quality for multivariate operational VAR.

On Trivariate Copulas with Bivariate Linear Spearman Marginal Copulas

Based on the trivariate reduction technique two different trivariate Bernoulli mixtures of univariate uniform distributions and their associated trivariate copulas with bivariate linear Spearman marginal copulas are considered. Mathematical characterizations of these Bernoulli mixture models are obtained. Since Bernoulli mixture trivariate reduction copulas are not compatible with all valid gra...