In general, risk of an extreme outcome in financial markets can be expressed as a function of the tail copula of a high-dimensional vector after standardizing marginals. Hence it is of importance to model and estimate tail copulas. Even for moderate dimension, nonparametrically estimating a tail...

We present a joint copula-based model for insurance claims and sizes. It uses bivariate copulae to accommodate for the dependence between these quantities. We derive the general distribution of the policy loss without the restrictive assumption of independence. We illustrate that this...

The copula function defines the degree of dependence and the structure of dependence. This paper proposes an alternative framework to decompose the dependence using quantile regression. We demonstrate that the methodology provides a detailed picture of dependence including asymmetric and...

In many cases of modeling bivariate count data, the interest lies on studying the association rather than the marginal properties. We form a flexible regression copula-based model where covariates are used not only for the marginal but also for the copula parameters. Since copula measures the...

The standard approaches used in the empirical literature to test economic convergence-divergence between countries and regions are all grounded on the Mankiw-Romer-Weil and Barro-Sala-i-Martin contributions that led to the celebrated b-convergence model. Such a model, however, presents strong...

This book is a collaborative effort from three workshops held over the last three years, all involving principal contributors to the vine-copula methodology. Research and applications in vines have been growing rapidly and there is now a growing need to collate basic results, and standardize...