This survey reviews the large and growing literature on copula-based models for economic
and financial time series. Copula-based multivariate models allow the researcher to specify …

Copula-based models provide a great deal of flexibility in modeling multivariate
distributions, allowing the researcher to specify the models for the marginal distributions …

Dependence Modeling with Copulas covers the substantial advances that have taken place
in the field during the last 15 years, including vine copula modeling of high-dimensional …

The official history of copulas begins in 1959 with Sklar [1959]; but, as is often the case in
Mathematics, for groundbreaking results there are forerunners and precedents. These latter …

This book introduces the main theoretical findings related to copulas and shows how
statistical modeling of multivariate continuous distributions using copulas can be carried out …

Almost all existing nonlinear multivariate time series models remain linear, conditional on a
point in time or latent regime. Here, an alternative is proposed, where nonlinear serial and …

Copulas are functions that describe the dependence between two or more random
variables. This article provides a brief review of copula theory and two areas of economics in …

Over the decades that have passed since they were introduced, copulae still remain a very
powerful tool for modeling and estimating multivariate distributions. This work gives an …

Multivariate time series exhibit two types of dependence: across variables and across time
points. Vine copulas are graphical models for the dependence and can conveniently capture …

Copula modelling is a popular tool in analysing the dependencies between variables.
Copula modelling allows the investigation of tail dependencies, which is of particular interest …