The aim of this article is to bring together different specifications for copula models with time-varying dependence structure. Copula models are widely used in financial econometrics and risk management. They are considered to be a competitive alternative to the Gaussian dependence structure....

The maximum likelihood estimator applied to the dynamic conditional correlation model is severely biased in high dimensions. This is, in particular, the case where the cross-section dimension is close to the sample size. It is argued that one of the reasons for the bias lies in an...

A new semiparametric dynamic copula model is proposed where the marginals are specified as parametric GARCH-type processes, and the dependence parameter of the copula is allowed to change over time in a nonparametric way. A straightforward two-stage estimation method is given by local maximum...

This paper proposes an original three-part sequential testing procedure (STP), with which to test for contagion using a multivariate model. First, it identifies structural breaks in the volatility of a given set of countries. Then a structural break test is applied to the correlation matrix to...

We propose a model that can capture the typical features of multivariate extreme events observed in financial time series, namely, clustering behaviors in magnitudes and arrival times of multivariate extreme events, and time-varying dependence. The model is developed within the framework of the...

Correlation mixtures of elliptical copulas arise when the correlation parameter is driven itself by a latent random process. For such copulas, both penultimate and asymptotic tail dependence are much larger than for ordinary elliptical copulas with the same unconditional correlation....

This paper proposes a new approach based on time-varying copulas to test for the presence of increases in stock market interdependence (also known as shift contagion) after a financial crisis. We discuss the importance of considering simultaneously separate breaks in volatility and dependence....

We propose a new model that can capture the typical features of multivariate extreme events observed in financial time series, namely clustering behavior in magnitudes and arrival times of multivariate extreme events, and time-varying dependence. The model is developed in the framework of the...