In this paper we discuss some statistical pitfalls that may occur in modeling cross-dependences with copulas in financial applications. In particular we focus on issues arising in the estimation and the empirical choice of copulas as well as in the design of time-dependent copulas.

In this paper we present a model to price and hedge basket credit derivatives andcollateralised loan obligation. Based upon the copula-approach by Schönbucher and Schubert (2001) the model allows a specification of the joint dynamics of credit spreads and default intensities, including a...

In this paper we provide a convenient econometric framework for the analy-sis of nonlinear dependence in financial applications. We introduce models withconstrained nonparametric dependence, which specify the conditional distrib-ution or the copula in terms of a one-dimensional functional...

The aim of this paper is to extend the results of Jarrow, Yu (2001) onthe spread term structures of corporate bonds. We first consider differentcharacterisations of these term structures, when the available informationcorresponds to the default histories of the firms. The approach is then...

This project identi.es and quanti.es two potential sources of model riskin the valuation of basket credit derivatives. The frameworkemployed is that of a latent variable model with factor structure which enjoys a great popularity in the .nancial industry as well as in academia. Preliminary...

We consider a nonparametric method to estimate copulas, i.e. functions linking joint distributions to their univariate margins. We derive the asymptotic properties of kernel estimators of copulas and their derivatives in the context of a multivariate stationary process satisfactory strong mixing...

We develop a test of equality between two dependence structures estimated through empirical copulas. We provide inference for independent or paired samples. The multiplier central limit theorem is used for calculating p-values of the Cramér-von Mises test statistic. Finite sample properties are...