Article ID: | iaor20105656 |
Volume: | 2010 |
Issue: | 1 |
Start Page Number: | 1 |
End Page Number: | 10 |
Publication Date: | May 2010 |
Journal: | Advances in Decision Sciences |
Authors: | Schellhorn Henry, Cossin Didier, Song Nan, Tungsong Satjaporn |
Keywords: | credit risk |
One of the key questions in credit dependence modelling is the specfication of the copula function linking the marginals of default variables. Copulae functions are important because they allow to decouple statistical inference into two parts: inference of the marginals and inference of the dependence. This is particularly important in the area of credit risk where information on dependence is scant. Whereas the techniques to estimate the parameters of the copula function seem to be fairly well established, the choice of the copula function is still an open problem. We find out by simulation that the t-copula naturally arises from a structural model of credit risk, proposed by Cossin and Schellhorn (2007). If revenues are linked by a Gaussian copula, we demonstrate that the t-copula provides a better fit to simulations than does a Gaussian copula. This is done under various specfications of the marginals and various configurations of the network. Beyond its quantitative importance, this result is qualitatively intriguing. Student's t-copulae induce fatter (joint) tails than Gaussian copulae