The current US-subprime mortgage crisis highlights that during economic downturns, likelihood and severity of multiple borrowers may deteriorate jointly. This is a particular concern in today’s credit markets where via mechanisms such as collateralized debt obligations, credit portfolios rather than single name credits are exposed to losses within contractual boundaries. According to a recent study by the British Bankers’ Association (2006), 54 percent of the global $20 trillion credit derivatives market consists of portfolio products. The evaluation of these requires the understanding of individual risk drivers as well as their dependence structure. Simplifying assumptions in existing models often lead to an underestimation of risks, particularly during economic downturns.

For instance, credit portfolio models aggregate parameters for the likelihood, severity and dependence structure underlying a credit portfolio and forecast the distribution of future credit losses. It is common practice to model these parameters independently and to introduce the dependence structure thereafter. Different contributions try to incorporate the dependence structure between the default events (compare e.g., Lucas 1995, Dietsch & Petey 2004, Hamerle et al. 2006, Frey & McNeil 2002, 2003, Rösch & Scheule 2004, Rösch 2005, McNeil & Wendin 2007) and between the default events and related recoveries (compare e.g., Frye 2000, Pykhtin 2003, Tasche 2004, Düllmann & Trapp 2005, Rösch & Scheule 2005).