
 The Importance of Simultaneous Jumps in Default Correlation (Job Market Paper) by Pouyan Mashayekh Ahangarani of the University of Southern California January 2007 Abstract: Correlated defaults have been an important area of research in credit risk analysis with the advent of basket of credit derivatives. Even the simple credit derivatives should be considered as a basket of two default risks since we should consider the bankruptcy risk of the derivative issuer as well. Considering jumps in the asset value helps to model the surprise risk of default in a group of firms. Simultaneous jumps in the asset values of companies can explain the default correlation. The multivariate jump diffusion model is used for modeling the asset value in the structural approach to credit risk modeling. GMM implemented on the moments generated by empirical characteristic function is the method used for estimation of the parameters. The principal component method is used for reducing the hassle of moment conditions in the characteristic function estimation of the model. At the end, the empirical result of joint default credit risk of a basket of two firms, Ford and General Motors are shown with using two models: one without jump and the other one with considering the simultaneous jump. Model selection criterion proves that the model with jump is a better model. The model without simultaneous jump underestimates the joint default probability of two firms. Keywords: Credit Risk, Correlation, GMM. Previously titled: Default Correlation with Considering Jumps (job market paper) Books Referenced in this paper: (what is this?) 