Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
476976 | European Journal of Operational Research | 2011 | 15 Pages |
We consider a credit risk model with two industrial sectors, where defaults of corporations would be influenced by two factors. The first factor represents the macro economic condition which would affect the default intensities of the two industrial sectors differently. The second factor reflects the influences of the past defaults of corporations against other active corporations, where such influences would affect the two industrial sectors differently. A two-layer Markov chain model is developed, where the macro economic condition is described as a birth–death process, while another Markov chain represents the stochastic characteristics of defaults with default intensities dependent on the state of the birth–death process and the number of defaults in two sectors. Although the state space of the two-layer Markov chain is huge, the fundamental absorbing process with a reasonable state space size could capture the first passage time structure of the two-layer Markov chain, thereby enabling one to evaluate the joint probability of the number of defaults in two sectors via the uniformization procedure of Keilson. This in turn enables one to value a variety of derivatives defined on the underlying credit portfolios. In this paper, we focus on a financial product called CDO, and a related option.
► We consider a credit risk model with two industrial sectors. ► Defaults are influenced by the macro economic condition and the past defaults. ► We propose Computational algorithms of CDO and CDO options. ► CDO and CDO options demand huge premium if the impact of contagion is large.