Using Dynamic Copula Method for CDO Pricing

This paper extends the copula method in CDO pricing to dynamic copula model. As one can see, financial data often cover a long time period and dependent structure between different time series always tends to change instead of to keep static. So using dynamic copula model to price CDO is much more accurate than traditional static one. In our work, we apply GOF test and binary segmentation procedure to detect the change of copula function. The result shows that in different time period, the best copula fitting for data set is not static, thus the expected loss and fair spread varies from one stage to another one. Our empirical research shows that fair spread of each tranches varying from different stages. This explains why CDO is so popular and profitable in the past year, but its investors suffered so much when financial crisis happened.