Publication Type

Master Thesis

Publication Date



Portfolio credit products, such as CDO and Single Tranche CDO (STCDO) have gained their popularity in financial industry. The key problem facing by the financial engineers is how to price these portfolio credit derivatives, especially how to model the dependent default structure. Copula model proposed by Li (2000) is widely used in practice. Comparing with simulation, factor copula model and conditional independent framework provide good balance between accuracy and computational efficiency, but it is hard to achieve good performance if sticking to normal distribution. There are a few ways to improve it: introducing Levy distributions, using generic copula functions, and the semi parametric estimation. In this paper the Levy distribution and conditional independent factor copula model are examined. The flexibility and accuracy improvement comes from calibrating the skewness and heavy tail of Levy distribution for the underlying marginal distributions. The simulation result and short period prediction result are discussed too. One of the other benefits of this model is that once calibrating to the standard market tranches spreads, the model can handle the customized CDO, e.g. Single Tranche CDO.


factor copula model, Levy process, portfolio credit derivatives

Degree Awarded

MSc in Finance


Finance and Financial Management | Portfolio and Security Analysis


LIM, Kian Guan

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.