Modeling Dependent Risk Factors with CreditRisk

16 Pages Posted: 31 Aug 2018

See all articles by Xiaohang Zhang

Xiaohang Zhang

Beijing University of Posts and Telecommunications (BUPT)

SuBang Choe

Independent

Ji Zhu

University of Michigan at Ann Arbor

Jill Bewick

Independent

Date Written: June 21, 2018

Abstract

The CreditRisk model has been widely used for calculating the loss distribution of a credit portfolio. However, its basic assumption of independent risk factors is not consistent with reality. Although the dependent structure can be mimicked by setting factor weights, a reasonable way to introduce correlated risk factors is needed. In this paper, an extension of the CreditRisk model, called the mixed vector model, is proposed. This model incorporates some common background factors with positive and negative correlations, so it can accommodate the complicated dependence structure of risk factors. The mixed vector model can rebuild the negative correlations better than other extended CreditRisk models. Moreover, it can be translated into the original CreditRisk framework with conditionally independent risk factors, so the numerical algorithm for calculating the loss distribution for the CreditRisk model can be reused with little modification.

Keywords: credit portfolio risk, CreditRisk model, dependent structure, risk factors, mixed vector model.

Suggested Citation

Zhang, Xiaohang and Choe, SuBang and Zhu, Ji and Bewick, Jill, Modeling Dependent Risk Factors with CreditRisk (June 21, 2018). Journal of Credit Risk, Vol. 14, No. 2, 2018. Available at SSRN: https://ssrn.com/abstract=3200341

Xiaohang Zhang (Contact Author)

Beijing University of Posts and Telecommunications (BUPT) ( email )

No 10, Xitucheng Road
Haidian District
Beijing, 100876
China

SuBang Choe

Independent

No Address Available

Ji Zhu

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Jill Bewick

Independent

No Address Available

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