Title :
On Infectious Models for Dependent Default Risk
Author :
Gu, Jiawen ; Ching, Wai-Ki ; Siu, Tak-Kuen
Author_Institution :
Dept. of Math., Univ. of Hong Kong, Hong Kong, China
Abstract :
Modeling dependent defaults is a key issue in risk measurement and management. In this paper, we introduce a Markovian infectious model to describe the dependent relationship of default processes of credit entities. The key idea of the proposed model is based on the concept of common shocks adopted in the insurance industry. We compare the proposed model to both one-sector and two-sector models considered in the credit literature using real default data. A log-likelihood ratio test is applied to compare the goodness-of-fit of the proposed model. Our empirical results reveal that the proposed model outperforms both the one-sector and two-sector models.
Keywords :
insurance; risk management; dependent default risk; infectious models; insurance industry; log likelihood ratio test; risk management; risk measurement; Biological system modeling; Computational modeling; Correlation; Data models; Hidden Markov models; Joints; Media; Markov chains; chain reaction of infectious defaults; common shock; default risk; one-sector model; two-sector model;
Conference_Titel :
Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
Conference_Location :
Yunnan
Print_ISBN :
978-1-4244-9712-6
Electronic_ISBN :
978-0-7695-4335-2
DOI :
10.1109/CSO.2011.185