• DocumentCode
    2348281
  • 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
  • fYear
    2011
  • fDate
    15-19 April 2011
  • Firstpage
    1196
  • Lastpage
    1200
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • 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
  • Type

    conf

  • DOI
    10.1109/CSO.2011.185
  • Filename
    5957868