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Credit Risk Contagion Based on Asymmetric Information Association


  • Shanshan Jiang
  • Hong Fan
  • Min Xia


The study of the contagion law of credit risk is very important for financial market supervision. The existing credit risk contagion models based on complex network theory assume that the information between individuals in the network is symmetrical and analyze the proportion of the individuals infected by the credit risk from a macro perspective. However, how individuals are infected from a microscopic perspective is not clear, besides the level of the infection of the individuals is characterized by only two states: completely infected or not infected, which is not realistic. In this paper, a credit risk contagion model based on asymmetric information association is proposed. The model can effectively describe the correlation among individuals with credit risk. The model can analyze how the risk individuals are infected in the network and can effectively reflect the risk contagion degree of the individual. This paper further analyzes the influence of network structure, information association, individual risk attitude, financial market supervision intensity, and individual risk resisting ability on individual risk contagion. The correctness of the model is verified by theoretical deduction and numerical simulation.

Suggested Citation

  • Shanshan Jiang & Hong Fan & Min Xia, 2018. "Credit Risk Contagion Based on Asymmetric Information Association," Complexity, Hindawi, vol. 2018, pages 1-11, July.
  • Handle: RePEc:hin:complx:2929157
    DOI: 10.1155/2018/2929157

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    References listed on IDEAS

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    Cited by:

    1. Xuzhen Zhu & Jinming Ma & Xin Su & Hui Tian & Wei Wang & Shimin Cai, 2019. "Information Spreading on Weighted Multiplex Social Network," Complexity, Hindawi, vol. 2019, pages 1-15, November.

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