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Credit Risk Contagion Based on Asymmetric Information Association

机译:基于不对称信息关联的信用风险传染

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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.
机译:研究信用风险的传染规律对金融市场监管非常重要。现有基于复杂网络理论的信用风险传染模型假设网络中个人之间的信息是对称的,并从宏观角度分析了受信用风险感染的个人比例。但是,从微观角度看个体如何感染尚不清楚,除了个体的感染水平以仅完全感染或未感染的两种状态为特征之外,这是不现实的。提出了一种基于信息不对称关联的信用风险传染模型。该模型可以有效描述信用风险个体之间的相关性。该模型可以分析风险个体在网络中的感染情况,并可以有效反映个体的风险传染程度。本文进一步分析了网络结构,信息关联,个人风险态度,金融市场监管强度和个人风险承受能力对个人风险传染的影响。通过理论推导和数值模拟验证了模型的正确性。

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