Analysis Of Inter-industry Credit Risk Contagion Based On Copula Function

With the continuous opening of economic globalization,various economic subjects are more and more closely connected.When a credit risk occurs in an economic entity,it often affects other economic entities associated with it,leading to defaults and even bankruptcy,which constitutes a credit risk contagion,so we need to strengthen the correlation of credit risk to achieve a better risk management.In this paper,the KMV model and Copula function are used to analyze the credit risk contagion between real estate industry and manufacturing industry.Firstly,the KMV model is modified by using stable distribution to fit return to estimate volatility and adding macroeconomic factors to default point,and the validity of the modified KMV model is tested.Then,by choosing the best Copula function to fit the default distance between the two industries,the infectivity of credit risk between the two industries based on the default distance is determined.The research results show that,statistically speaking,the default point of the real estate industry is negatively correlated with GDP,positively correlated with CPI,and has no significant effect on M2.For the manufacturing industry,the default point is negatively correlated with GDP and positively correlated with CPI and M2.At the same time,the modified KMV model is better for the recognition of default.By comparing the squared Euclidean distance,it is found that Gaussian Copula can best fit the default distance between the two industries,and there is a negative correlation between the default distance,which means that the credit risk of the real estate industry and the manufacturing industry is negatively correlated.When the credit risk of one industry increases,the credit risk of another industry will decrease accordingly.When a commercial bank chooses a credit portfolio,they can disperse the default risk and avoid the loss by taking the correlation of credit risk into account.