Research on the Network Linkage Effects of Systemic Credit Risk’s Infection

By using credit asset network model, we describe the price linkage mechanism of infection caused by a network of credit assets, and for more representative of Baosteel supply chain, estimate the distribution's parameters of the asymmetric generalized heteroscedasticity model. And then we choose multivariate distribution function, to fit correlation coefficients, make use of multiple connections function of the dynamic conditional autocorrelation to calculate four correlation coefficients for C-vine structure decomposition dynamically, describe and analyze the time variation characteristics. Research shows that, there are strong network transmission linkage effects on the stock price of enterprises that have associated credit assets. The static and dynamic correlation measurement method based on the connection function of a multivariate distribution can be used to measure the network transmission linkage effect, both unconditional and conditional correlation coefficients are showing varying degrees of significant time-varying.