Empirical Research on Risk Overflow Effect of P2P Lending on Commercial Bank in China

Abstract

At first, an analysis is made on the risk overflow effect of network loan platform on traditional commercial banks in China. On this basis, the marginal distribution of the predictor of the GARCH-GPD model is established based on the financial time sequence characteristics of the comprehensive interest rate uncertainty of the network loan platform, so as to solve the overall coefficient of association and the tail coefficient of association between the comprehensive interest rate of network loan platform and the share index through the Archimedes Copula function. According to the research result, the risk overflow effect of network loan platform on traditional commercial banks is mainly reflected in direct and indirect aspects. Different from the traditional banking market, favorable news has greater effects on the network loan market behaviors. The information implication is even higher in the network loan platform. Besides, it takes a longer time for the market to digest the information. Compared with other financial institutions, it is easier for the risk of network loan platform to overflow toward traditional commercial banks. Moreover, the comprehensive interest rate uncertainty of network loan platform is positively related to the variation of commercial bank index. Violent decrease in the comprehensive interest rate of network loan platform caused by extreme events caused stronger related response to the benefits of the market index and the bank index. Its effects far exceed the action of simultaneous rise in relevant market indexes.