Research on Dynamic Evolution of Systemic Risk in Chinese Banking System

Hong Fan,Wanqin Sheng

doi:10.3389/fphy.2020.00199

Abstract

Systemic risk is not only related to the contagious risk of interbank market risk exposure, but also to the credit risk exposure. At the same time, the dynamic characteristics of banking system also affect the systemic risk. A large number of studies have revealed the contagious risk of interbank market risk exposure, but the systematic risk research that considers these factors at the same time is still rare. Therefore, the present paper constructs dynamically evolving banking systemic risk assessment model under double risk exposures in the same framework that includes two parts: one is the assessment of credit risk; the other is the contagious risk. On the assessment of credit risk, we use Geometric Brownian Motion in physics and Monte Carlo simulation calculation method based on the big data of the stock market. On the assessment of contagious risk, we use the method of Geometric Brownian Motion in physics and minimum density method. Then we use data of 205 Banks and 3,017 listed companies in 18 industries in Chinese to study the dynamic evolution law of the Chinese banking systemic risk. The results show that the evolution characteristics of credit risk of 18 real industries can be divided into 4 types which are stability after decline, increase in fluctuation, decrease in fluctuation, and fluctuation. The systemic risk of Chinese banking system with the double risk exposures gradually increased with the evolution of time, and then stabilized at a certain degree. Among them, the initial increase of contagious risk is fast, and then stable; the credit risk starts small, slowly increases, and eventually stabilizes. The evolution degree of contagious risk is higher than that of credit risk. Large banks have the strongest ability to withstand the impact of double risk exposures, while foreign banks have the weakest.

Highlights

After the international financial crisis in 2008 and the European debt crisis in 2010, countries have paid enough attention to strengthening financial supervision, maintaining financial stability, and preventing and controlling systemic risks
In Equation (19), we use the method proposed by Fan et al [29] to estimate the asset sequence of bank i Vi(t) and liability sequence Di(t); the borrowing asset sequence Ai(t) and liability sequence Li(t) will be discussed in section The Dynamic Evolution of Interbank Market Network; Lossi(t) indicates the external asset loss of bank i caused by the impact of the credit risk exposure, which can be found in Equation (15)
Based on the double risk exposure, we use the data of assets, liabilities, and industry loans of 205 Chinese banks, as well as the data of 3017 listed companies’ stock market to study the dynamic evolution law of the systemic risk of Chinese banking system

Summary

INTRODUCTION

After the international financial crisis in 2008 and the European debt crisis in 2010, countries have paid enough attention to strengthening financial supervision, maintaining financial stability, and preventing and controlling systemic risks. After constructing the dynamic evolution of assets and liabilities, the present paper uses the simulation methods, complex network methods, and empirical data to build a dynamic evolution model of banking systemic risk assessment to analyze the impact of the direct shock of credit risk exposure of the real industry and the indirect shock of interbank market exposure on the systemic risk of China’s banking system. In Equation (19), we use the method proposed by Fan et al [29] to estimate the asset sequence of bank i Vi(t) and liability sequence Di(t); the borrowing asset sequence Ai(t) and liability sequence Li(t) will be discussed in section The Dynamic Evolution of Interbank Market Network; Lossi(t) indicates the external asset loss of bank i caused by the impact of the credit risk exposure, which can be found in Equation (15).

RESULTS

Bankrupt enterprise

DISCUSSION AND CONCLUSIONS