Integrated Risk Measurement Of Chinese Listed Commercial Bank Based On Copula Function

The risk is everywhere. The Asian financial crisis in 1997 and the global financial crisis caused by the U.S. subprime mortgage crisis in 2007 led to the result that the entire financial system suffered a huge blow and loss. Enormous changes has taken place in the pattern of the financial system, some financial institutions in risk stand down or even grow up, some of the world’s financial institutions are crashing down. In the face of the financial crisis, we can interpret and analyze from different angles, but the source of the study is the loss or control in risk management.With the deepening of economic globalization and financial liberalization, our financial industry has entered a business model of internationalization and generalization, accompanied by the complexity and diversification of risk. Commercial banks which are the dominant in the financial system, obtain not only opportunity and profit from the innovation of financial derivatives, but also challenges and risks. The risk management of commercial banks is a huge and complicated system engineering. Basel Ⅱ clearly points out:the risk management of commercial banks from the pure credit risk management mode to the credit risk, market risk, operational risk and comprehensive risk management model. The overall risk management is the demand, even more is the core of management. With the increase of risk, how to understand and measure the risk of commercial banks correctly is particularly important. The integrated of risk measurement and control has become an important content of commercial banks management.This paper gives a detailed description of the three major risks faced by commercial banks:the basic meaning, characteristics and measurement methods of credit risk, market risk and operational risk. Then This paper uses the copula function to reflect the relationship between the risk of commercial banks. The Copula function is an effective method for measuring the integrated risk. It can separate the edge distribution and risk of different risk from the study of the dependence structure, and the choice of marginal distribution is not limited. This paper takes the 12 domestic commercial banks of China as the research sample, and adopts marginal factor method to integrate three risks of commercial banks. First of all, select SSE T-bond index return rate and SSE corporate bond index return rate as the influencing factors of credit risk, and get credit risk rate of return on value estimation by the method of risk factors of the OLS regression then determine the credit risk of marginal distribution model; Secondly, select of SSE T-bond index return rate, the RMB against the U.S. dollar closing price earnings ratio, Shanghai and Shenzhen 300 index returns rate as the factors influencing the market risk, and get the market risk return rate by the method of risk factors of the OLS regression, then estimate and determine the market risk of marginal distribution model; Thirdly, use Monte Carlo method to simulate the operation risk margin sequence based on the theory of extreme valueand determine the marginal distribution model of operational risk. After obtainning the Risk of marginal distribution model,use C vine copula function and D vine copula function to establish the model of integrated risk, then use R software to estimate the optimal copula function type and parameter values. According to the principle of AIC, C vine copula function compared with D vine copula function, which is chosen as the measurement model of commercial bank integrated risk. Finally, calculate the VaR by Monte Carlo, and compare with VaR by the traditional linear summation method. VaR value by copula model is more consistent and copula model integrated risk of commercial bank fits better.The paper make some new attempts in the previous research results:first of all, quantificat operational risk by Monte Carlo simulation method, integrating into our country commercial bank risk measurement and management. Secondly, in the integrated risk measurement, the paper uses the vine copula function to make model, and compares the results of C vine copula and D vine copula, and draws the optimal vine structure. This method is more flexible and reliable than the simple high-dimensional copula function.