Research On The Systemic Risk Of Commercial Banks And Its Influencing Factors

Under the background of economic globalization, the financial crisis should not be underestimated as it probably bring bad consequences from one region to another, from one industry to another and from managers to workers. Therefore systemic risk management is particularly important in the financial industry, where the banks is the core of the entire financial market sector and the banking systemic risk is the key to the whole body. "One change makes all change".Based on the definition of systemic risk on the bank, through the relevant measure theory of systemic risk, the systemic risk level of China’s listed commercial banks can be calculated and analyzed by using more mature measurement methods, namely CoVaR. The results of this research part are:Systemic risk of China’s commercial banks gradually increasing over time; Systemic risk levels of different types of banks are also different in cross section; The level of systemic risk in the banking closely linked with the development trend of the overall bank at the same time and systemic risk increases sharply mostly along with the tightening of the liquidity level, the improvement of non-performing loan ratio and other problems.Then, on the basis of screening and analysis of relevant indicators and threshold panel data regression, it can be explored what effects will be brought by different indicator variables on bank systemic risk after constructing the index system of the corresponding affecting stability by controlling variables and delaying the first order robustness test. The results of this research part are:1) Macroeconomic variables and economic variables on industry showed significant negative correlation with systemic risk and the impacts on smaller banks are more obvious; 2) From the bank variables, price-earnings ratios, the ratios of loans to the ten largest customers, bad rates, cost income ratios and loan-deposit ratios, returns on equity (ROE) of systemic risk are positively correlated while the GDP growth rates, the banking climate index, the ratios of liquid assets, assets, net interest margin rates of return (NIMP) on systemic risk are negatively correlated; 3) The assets and cost income ratios have different effects on different scale banks’ systemic risk; 4) In the first-order lag conditions, the effects are still significant except for liquid assets ratios indicators.Finally, based on the above, the policy recommendations can be put forward as the characteristics of the bank systemic risk:Make further improvements the regulatory framework, and refine regulatory content; Judge the different levels of risk indicators for the impact of domestic banks from the rational view; Implement the mechanism of linkage supervision, strengthen cooperation and contact between the various regulatory authorities.Innovation of this paper lies in:The systemic risk level of each bank is explored based on the CoVaR model and through quantile regression; The high dimension problem is solved by the adaptive lasso regression by which affect variables can be selected from a number of relevant variables; Considering the possible nonlinear relationship between variables and systemic risk, the research can be studied through the classification of the panel threshold regression model.