The Empirical Research Of Relationship Between The Banking Industrial Risk And Monetary Policies In China

This paper studies the risk level of banking industry in China, on the background of the worldwide financial crisis and economic depression in 2008 due to subprime lending collapse. The goal of this research is to clarify the mechanism of monetary policies exerting influence on banking industries, and then to get an accurate equation for the central bank’s reference, which also provides useful instruments for regulatory commission and management within to control operational risk suffered.Considering the development and operating process of China’s monetary policies system and getting materials from similar researching area home and broad, much attention is payed to banks’ operating risk exposing mode related to the monetary policies, as well as the detailed consequences. Then the empirical study is conducted based on the theoretical inference, which verifies the important role of the banking industry in transmission of central bank’s monetary policies, according to the updated figure from 2006 to 2015, when state-owned and state-controlled commercial banks have already completed the equity reforms.In order that the fitting equation could be adopted in policy making and meet the precision standard, the elimination of conflicts to the hypothesis in the Classic Linear Regression models is essential, such as the heteroscedasticity and auto correlation of residuals. Although the new regression model is more trustworthy from a statistical standpoint, the implication behind the equation is not quite reasonable according to the financial market. In the end, the adoption of GARCH model describes the residual item into conditional variance and get good results.Based on the mean function and variance equation, along with the financial theory analysis, it is concluded that the banks’ industrial level risk will go up when the benchmark interest rate falls down, but banks’ risk management department would take severe steps to prevent likely negative losses in the future if the quantitative easing polices continues. The banks potential risk exposure will be higher as the central bank use the expectation management policies more frequently, as a result, the government decision making process has to balance the economic growth and the financial market stability.This paper has brought new ideas in both theoretical analysis and empirical study, which are quantization of the whole monetary system and the adding of expectation management policy, the central bank’s new monetary instrument. The final relation model is quite accurate and practical for forecasting benefiting from econometrics method.