The Credit Risk Metrics Study And Empirical Analysis Of The Commercial Bank In China Based On The Amended KMV Model

The current credit risk analysis of the commercial bank in China is performed from two aspects of vertical and horizontal. Firstly, to analyze the current credit risk of the commercial bank in China vertically according to the related data in 2009-2014 of 17 banks, after data orgnation to draw diagram with Excel or Spss 19.0, as can be seen from the diagrams, the current credit risk of the commercial bank in China as follows: non-performing loan ratio was down first and then up and provision coverage was up first and then down in 2009-2014; the concentration ration of loan customer decreased by years in 2009-2014, but concentration ration of industry was still relatively high; capital adequacy ratio and core capital adequacy ratio were all meet regulatory requirements, but some volatility is difficult to support long-term. Secondly, to study competitiveness of the commercial banks in China horizontally, to select 16 data indicators reflecting the bank competieiveness and process the data with factor analysis, it can be found form the analysis that the Industrial and Commercial Bank of China, the China Construction Bank, the Bank of China, the Agricultural Bank of China ranked top, and the Bank of Communications ranked relatively rearward as one of the state-owned commercial bank.The Bank of Communications ranked relatively rearward in the aspects of profitability and asset quality indicators, thus it should enhance its competitiveness respectively. Similarly, each bank may find its own advantages and disadvantages according to its common factors ranking to improve their own competitiveness. Finally, according to the results of vertical and horizontal analysis, to make suggestions for the credit risk management strategy of the commercial banks in China in order to assess and regulate credit risk effectively.For the aspect of credit risk metrics study under amended KMV model, firstly, to introduce the main credit risk metrics model simply; secondly, to analyze the basic principles and assumptions of KMV model to find the advantages and disadvantages of the model and then to amend the model; thirdly, to amend the KMV model in calculating the equity market value and the equity market value volatility, to determine the default point with t test; finally, to select 14 listed companies special treated and respective 14 non-listed companies special treated and 28 listed companies in the Shanghai and Shenzhen main board stock market, and to empirically analyze their related data in annual report of 2012-2014 and closing price of stock each day of January 1, 2012- December 31, 2014. The results of empirical analysis are as follows:(1) The amended KMV model has better recognition effect for the credit risk condition of listed company special treated and non-listed company special treated in China.(2) By calculating the default distance and probability of the 28 listed companies, it can be found that the longer the default distance, the lower the default probability, and the risk that the company default is lower. The average default distance and probability of the 28 listed companies have some volatility form 2012 to 2014.(3) To utilize the Matlab to calculate the different default distance and probability by selecting 17 different a values, and to utilize the t test-mean paired two sample analysis to determine that the best default point value of the company is 0.65.