The Study Of Credit Risk Of Commercial Banks On Credit Portfolio View Model

Healthy and stable development of national economy and prosperity depends on the stable operation of commercial Banks.The World Bankstudyglobal banking crisisfor many years.The study conclusion shows that the commercial bank bankruptcy of credit risk is the major cause of the bad management.Strengthen of the management and control of credit risk is the key to the healthy development of the commercial banks.Credit risk quantitative management is a very complicated systematic engineering.The different risk measurement technology and the measurement model formed on the basis of different credit risk management theory.Based on the Credit Portfolio View(CPV)model,I evaluate our country commercial bank loan default rates and predict commercial banks non-performing loan ratio.The paperuses the CPV method to study credit risk of commercial bank loan,selected commercial Banks non-performing loan ratio as evaluation of commercial bank credit risk indicators.From the results,total retail sales of social consumer goods,the M2 supply growth rate,net exports and the one-year deposit rate are important factor to influence the non-performing loans of commercial banks in China.In regression model,theregression coefficien of total retail sales of social consumer goods,the M2 supply growth rate,net exports is negative.This meansthemacroscopic variables have reverse influence for the composite indicator,so theyalso have reverse influence for the commercial banks.When social total retail sales of consumer goods,the M2 supply growth rate,net exports rise and fall,the commercial Banks non-performing loan ratio rises.One-year deposit rate regression coefficient is positive,indicating its effect on the comprehensive index is positive,which means that non-performing loans of commercial Banks is positive,the commercial bank non-performing loans will rise with the one-year deposit interest rates rise.The main innovation pointsof this article is the process of forecast analysis.To predict non-performing loan ratio,we have to predict macroeconomic variable which have a significant impact on non-performing loan ratio.This article has carried on the regression analysis to macroeconomic variable,which makes the prediction of macroeconomic economic variables more theoretical and persuasive.In the process of using logistic model to predict non-performing loan ratio,this paperanalyze the residual partmore cautious.Accroding to using cholesky method,this papermakes the residual vector Et+1 be randomly generated and correlation between residual vector.UsingEt+1 to predict the non-performing loan ratio,considering the random shocks,macroeconomic situation and the correlation between impact,the consequence will be more reasonable.In this paper,I predict the default rate for the next four period,prediction results show that with the increase of forecast periods,model prediction deviation is also increased.