【作者】 崔健；

【导师】 王庆石；

【作者基本信息】 东北财经大学 ， 数量经济学， 2016， 硕士

【摘要】 当今社会,银行成为一国金融体系的重要组成部分,在一个国家金融以及经济发展中起着核心作用,可以说如果一个国家银行业不能发挥应有的作用,该国的经济也就不会发达。银行业作为金融体系里的一个极为重要的部分能够极大地促进经济和社会的发展,同样,经济以及社会的发展也可以促进银行业的完善和发展。信用风险又称为违约风险,它不但自古以来就是金融市场所面临的核心风险,而且一直以来都是银行业风险管控的重中之重。历年来多次全球范围内的银行业危机表明,信用风险的管理和控制不善将会使得商业银行发生破产的悲剧。本文以Credit Portfolio View(CPV)模型为研究模型,来对我国商业银行贷款违约率进行评估,并在此基础上对商业银行不良贷款率进行预测。本文选用CPV方法对商业银行贷款的信用风险进行实证研究,选取商业银行不良贷款率作为评估商业银行信用风险的指标,从实证结果来看,社会消费品零售总额、货币供应量M2增长率、净出口、一年期存款利率是影响我国商业银行不良贷款率的重要因素。在回归模型中,社会消费品零售总额、货币供应量M2增长率、净出口的回归系数为负,说明它们对于综合指标的影响是反向的,也就意味着对商业银行的不良贷款率的影响也是反向的,即商业银行不良贷款率会随着社会消费品零售总额、货币供应量M2增长率、净出口上升而下降;一年期存款利率回归系数为正,说明它对于综合指标的影响是正向的,也就意味着对商业银行的不良贷款率的影响也是正向的,即商业银行不良贷款率会随着一年期存款利率上升而上升。本文的创新点主要是利用cholesky方法使得残差向量Et+1的各元素之间具有相关性关系,即在预测每个宏观经济变量时所用的残差之间具有相关性关系。当某个经济冲击发生时,如房地产泡沫破裂,必然会引起GDP增长速度、国房景气指数等经济指标的大幅波动,在宏观经济变量的自回归方程中,波动体现在残差向量各元素的数值变化上。因为房地产泡沫破裂对GDP增长速度和国房景气指数的影响是具有相关性的,即一定会引起两个经济指标有不同程度的下降,所以在预测GDP增长速度和国房景气指数所用的残差也应有相关关系,简单的随机生成残差不能反映这种相关关系。通过cholesky方法,给随机生成的残差向量赋予了相关性结构,以此为误差矩阵来预测贷款违约率更为合理。更多还原

【Abstract】 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.更多还原