经济数学
經濟數學
경제수학
MATHEMATICS IN ECONOMICS
2014年
4期
8-13
,共6页
债券评级%MDA%Logistic%Probit%神经网络%变量甄选
債券評級%MDA%Logistic%Probit%神經網絡%變量甄選
채권평급%MDA%Logistic%Probit%신경망락%변량견선
bond rating%MDA%Logistic%Probit%neural network%variable selection
在国内外债券评级的研究基础之上，选用 MDA、Logistic 模型、Probit模型以及神经网络四种债券评级方法，结合中国上市公司的风险特征，从变量甄选的角度对债券评级方法进行优化，同时采用中国上市公司数据进行实证分析.实证结论表明：甄选出的评级变量较国外常用的评级指标更好的刻画了中国上市公司的风险特征；Logistic 模型、Probit 模型和神经网络方法都对中国上市公司的债券有较高的评级分类能力，尤其是 Probit 模型和神经网络方法对中国公司债券的评级非常准确，误判率接近于0.
在國內外債券評級的研究基礎之上，選用 MDA、Logistic 模型、Probit模型以及神經網絡四種債券評級方法，結閤中國上市公司的風險特徵，從變量甄選的角度對債券評級方法進行優化，同時採用中國上市公司數據進行實證分析.實證結論錶明：甄選齣的評級變量較國外常用的評級指標更好的刻畫瞭中國上市公司的風險特徵；Logistic 模型、Probit 模型和神經網絡方法都對中國上市公司的債券有較高的評級分類能力，尤其是 Probit 模型和神經網絡方法對中國公司債券的評級非常準確，誤判率接近于0.
재국내외채권평급적연구기출지상，선용 MDA、Logistic 모형、Probit모형이급신경망락사충채권평급방법，결합중국상시공사적풍험특정，종변량견선적각도대채권평급방법진행우화，동시채용중국상시공사수거진행실증분석.실증결론표명：견선출적평급변량교국외상용적평급지표경호적각화료중국상시공사적풍험특정；Logistic 모형、Probit 모형화신경망락방법도대중국상시공사적채권유교고적평급분류능력，우기시 Probit 모형화신경망락방법대중국공사채권적평급비상준학，오판솔접근우0.
Based on the researches about bond rating at home and abroad,this paper chooses four types of methods in-cluding MDA,Logistic Model,Probit model and neural network,and according to the risk features of China list corporations, such methods were optimized by the angle of the variable selection,and the data of China list corporation was used to conduct an empirical analysis.The conclusions show that the rating variables selected can capture the risk features of China list corpora-tions better than the rating variables often chosen in the literatures abroad,and all of Logistic Model,Probit model and neural network have much more capability of rating classification to the bonds of China list corporations,especially the rating results of the Probit model and neural network method are very precise,and the error classification rates are almost 0.
