中国公司债券评级方法应用研究
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引用本文:田渊博.中国公司债券评级方法应用研究[J].经济数学,2014,(4):8-13
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作者单位
田渊博 (东北财经大学 金融学院和应用金融研究中心辽宁 大连 116025) 
中文摘要: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.
中文关键词:债券评级  MDA  Logistic  Probit  神经网络  变量甄选
 
An Application Study on Bond Rating Method of China Corporation
Abstract:Based on the researches about bond rating at home and abroad, this paper chooses four types of methods including 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 corporations 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.
keywords:bond rating  MDA  Logistic  Probit  neural network  variable selection
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