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论文类型： 期刊论文

发表时间： 2022-06-29

发表刊物： 管理科学学报

所属单位： 经济管理学院

卷号： 21

期号： 3

页面范围： 105-126

ISSN号： 1007-9807

摘要： Credit rating is aimed at measuring the possibility of default,so credit rating system must be able to identify default risk,and separate default customers and non-default customers.This paper through thinking of non-default enterprises close to positive ideal point and default enterprises close to negative ideal point,multiobjective programming model is constructed to solve the optimal combination weights.Through the J-T nonparametric test,the rationality of the credit evaluation model is verified.And this paper does empirical analysis about 1 814 loan customers in a regional commercial bank of China.The innovations and characters in this paper:Firstly,minimizing the distance of non-default enterprises' weighted data to positive ideal point as the first objective function,minimizing the distance of default enterprises' weighted data to negative ideal point as the second objective function,multi-objective programming model is constructed to solve the optimal combination weights.The optimal combination weights satisfy the goal "the higher scores of non-default enterprises,the lower scores of default enterprises" and ensure that credit rating model maximizes the distance of non-default enterprises and default enterprises.It changes the disadvantage that combination weights is contrary to credit rating purpose in existing research,and changes the disadvantage that a lot of the score overlap between non-default and default enterprises and the ability of distinguish between non-default and default enterprises is low in existing research.Secondly,this paper use the J-T nonparametric test to verify the rationality of the credit evaluation model,aimed to ensure that the scores of non-default enterprises is higher significantly than the scores of default enterprises,avoids the irrational phenomenon in existing research that the scores of default enterprises is higher.Thirdly,Compared with traditional combination weighting models in existing research,the default identification ability of the combination weighting model in this research is higher than two kinds of combination weighting models in existing research,one is the combination weighting model based on maximum variance,the other is the combination weighting model based on minimum deviation.

备注： 新增回溯数据