›› 2018, Vol. 30 ›› Issue (3): 15-28.

• 经济与金融管理 • 上一篇    下一篇

基于Fisher判别的小型工业企业债信评级模型及实证

潘明道, 周颖, 迟国泰, 孟斌   

  1. 大连理工大学管理与经济学部, 大连 116024
  • 收稿日期:2016-06-17 出版日期:2018-03-28 发布日期:2018-03-26
  • 通讯作者: 周颖(通讯作者),大连理工大学管理与经济学部副教授,硕士生导师,博士
  • 作者简介:潘明道,大连理工大学管理与经济学部,博士;迟国泰,大连理工大学管理与经济学部教授,博士生导师,博士;孟斌,大连理工大学管理与经济学部,博士
  • 基金资助:

    国家社科基金项目(16BTJ017);辽宁经济社会发展重点课题(2015lslktzdian-05);教育部科学技术研究项目(2011-10);中国银监会银行业信息科技风险管理项目(2012-4-005);中国邮政储蓄银行总行小额贷款信用风险评价与贷款定价资助项目(2009-07);大连银行小企业信用风险评级系统与贷款定价项目(2012-01)。

Small Industrial Enterprises' Credit Rating Model and Empirical Analysis Based on Fisher Discriminant

Pan Mingdao, Zhou Ying, Chi Guotai, Meng Bin   

  1. Faculty of Management and Economics, Dalian University of Technology, Dalian 116024
  • Received:2016-06-17 Online:2018-03-28 Published:2018-03-26

摘要:

本文以中国某商业银行1814个小型工业企业贷款客户数据为样本,根据指标对违约状态鉴别精度的影响程度进行第一次筛选,保证遴选出的指标对违约状态鉴别能力都有显著影响;根据准则内相关分析进行第二次筛选,避免遴选出的指标反映信息重复,构建了一套能显著区分小型工业企业违约状态的评级体系。本文的创新与特色:一是根据有、无特定指标两种状态下、Fisher判别对违约状态鉴别精度的提高或降低,反映特定指标对违约状态的影响程度,剔除对违约状态的判别精度没有影响或有降低影响的指标,保留可以显著提高违约状态判别精度的指标,完善了现有研究遴选指标的标准与违约状态无关的不足。二是在相关系数大于0.7的两个指标中,根据对Fisher判别精度影响程度越大、这个指标区分违约状态能力越强的思路剔除对Fisher判别精度影响程度较小的指标,避免了现有研究在剔除冗余指标时、对违约状态影响大的指标可能被误删的不足。

关键词: 工业企业, 小型企业, 债信评级, Fisher判别

Abstract:

According to the influence degree of indexes on the identification precision of default state, this study conducts the first screening to ensure that the selected indexes have a significant effect to the identification ability of default state. According to correlation analysis within guidelines, this study conducts the second screening to keep the selected indexes from reflecting the same information. This study builds a set of rating system which can significantly distinguish the default state of small industrial enterprises. This paper makes an innovative and characteristic attempt in two aspects. Firstly, according to the condition either with or without specific indicators, effects of using Fisher discriminant on identification accuracy of default state, it reflects the influence of specific indicators on the default state. Secondly, with regards to the two indicators with correlation coefficient above 0.7, this paper, based on the thought that the greater impact on the Fisher discriminant accuracy, the stronger ability of the index to distinguish default state, accurately removes the indexes that have smaller influence on Fisher discriminant.

Key words: industrial corporate, small corporate, credit rating, fisher discriminant