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中国管理科学

中国管理科学 ›› 2009, Vol. 17 ›› Issue (5): 1-8.

• 论文 •    下一篇

非极端回收不良贷款的回收率预测研究

陈暮紫1,2, 马宇超2, 王博2, 陈浩2, 唐跃2, 陈敏2, 杨晓光2   

  1. 1. 中国科学技术大学统计与金融系, 安徽合肥 230026;
    2. 中国科学院数学与系统科学研究院, 北京 100080
  • 收稿日期:2008-12-22 修回日期:2009-04-20 出版日期:2009-10-31 发布日期:2009-10-31
  • 作者简介:陈暮紫(1983- ),女(汉族),广西南宁人,中国科学技术大学管理学院统计与金融系,博士研究生,研究方向:金融工程.
  • 基金资助:

    国家973计划(No.2007CB814902);国家自然科学基金资助项目(70425004)

Forecasting Models for Non-performing Loans of Non-extreme Recovery

CHEN Mu-zi1,2, MA Yu-chao2, WANG Bo2, CHEN Hao2, TANG Yue2, CHEN Min2, YANG Xiao-guang2   

  1. 1. Department of Statistic and Finance, University of Science and Technology of China, Hefei 230026, China;
    2. Academy of Mathematics and Systems Science, CAS, Beijing 100080, China
  • Received:2008-12-22 Revised:2009-04-20 Online:2009-10-31 Published:2009-10-31

PDF (PC)

1309

被引次数

14

摘要： 本文依托Loss Metric数据库,对非极端回收不良贷款的回收率预测模型进行了研究。文章通过对非极端回收不良贷款的回收率进行Beta-正态变换和Logit变换,结合影响不良贷款回收率的众多因素,进行了从简单到复杂、从单笔贷款债务人到多笔贷款债务人的逐级建模,并剖析了影响回收率的各个因素。实证结果表明,单笔贷款债务人的回收率模型可作为多笔贷款债务人回收率预测的基准;从单笔贷款债务人模型中可以更直观的分析各个不同的变量对回收率的影响。

关键词: 非极端回收, 不良贷款, 回收率, 单笔贷款债务人, 多笔贷款债务人

Abstract: Using the data from Lossmetric,this paper tries to build forecasting models for non-performing loans of non-extreme recovery. The paper first uses beta-normal transformation and logit transformation to process recovery rates,and gives an individual analysis for each impacting factor on recovery rate. Then the paper proceeds a model-establishing process from simple model to complex model,from single debt obligor's model to multi-debt obligor's model,aiming at a comprehensive investigation on the impacting factors. Empirical results show that both the single debt obligor's model and the multi-debt obligor's model have good predicting power,moreover the single debt obligor's model itself can reflect the relationship between the recovery rate and the impacting factors,and it can be used as the foundation of multi-debt obligor's model.

Key words: non-extreme recovery, non-performing loan, recovery rate, single debtobligor, multi-debt obligor

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