证据权重方法与信用风险控制

doi:10.6040/j.issn.1671-9352.0.2014.269

山东大学学报（理学版） ›› 2014, Vol. 49 ›› Issue (12): 55-59.doi: 10.6040/j.issn.1671-9352.0.2014.269

证据权重方法与信用风险控制

甘信军¹, 杨维强²

1. 山东大学数学学院, 山东济南 250100;
2. 山东大学金融研究院, 山东济南 250100

收稿日期:2014-06-11 修回日期:2014-11-07 出版日期:2014-12-20 发布日期:2014-12-20
通讯作者: 杨维强(1976- ),男,博士,讲师，研究方向为金融数学等. E-mail:ywq@sdu.edu.cn E-mail:ywq@sdu.edu.cn
作者简介:甘信军(1986- ),男,博士研究生，研究方向为金融统计、生物统计. E-mail:xjgansdu@163.com
基金资助:
山东省科技发展计划项目(2011YD01105)

Weight of evidence method and credit risk control

GAN Xin-jun¹, YANG Wei-qiang²

1. School of Mathematics, Shandong University, Jinan 250100, Shandong, China;
2. Institute for Financial Studies, Shandong University, Jinan 250100, Shandong, China

Received:2014-06-11 Revised:2014-11-07 Online:2014-12-20 Published:2014-12-20

摘要/Abstract

摘要： 研究了证据权重方法在商业银行信用风险分析中的应用,给出了完整的证据权重逻辑回归算法,并且成功地将此算法应用到商业银行真实的企业财务数据,建立了信用风险评级模型,使得商业银行对于企业违约概率的定量刻画更加精准。此外通过与经典方法的比较,验证了该方法的可行性与效率。

关键词: 变量选择, 违约概率, 证据权重方法, 逻辑回归

Abstract: The weight of evidence (WOE) method was adopted on the credit risk control in commercial bank and a full description of the algorithm was proposed. By employing this WOE approach on the real financial data of commercial bank, the risk control model was constructed such that the probability of default can be estimated more precisely. The significant advantages of WOE method over conventional methods were verified, especially in statistical power.

Key words: variable selection, probability of default, logistic regression, weight of evidence

中图分类号:

O212.5

甘信军, 杨维强. 证据权重方法与信用风险控制[J]. 山东大学学报（理学版）, 2014, 49(12): 55-59.

GAN Xin-jun, YANG Wei-qiang. Weight of evidence method and credit risk control[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(12): 55-59.

参考文献

[1] HASTIE T, TIBSHIRARI R, FRIEDMAN J. The Elements of statistical learning[M]. 2nd ed. Berlin: Springer, 2008:119-127; 389-415; 417-455.
[2] SIDDIQI N. Credit risk scorecards[M]. John Wiley & Sons, 2006: 73-127.
[3] 张尧庭, 方开泰. 多元统计分析[M]. 北京：科学出版社, 1999: 254-328. ZHANG Yaoting, FANG Kaitai. Multivariate statistical analysis[M]. Beijing: Scientific Press Ltd, 1999: 254-328.
[4] HÄRDLE W, MVLLER M, SPERLICH S, et al. Nonparametric and semiparametric models[M]. Berlin: Springer, 2004: 145-165.
[5] GOOD I J. Weight of evidence: a brief survey[J]. Bayesian Statistics. North-Holland, Amsterdam 1983, 2:249-269.
[6] GREIFF W. Maximum entropy, weight of evidence and information retrieval[D]. University of Massachusetts Amherst, 1999.
[7] 茆诗松. 统计手册[M].北京：科学出版社, 2006. MAO Shisong. Statistical handbook[M]. Beijing: Scientic Press Ltd, 2006.

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证据权重方法与信用风险控制

Weight of evidence method and credit risk control

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