信用风险分析的生存混合模型

Leo S. F. Mo, Kelvin K. W. Yau
{"title":"信用风险分析的生存混合模型","authors":"Leo S. F. Mo, Kelvin K. W. Yau","doi":"10.2202/2153-3792.1061","DOIUrl":null,"url":null,"abstract":"The survival mixture model, which is an extension of the ordinary survival model that allows the existence of a fraction of the borrowers to be risk-free, is applied to credit risk analysis. In a regression setting, the effect of borrowers' characteristics on both the risk-free probability and default risk can be assessed simultaneously. Using the C statistic as a measure of accuracy, the survival mixture model shows improved power to discriminate between ‘good' and ‘bad' customers, when compared with other commonly used statistical models for credit risk analysis. A simulation study is conducted to assess the performance of the proposed numerical estimation method. The survival mixture model not only concentrates on the time-to-default of the borrowers, it also predicts the probability of being risk-free. It provides additional information about the borrowers' default risk in relation to their characteristics, which assists the lending institutions to better manage credit risk.","PeriodicalId":244368,"journal":{"name":"Asia-Pacific Journal of Risk and Insurance","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Survival Mixture Model for Credit Risk Analysis\",\"authors\":\"Leo S. F. Mo, Kelvin K. W. Yau\",\"doi\":\"10.2202/2153-3792.1061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The survival mixture model, which is an extension of the ordinary survival model that allows the existence of a fraction of the borrowers to be risk-free, is applied to credit risk analysis. In a regression setting, the effect of borrowers' characteristics on both the risk-free probability and default risk can be assessed simultaneously. Using the C statistic as a measure of accuracy, the survival mixture model shows improved power to discriminate between ‘good' and ‘bad' customers, when compared with other commonly used statistical models for credit risk analysis. A simulation study is conducted to assess the performance of the proposed numerical estimation method. The survival mixture model not only concentrates on the time-to-default of the borrowers, it also predicts the probability of being risk-free. It provides additional information about the borrowers' default risk in relation to their characteristics, which assists the lending institutions to better manage credit risk.\",\"PeriodicalId\":244368,\"journal\":{\"name\":\"Asia-Pacific Journal of Risk and Insurance\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asia-Pacific Journal of Risk and Insurance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2202/2153-3792.1061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asia-Pacific Journal of Risk and Insurance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2202/2153-3792.1061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

将混合生存模型应用于信用风险分析,该模型是对普通生存模型的扩展,允许部分借款人的存在是无风险的。在回归设置中,可以同时评估借款人特征对无风险概率和违约风险的影响。与其他常用的信用风险分析统计模型相比,使用C统计量作为准确性度量,生存混合模型显示出更好的区分“好”和“坏”客户的能力。通过仿真研究对所提出的数值估计方法的性能进行了评估。生存混合模型不仅关注借款人的违约时间,还预测无风险的概率。它根据借款人的特点提供了有关其违约风险的额外信息,这有助于贷款机构更好地管理信贷风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Survival Mixture Model for Credit Risk Analysis
The survival mixture model, which is an extension of the ordinary survival model that allows the existence of a fraction of the borrowers to be risk-free, is applied to credit risk analysis. In a regression setting, the effect of borrowers' characteristics on both the risk-free probability and default risk can be assessed simultaneously. Using the C statistic as a measure of accuracy, the survival mixture model shows improved power to discriminate between ‘good' and ‘bad' customers, when compared with other commonly used statistical models for credit risk analysis. A simulation study is conducted to assess the performance of the proposed numerical estimation method. The survival mixture model not only concentrates on the time-to-default of the borrowers, it also predicts the probability of being risk-free. It provides additional information about the borrowers' default risk in relation to their characteristics, which assists the lending institutions to better manage credit risk.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Estimating Risk Relativity of Driving Records using Generalized Additive Models: A Statistical Approach for Auto Insurance Rate Regulation Assessing the Impact of Climate Risk Stresses on Life Insurance Portfolios The Risk of Natural Catastrophe in Early America: Perspectives from the Phoenix Assurance Company London and Nascent US Insurers Frontmatter Special Issue: History of Insurance in a Global Perspective: A Novel Research Agenda
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1