How Accurately Can Z-score Predict Bank Failure?

Q1 Economics, Econometrics and Finance
Laura Chiaramonte, (Frank) Hong Liu, Federica Poli, Mingming Zhou
{"title":"How Accurately Can Z-score Predict Bank Failure?","authors":"Laura Chiaramonte,&nbsp;(Frank) Hong Liu,&nbsp;Federica Poli,&nbsp;Mingming Zhou","doi":"10.1111/fmii.12077","DOIUrl":null,"url":null,"abstract":"<p>Bank risk is not directly observable, so empirical research relies on indirect measures. We evaluate how well Z-score, the widely used accounting-based measure of bank distance to default, can predict bank failure. Using the U.S. commercial banks’ data from 2004 to 2012, we find that on average, Z-score can predict 76% of bank failure, and additional set of other bank- and macro-level variables do not increase this predictability level. We also find that the prediction power of Z-score to predict bank default remains stable within the three-year forward window.</p>","PeriodicalId":39670,"journal":{"name":"Financial Markets, Institutions and Instruments","volume":"25 5","pages":"333-360"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/fmii.12077","citationCount":"54","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Financial Markets, Institutions and Instruments","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/fmii.12077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 54

Abstract

Bank risk is not directly observable, so empirical research relies on indirect measures. We evaluate how well Z-score, the widely used accounting-based measure of bank distance to default, can predict bank failure. Using the U.S. commercial banks’ data from 2004 to 2012, we find that on average, Z-score can predict 76% of bank failure, and additional set of other bank- and macro-level variables do not increase this predictability level. We also find that the prediction power of Z-score to predict bank default remains stable within the three-year forward window.

z分数预测银行倒闭有多准确?
银行风险不可直接观察,因此实证研究依赖于间接测度。我们评估了Z-score(广泛使用的基于会计的银行违约距离衡量标准)在预测银行倒闭方面的效果。利用2004年至2012年美国商业银行的数据,我们发现Z-score平均可以预测76%的银行倒闭,而其他银行和宏观层面的变量并没有增加这种可预测性。我们还发现,Z-score对银行违约的预测能力在未来三年的窗口内保持稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Financial Markets, Institutions and Instruments
Financial Markets, Institutions and Instruments Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
1.80
自引率
0.00%
发文量
17
期刊介绍: Financial Markets, Institutions and Instruments bridges the gap between the academic and professional finance communities. With contributions from leading academics, as well as practitioners from organizations such as the SEC and the Federal Reserve, the journal is equally relevant to both groups. Each issue is devoted to a single topic, which is examined in depth, and a special fifth issue is published annually highlighting the most significant developments in money and banking, derivative securities, corporate finance, and fixed-income securities.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信