财务比率分数阶多项式变换的破产预测

IF 6 2区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Zenon Taoushianis
{"title":"财务比率分数阶多项式变换的破产预测","authors":"Zenon Taoushianis","doi":"10.1016/j.ejor.2025.07.036","DOIUrl":null,"url":null,"abstract":"We show that simple nonlinear transformations of financial ratios, within a multivariate fractional polynomial approach, yield substantial improvements in bankruptcy prediction. The approach selects optimal power functions balancing parsimony and complexity. Focusing on a dataset comprising of non-financial firms, we develop a parsimonious nonlinear logit model with minimal parameter specification and clear interpretability, outperforming linear logit models. The model improves the in-sample fit, while out-of-sample it significantly reduces costly misclassification errors and improves discriminatory power. Similar insights are obtained when applying fractional polynomials on a secondary dataset consisting of banking firms. Interestingly, the fractional polynomial model compares favourably with other nonlinear models. By simulating a competitive loan market, we demonstrate that the bank using the fractional polynomial model builds a higher-quality loan portfolio, resulting in superior risk-adjusted profitability compared to banks employing alternative models.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"14 1","pages":""},"PeriodicalIF":6.0000,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bankruptcy prediction with fractional polynomial transformation of financial ratios\",\"authors\":\"Zenon Taoushianis\",\"doi\":\"10.1016/j.ejor.2025.07.036\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We show that simple nonlinear transformations of financial ratios, within a multivariate fractional polynomial approach, yield substantial improvements in bankruptcy prediction. The approach selects optimal power functions balancing parsimony and complexity. Focusing on a dataset comprising of non-financial firms, we develop a parsimonious nonlinear logit model with minimal parameter specification and clear interpretability, outperforming linear logit models. The model improves the in-sample fit, while out-of-sample it significantly reduces costly misclassification errors and improves discriminatory power. Similar insights are obtained when applying fractional polynomials on a secondary dataset consisting of banking firms. Interestingly, the fractional polynomial model compares favourably with other nonlinear models. By simulating a competitive loan market, we demonstrate that the bank using the fractional polynomial model builds a higher-quality loan portfolio, resulting in superior risk-adjusted profitability compared to banks employing alternative models.\",\"PeriodicalId\":55161,\"journal\":{\"name\":\"European Journal of Operational Research\",\"volume\":\"14 1\",\"pages\":\"\"},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2025-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Operational Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1016/j.ejor.2025.07.036\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Operational Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1016/j.ejor.2025.07.036","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0

摘要

我们表明,在多元分数多项式方法中,财务比率的简单非线性变换在破产预测中产生了实质性的改进。该方法在简洁性和复杂性之间选择最优幂函数。专注于由非金融公司组成的数据集,我们开发了一个简约的非线性logit模型,具有最小的参数规范和清晰的可解释性,优于线性logit模型。该模型改善了样本内拟合,而样本外则显著降低了代价高昂的误分类误差,提高了判别能力。在由银行公司组成的二级数据集上应用分数多项式时,可以获得类似的见解。有趣的是,分数阶多项式模型与其他非线性模型相比具有优势。通过模拟竞争性贷款市场,我们证明了使用分数多项式模型的银行建立了更高质量的贷款组合,与使用替代模型的银行相比,产生了更高的风险调整盈利能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bankruptcy prediction with fractional polynomial transformation of financial ratios
We show that simple nonlinear transformations of financial ratios, within a multivariate fractional polynomial approach, yield substantial improvements in bankruptcy prediction. The approach selects optimal power functions balancing parsimony and complexity. Focusing on a dataset comprising of non-financial firms, we develop a parsimonious nonlinear logit model with minimal parameter specification and clear interpretability, outperforming linear logit models. The model improves the in-sample fit, while out-of-sample it significantly reduces costly misclassification errors and improves discriminatory power. Similar insights are obtained when applying fractional polynomials on a secondary dataset consisting of banking firms. Interestingly, the fractional polynomial model compares favourably with other nonlinear models. By simulating a competitive loan market, we demonstrate that the bank using the fractional polynomial model builds a higher-quality loan portfolio, resulting in superior risk-adjusted profitability compared to banks employing alternative models.
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
European Journal of Operational Research
European Journal of Operational Research 管理科学-运筹学与管理科学
CiteScore
11.90
自引率
9.40%
发文量
786
审稿时长
8.2 months
期刊介绍: The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making.
×
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:604180095
Book学术官方微信