用于金融风险管理的可解释机器学习:两个实际应用案例

IF 1.2 4区 数学 Q2 STATISTICS & PROBABILITY Statistics Pub Date : 2024-09-13 DOI:10.1080/02331888.2024.2401078
Angelo Famà, Jurgena Myftiu, Paolo Pagnottoni, Alessandro Spelta
{"title":"用于金融风险管理的可解释机器学习:两个实际应用案例","authors":"Angelo Famà, Jurgena Myftiu, Paolo Pagnottoni, Alessandro Spelta","doi":"10.1080/02331888.2024.2401078","DOIUrl":null,"url":null,"abstract":"We explore the potential of machine learning (ML) models applied in two financial risk management areas, i.e., credit risk management and financial risk hedging, through two practical use cases. Th...","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"186 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Explainable machine learning for financial risk management: two practical use cases\",\"authors\":\"Angelo Famà, Jurgena Myftiu, Paolo Pagnottoni, Alessandro Spelta\",\"doi\":\"10.1080/02331888.2024.2401078\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We explore the potential of machine learning (ML) models applied in two financial risk management areas, i.e., credit risk management and financial risk hedging, through two practical use cases. Th...\",\"PeriodicalId\":54358,\"journal\":{\"name\":\"Statistics\",\"volume\":\"186 1\",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/02331888.2024.2401078\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/02331888.2024.2401078","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0

摘要

我们通过两个实际应用案例,探讨了机器学习(ML)模型在两个金融风险管理领域(即信用风险管理和金融风险对冲)中的应用潜力。这...
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
Explainable machine learning for financial risk management: two practical use cases
We explore the potential of machine learning (ML) models applied in two financial risk management areas, i.e., credit risk management and financial risk hedging, through two practical use cases. Th...
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
Statistics
Statistics 数学-统计学与概率论
CiteScore
1.00
自引率
0.00%
发文量
59
审稿时长
12 months
期刊介绍: Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
期刊最新文献
Robust estimator of the ruin probability in infinite time for heavy-tailed distributions Gaussian modeling with B-splines for spatial functional data on irregular domains A note on the asymptotic behavior of a mildly unstable integer-valued AR(1) model Explainable machine learning for financial risk management: two practical use cases Online updating Huber robust regression for big data streams
×
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