Optimizing composite early warning indicators

IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE
Daniel O. Beltran , Vihar M. Dalal , Mohammad R. Jahan-Parvar , Fiona A. Paine
{"title":"Optimizing composite early warning indicators","authors":"Daniel O. Beltran ,&nbsp;Vihar M. Dalal ,&nbsp;Mohammad R. Jahan-Parvar ,&nbsp;Fiona A. Paine","doi":"10.1016/j.najef.2024.102250","DOIUrl":null,"url":null,"abstract":"<div><p>Research on predicting financial crises has produced various composite early warning indicators (EWIs) using macroeconomic and financial time-series. Much of the focus has been on identifying the best leading indicators for financial crises (e.g., credit-to-GDP ratios, financial asset prices, etc.). This paper instead focuses on how to optimally extract and combine signals from multiple cyclical indicators. We find that when combining multiple indicators into a composite EWI, jointly optimizing the indicators improves performance relative to optimizing individually and combining their signals. The performance of our jointly optimized EWIs is robust to the key modelling choices inherent in their design including the trend-cycle decomposition method and the preference for false positives over false negatives.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"74 ","pages":"Article 102250"},"PeriodicalIF":3.8000,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"North American Journal of Economics and Finance","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S106294082400175X","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

Abstract

Research on predicting financial crises has produced various composite early warning indicators (EWIs) using macroeconomic and financial time-series. Much of the focus has been on identifying the best leading indicators for financial crises (e.g., credit-to-GDP ratios, financial asset prices, etc.). This paper instead focuses on how to optimally extract and combine signals from multiple cyclical indicators. We find that when combining multiple indicators into a composite EWI, jointly optimizing the indicators improves performance relative to optimizing individually and combining their signals. The performance of our jointly optimized EWIs is robust to the key modelling choices inherent in their design including the trend-cycle decomposition method and the preference for false positives over false negatives.

优化综合预警指标
关于预测金融危机的研究利用宏观经济和金融时间序列产生了各种综合预警指标(EWIs)。大部分研究的重点是确定金融危机的最佳先行指标(如信贷与国内生产总值比率、金融资产价格等)。本文则关注如何从多个周期性指标中提取并优化组合信号。我们发现,在将多个指标组合成一个综合 EWI 时,联合优化这些指标相对于单独优化和组合它们的信号会提高性能。我们联合优化的 EWI 的性能对其设计中固有的关键建模选择(包括趋势-周期分解方法和假阳性优于假阴性)是稳健的。
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
CiteScore
7.30
自引率
8.30%
发文量
168
期刊介绍: The focus of the North-American Journal of Economics and Finance is on the economics of integration of goods, services, financial markets, at both regional and global levels with the role of economic policy in that process playing an important role. Both theoretical and empirical papers are welcome. Empirical and policy-related papers that rely on data and the experiences of countries outside North America are also welcome. Papers should offer concrete lessons about the ongoing process of globalization, or policy implications about how governments, domestic or international institutions, can improve the coordination of their activities. Empirical analysis should be capable of replication. Authors of accepted papers will be encouraged to supply data and computer programs.
×
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