An evaluation of the effectiveness of three early-warning models on financial indexes
Yumei He,
Xinyi Xu,
Yuewen Cai and
Mengya Cheng
Applied Economics Letters, 2022, vol. 29, issue 20, 1880-1884
Abstract:
In this paper, we construct three financial early warning models, and evaluate and compare their early warning effects. These models are based on factor analysis, logistic regression, and Verhulst-BP neural network, taking Chinese listed mineral resource companies as samples. The results show that the model based on Verhulst-BP neural network has the best early warning effect among the three models, and the early warning model based on logistic regression is more accurate than the one based on factor analysis.
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/13504851.2021.1965079 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:apeclt:v:29:y:2022:i:20:p:1880-1884
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20
DOI: 10.1080/13504851.2021.1965079
Access Statistics for this article
Applied Economics Letters is currently edited by Anita Phillips
More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().