EconPapers    
Economics at your fingertips  
 

Design of Financial Crisis Early Warning Model Based on PSO-SVM Algorithm

Wan Li and Wenlong Hang

Mathematical Problems in Engineering, 2022, vol. 2022, 1-8

Abstract: To address the problem that the accuracy of the SVM algorithm is affected by random parameters at the input end, a financial crisis early warning model (FCEWM) based on PSO-SVM is constructed based on the nonequilibrium sample characteristics of different financial conditions of listed companies in China’s gem. The model uses the PSO algorithm to optimize the parameters of SVM and selects 24 financial risk evaluation indexes as the input to predict the financial crisis. The results show that the proposed model is superior to other models in prediction accuracy and robustness.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/3241802.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/3241802.xml (application/xml)

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:hin:jnlmpe:3241802

DOI: 10.1155/2022/3241802

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().

 
Page updated 2025-03-19
Handle: RePEc:hin:jnlmpe:3241802