Volume 9 Number 2 (Feb. 2014)
Home > Archive > 2014 > Volume 9 Number 2 (Feb. 2014) >
JSW 2014 Vol.9(2): 313-318 ISSN: 1796-217X
doi: 10.4304/jsw.9.2.313-318

Least-square Support Vector Machine for Financial Crisis Forecast Based on Particle Swarm Optimization

Xinli Wang
Economics and Management Department, North China Electric Power University, Baoding City, China

Abstract—Whether listed companies run soundly or not has direct impact on development of capital market, therefore, how to forecast financial crisis of listed companies accurately has been a widespread topic. Essentially financial crisis of listed companies is mainly about model pattern classification. Considering that Particle Swarm Optimization (PSO) and Support Vector Machine (SVM) have great performance and strength on classification and regression analysis, this paper puts forward the hybrid forecast thought by combination of the two methods above as research focus. Firstly via building performance indicators, the forecast model based on classification is established and related parameters are optimized by PSO. Then empirical financial crisis analysis will be conducted on this method using financial data of listed companies. The simulation results indicate that the forecast model established in this paper combines the strength of artificial intelligence and statistics, and can avoid phenomenon of over fitting and under fitting compared with traditional models. Moreover, with strong generalization ability, the model is accurate and universal, hence having high application value.

Index Terms—particle swarm optimization, least squares support vector machine, pattern classification, financial crisis

[PDF]

Cite: Xinli Wang, "Least-square Support Vector Machine for Financial Crisis Forecast Based on Particle Swarm Optimization," Journal of Software vol. 9, no. 2, pp. 313-318, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
  • Apr 26, 2021 News!

    Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec)     [Click]

  • Jun 22, 2020 News!

    Papers published in JSW Vol 14, No 1- Vol 15 No 4 have been indexed by DBLP     [Click]

  • Sep 13, 2021 News!

    The papers published in Vol 16, No 6 have all received dois from Crossref    [Click]

  • Jan 28, 2021 News!

    [CFP] 2021 the annual meeting of JSW Editorial Board, ICCSM 2021, will be held in Rome, Italy, July 21-23, 2021   [Click]

  • Sep 13, 2021 News!

    Vol 16, No 6 has been published with online version     [Click]