Prediction of Bankruptcy with SVM Classifiers Among Retail Business Companies in EU

Václav Klepáč and David Hampel
Additional contact information
Václav Klepáč: Department of Statistics and Operation Analysis, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2016, vol. 64, issue 2, 627-634

Abstract: Article focuses on the prediction of bankruptcy of the 850 medium-sized retail business companies in EU from which 48 companies gone bankrupt in 2014 with respect to lag of the used features. From various types of classification models we chose Support vector machines method with linear, polynomial and radial kernels to acquire best results. Pre-processing is enhanced with filter based feature selection like Gain ratio, Chi-square and Relief algorithm to acquire attributes with the best information value. On this basis we deal with random samples of financial data to measure prediction accuracy with the confusion matrices and area under curve values for different kernel types and selected features. From the results it is obvious that with the rising distance to the bankruptcy there drops precision of bankruptcy prediction. The last year (2013) with avaible financial data offers best total prediction accuracy, thus we also infer both the Error I and II types for better recognizance. The 3rd order polynomial kernel offers better accuracy for bankruptcy prediction than linear and radial versions. But in terms of the total accuracy we recommend to use radial kernel without feature selection.

Keywords: bankruptcy prediction; classification; feature selection; support vector machines (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://acta.mendelu.cz/doi/10.11118/actaun201664020627.html (text/html)
http://acta.mendelu.cz/doi/10.11118/actaun201664020627.pdf (application/pdf)
free of charge

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:mup:actaun:actaun_2016064020627

DOI: 10.11118/actaun201664020627

Access Statistics for this article

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis is currently edited by Markéta Havlásková

More articles in Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis from Mendel University Press
Bibliographic data for series maintained by Ivo Andrle ().