The application of ensemble methods in forecasting bankruptcy

Miklós Virág and Tamás Nyitrai

Financial and Economic Review, 2014, vol. 13, issue 4, 178-193

Abstract: In practice, one chosen method is generally used to solve classification tasks. Although the most modern procedures yield excellent accuracy rates, international research findings show that a concurrent (ensemble) application of methods with weaker classification performance achieves comparable rates of high accuracy. This article’s main objective is to compare the predictive power of the two ensemble methods (Adaboost and Bagging) most commonly used in bankruptcy prediction, using a sample consisting of 976 Hungarian corporations. The article’s other objective is to compare the accuracy rates of bankruptcy models built on the deviations in specific financial ratios from industry averages to those of models built on financial ratios and variables factoring in their dynamics.

Keywords: bankruptcy prediction; ensemble methods; industry average; decision trees (search for similar items in EconPapers)
JEL-codes: C38 C49 G33 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://english.hitelintezetiszemle.hu/letoltes/8-virag-nyitrai-en.pdf

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:mnb:finrev:v:13:y:2014:i:4:p:180-195

Access Statistics for this article

More articles in Financial and Economic Review from Magyar Nemzeti Bank (Central Bank of Hungary) Contact information at EDIRC.
Bibliographic data for series maintained by Morvay Endre ( this e-mail address is bad, please contact ).