Template-Type: ReDIF-Article 1.0
Author-Name: Miklós Virág
Author-Name: Tamás Nyitrai
Author-Workplace-Name: Corvinus University Budapest
Author-Email: miklos.virag@uni-corvinus.hu
Title: The application of ensemble methods in forecasting bankruptcy
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.
Classification-JEL: C38, C49, G33
Keywords: bankruptcy prediction, ensemble methods, industry average, decision trees
Journal: Financial and Economic Review  
Pages: 178-193
Volume: 13
Issue: 4
Year: 2014
File-URL: http://english.hitelintezetiszemle.hu/letoltes/8-virag-nyitrai-en.pdf
Handle: RePEc:mnb:finrev:v:13:y:2014:i:4:p:180-195