ANALYSIS OF IMPACT OF USING THE TREND VARIABLES ON BANKRUPTCY PREDICTION MODELS PERFORMANCE

• Authors: Gavurová Beáta , Janke František , Packová Miroslava
• Languages of publication: EN

Abstracts

EN

The main objective of this paper is to analyse the impact of trend variables on the predictive ability of the models constructed using two methods: discriminant analysis and decision tree technique. The second objective is to develop a new model with prediction accuracy higher by at least 10% in comparison with other models being currently used in the Slovak business environment (Altman model, Index IN05). After analysing and comparing these methods, we came to the conclusion that the most suitable method for developing the model was the decision tree technique. Using this technique we were able to extract classification rules for bankruptcy prediction and achieve predictive ability of about 85% which, in comparison with other models, showed higher predictive performance by about 10%. Moreover, we confirmed that by applying the dynamic approach predictive ability of the decision tree increased; however we did not derive the same result using the discriminant analysis method.

Keywords

EN

BANKRUPTCY PREDICTION MODELS; FAILURE; DISCRIMINANT ANALYSIS; DECISION TREE

• Publisher: Institute of Slovak and World Economics and Institute for Forecasting, Slovak Academy of Sciences
• Journal: Ekonomický časopis (Journal of Economics)
• Year: 2017
• Volume: 65
• Issue: 4
• Pages: 370 – 383

Contributors

author

Gavurová Beáta

• Technical University of Košice, Faculty of Economics, Department of Banking and Investment, B. Němcovej 32, 040 01 Košice, Slovak Republic

author

Janke František

author

Packová Miroslava