BANKRUPTCY MODELLING: FACTORS INFLUENCING MODELS PREDICTABILITY

Many authors during the last fifty years have examined several possibilities to predict business failure. They have studied bankruptcy prediction models under different perspectives but still could not indicate the most reliable model. The aim of this article is finding a direction on how to build bankruptcy prediction models. We want to see if the companies' segmentation according to different criteria and using so-called standard financial indicators means better explanatory power while predicting bankruptcy. Considering the research objective, the following hypotheses were set: H1: The usually used financial indicators in financial analysis are the most important for bankruptcy prediction.; H2: The application of a model based on different segmentation criteria improves the reliability of bankruptcy prediction. This paper focuses on the Czech economy, specifically at small and medium-sized enterprises (SMEs). It is the ongoing research about the value of several popular bankruptcy models that are often applied, namely the Altman Z-score, the Ohlson O-score, the Zmijewski's model, the Taffler's model, and the IN05 model. We have used logistic regression and investigated around 2 800 companies, of which 642 failed during 2010 - 2017. Our findings confirm hypothesis H2 and reject hypothesis H1. Some suggestion arises from it. When we develop a bankruptcy model, it is necessary to sort companies according to different criteria. It also confirms findings of the last years literature review the closer the similarity of businesses, the greater accuracy of bankruptcy models. Further, it is required to exploit common used financial indicators with a combination of modified indicators to assess the probability of bankruptcy precisely.