Predicting Bankruptcy under Alternative Conditions: The Effect of a Change in Industry and Time Period on the Accuracy of the Model

According to the literature, bankruptcy prediction models are less accurate if applied under alternative conditions. We created our own bankruptcy prediction model in our previous research. When creating this model, we tried to apply an approach different to previous ones. We used the traditional method of linear discrimination analysis in creating the model, but employed only transformed variables with approximately normal distribution. What is more, the variable pairs are mostly negatively correlated. According to the literature, such factors should positively influence model accuracy. However, there is extremely limited literature about how such application affects the stability of the model's accuracy. The aim of this paper is to analyse the stability of the model's accuracy when applied in different time periods or different lines of business. Moreover, we also aim to examine and discuss the effectiveness of the procedure used to create the model.