Selection of variables in the function of improving the bankruptcy prediction model

Abstract

The significance of early disclosure of the probability of launching a bankruptcy proceeding leads the authors to develop a model of high prediction power. In this way, the authors use different variables and statistical tools, and techniques. The impact of the economic environment and data availability limits the introduction of certain variables in bankruptcy prediction models. The paper aims to explore attitudes in existing literature regarding the selection of variables used to develop models for predicting bankruptcy, their characteristics, limitations, and impact on the power of predictions. The labor findings show that the historical character of the data and the conservative approach to financial reporting have turned authors to the use of non-financial and market variables. For the most part, efficient markets absorb all external and internal information and future predictions, which are read through market prices. However, this assumption does not apply to less developed markets, and the use of market variables is questionable. In conditions of increased systemic risk, macroeconomic variables can be good indicators for predicting the likelihood of bankruptcy. Developing a model for predicting bankruptcy requires looking at the economic environment and choosing variables that correspond to existing business conditions. With the changing economic environment, adjustment of the model needs to be made so that the accuracy of the forecast does not decrease.