Classification methods in the research on the financial standing of construction enterprises after bankruptcy in Poland

Abstract

In the literature devoted to applications of multivariate statistical analysis to finance, the issue of bankruptcy forecasting is dealt with at length, but few papers concern the statistical evaluation of financial standing of companies after they have been declared bankrupt. The examination of their way out from the insolvency problem may be a source of valuable information, useful for the assessment of the probability that other bankrupt enterprises achieve success as a result of the execution of restructuring proposals. The purpose of this article is to present a proposal to use selected classification methods when studying the financial standing of companies after the declaration of bankruptcy in comparison with the situation of financially sound companies. The logit model and the classification tree were used to classify companies. The evaluation of the classification efficiency was based on the following measures: sensitivity, specificity and AUC. In the study, both univariate (Tukey’s criterion) and multivariate (projection depth function) methods for detecting outliers were considered. The study covered construction companies in Poland in the years 2005–2009.