МОДЕЛИРОВАНИЕ ВЕРОЯТНОСТИ БАНКРОТСТВА КОМПАНИЙ СТРОИТЕЛЬНОЙ ОТРАСЛИ

Abstract

Due to the unstable economic situation, companies are facing financial difficulties, so their assessment of the likelihood of bankruptcy in the short term is more than relevant. This article reflects the main results of building a model for predicting the probability of bankruptcy of companies in the construction industry: companies, developers. The model was built using a statistical method – logistic regression. The sample of the study included operating construction companies that operate on the territory of the Russian Federation and bankrupt companies. Initially, the study sample consisted of 132 companies, data on which were collected using the Russian reference and information system SPARK. The total sample of the study was divided into training and test in the ratio of 80% and 20%, respectively. The endogenous variable was a binary one, and the exogenous variables were 10 financial indicators selected by experts based on a literature review. As a result, the following factors turned out to be significant: solvency ratio; coverage ratio; asset turnover ratio. According to the results of the study, the accuracy of predicting bankrupt companies of the author's model is 76,2%, and nonbankrupt 83,3%. The overall predictive power of the logit model is 78%. The obtained model for predicting the probability of bankruptcy of companies in the construction industry, firms that operate in the wholesale and retail trade in building materials and goods for repairs, can be introduced into their scoring system for assessing the reliability of counterparties in order to conduct a more accurate scoring procedure and minimize financial risks.