Importance This article discusses the impact of the company's financial performance on the likelihood of its bankruptcy, considering Russian non-financial companies as a case study. Objectives The article aims to build a model of forecasting bankruptcy of Russian companies of non-financial sector, which will 80-percent-least-reliable predict the bankruptcy of the company a year before its onset. Methods For the study, we used the methods of logit analysis and decision tree. Results The article presents a model that with more than 80-percent-reliability predicted bankruptcy of the company one year before its onset through both statistical method (logistic regression) and methods of machine learning (decision trees). Conclusions and Relevance The models obtained can be used to determine the probability of the company's bankruptcy one year before its onset. For further research in this area, it is possible to include market indicators to improve the quality of the predictive model.
Fedorova E., Gilenko E., Dovzhenko S. Bankruptcy Prediction for Russian Companies: Application of Combined Classifiers. Expert Systems with Applications, 2013, vol. 40, iss. 18, pp. 7285–7293. URL: https://doi.org/10.1016/j.eswa.2013.07.032
Tinoco M., Wilson N. Financial Distress and Bankruptcy Prediction among Listed Companies Using Accounting, Market and Macroeconomic Variables. International Review of Financial Analysis, 2013, vol. 30, pp. 394–419. URL: https://doi.org/10.1016/j.irfa.2013.02.013
Theodossiou P.T. Predicting Shifts in the Mean of a Multivariate Time Series Process: An Application in Predicting Business Failures. Journal of the American Statistical Association, 1993, vol. 88, iss. 422, pp. 441–449.
Wruck K.H. Financial Distress, Reorganization, and Organizational Efficiency. Journal of Financial Economics, 1990, vol. 27, iss. 2, pp. 419–444. URL: https://doi.org/10.1016/0304-405X(90)90063-6
Lugovskaya L. Predicting Default of Russian SMEs on the Basis of Financial and Non-financial Variables. Journal of Financial Services Marketing, 2010, vol. 14, iss. 4, pp. 301–313. URL: https://doi.org/10.1057/fsm.2009.28
Zmijewski M.E.Methodological Issues Related to the Estimation of Financial Distress Prediction Models. Journal of Accounting Research, 1984, vol. 22, pp. 59–82. URL: https://doi.org/10.2307/2490859
Mselmi N., Lahiani A., Hamza T. Financial Distress Prediction: The Case of French Small and Medium-sized Firms. International Review of Financial Analysis, 2017, no. 50, pp. 67–80. URL: https://doi.org/10.1016/j.irfa.2017.02.004
Nam J.-H., Jinn T. Bankruptcy Prediction: Evidence from Korean Listed Companies during the IMF Crisis. Journal of International Financial Management and Accounting, 2000, vol. 11, iss. 3, pp. 178–197. URL: https://doi.org/10.1111/1467-646X.00061