Fedorova E.A.Financial University under Government of Russian Federation, Moscow, Russian Federation ecolena@mail.ru
Timofeev Ya.V.Financial University under Government of Russian Federation, Moscow, Russian Federation timofeo@bk.ru
There are two approaches to enterprise bankruptcy prediction: one draws on statutory regulations, and the other one draws on the use of bankruptcy prediction models. We chose construction and agriculture as the study objects, as the share of these industries accounts for about 9% of Russian GDP. Therefore, it is essential for financial management of enterprises operating in the sectors to ensure their sustainability. In the study, based on the sampling of domestic enterprises, we have developed models with high accuracy of bankruptcy prediction of enterprises involved in construction and agriculture. We used financial statements of 1,378 construction enterprises (including 378 bankrupts) and 1,412 farms (including 412 bankrupts) from SPARK and Ruslana information systems. We used four categories of indicators, including liquidity, solvency indicators, and indicators mentioned in statutory regulations. On the basis of logit regression, we have developed two models having a higher predictive capability as compared to the models by Altman, Fulmer, Taffler, O.P. Zaitseva and the ISEA. The maximum forecast power of the developed model for agriculture is 78.3%, in general case, 88.59% for healthy companies, and 77.18%, for potential bankrupts. The overall predictive capability of the developed model for the construction industry is 81.33%. However, bankrupt enterprises are better predicted under the Fulmer model (by 13.05% versus the developed model).
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