Подход к прогнозированию финансового состояния предприятия с учетом изменения макроэкономических показателей

Аудит и финансовый анализ. 2016. № 4. С. 195–200.

Биджоян Д. С.

Analysis and forecasting the financial statement of company play a very important role in decision-making process as for investors and management to implement good governance. For 80 years, the study of this problem was proposed huge number of models fundamentally different from each other methodologically. This article analyzes the main approaches to forecasting bankruptcy and solvency that could be classified into four group: expert models, multiple discriminant analysis, logistic regression, neural networks. The advantages and disadvantages of each method are represented. Based on the analysis of existing methods flaw inherent have been identified in all techniques consisting in not including in the model macroeconomic factors, and an approach based on logistic regression on panel data taking into account the macroeconomic situation. Under macroeconomic indicators are understood currencies against the dollar and the euro, the price of Brent crude oil, as well as the refinance and tax rates.

Keywords: неплатежеспособность, дискриминантный анализ, нейронные сети, financial statements, логистическая регрессия, discriminant analysis, финансовое состояние, прогнозирование банкротства предприятия, tax rate, logistic regression model, макроэкономические факторы, artificial neural networks, currency, bankruptcy forecasting, ключевая ставка, курс валюты, mecroeconomic factors, Insolvency forecasting