INTEGRATED MODEL PREDICTION STABILITY OF THE FINANCIAL ORGANIZATIONS

Abstract

The paper outlines the key principles of an integrated method of analysis of financial stability of the financial and economic organizations of the banking sector. The research focuses on the use of the openly available financial information of banks and recommends a wide range of interested users to make different investment decisions. The article analyzes the mathematical foundations of forecasting the financial stability of banks. The necessity of primary processing of rated incoming information in the form of time series is established. The essence of methodologies of integrated autoregression with moving average and multilayer perceptron neural networks is explained. Provides the recommendations for improving the methods of forecasting financial stability of the bank. The article proves the feasibility of using a comprehensive application of the modelling methodology. The results of practical calculations application of the methodology for the Ukrainian financial market are provided.

Keywords

• моделі прогнозування
• фінансова стійкість банку
• часовий ряд
• персептронна нейромережева модель
• проінтегрована авторегресія