Conceptual bases of macro prediction on the basis of the neural networks systems

Abstract

Introduction. Under the conditions of accelerated integration of global financial markets, the growth of information exchange speed and large-scale transmission of electronic money, the forecasting of economy scenarios under a sharp change in the environment, particularly during the global financial crisis becomes an important task.

Purpose. The aim of the research is to develop and substantiate the conceptual principles of macro-prediction on the basis of the neural networks system in conditions of increasing non-linearity of the environment.

Method (methodology). The use of system analysis, integrated approaches which are based on the principles of economic theory, on the one hand, and, on the other, on the conceptual basis of economic and mathematical modeling of economics and finances processes, have become the methodological basis of the research.

Results. The use of the neural networks system in the task of macro prediction of the economic systems behavior under the crisis conditions has been justified. It has been definitedthe list of indicators that formed a training sample for simulation. The basic functional model of information technology of the forecasting process has been constructed.