ADAPTIVE MODELING AND FORECASTING ECONOMIC AND FINANCIAL PROCESSES

Анотація

The study is directed towards development of adaptive decision support system for modeling and forecasting nonlinear nonstationary processes in economy, finances and other areas of human activities. Widely known are the heteroscedastic, integrated, and cointegrated processes. To determine correctly the processes class special statistical tests are applied what results in correct selection of the model structure. The structure and parameter adaptation procedures for the regression and probabilistic models are proposed as well as respective information system architecture and functional layout are developed. The system development is based on the modern system analysis principles such as hierarchical information system development approach, adaptive model structure estimation, optimization of model parameter estimation procedures, identification, taking into consideration and influence minimization of possible uncertainties met in the whole process of data processing, mathematical model development and forecast estimation. The uncertainties are inherent to data collecting, model structure and parameter estimation, forecasting procedures and play a role of negative influence factors to the information system computational procedures. Reduction of their influence is favorable for enhancing the quality of intermediate and final results of computational experiments. All the methods, models and procedures developed are functioning in the frames of the information decision support system proposed. The system functioning is directed towards improvement of model and forecasts quality as well as decisions based on the forecasts. The illustrative examples of practical application of the system developed proving the system functionality are provided.

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