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Journal of Automation and Information Sciences
SJR: 0.275 SNIP: 0.59 CiteScore™: 0.8

ISSN Imprimir: 1064-2315
ISSN En Línea: 2163-9337

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Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v40.i3.60
pages 59-69

Comparative Analysis of Some Forecasting Methods on Nonstationary Processes

Petr I. Bidyuk
Institute for Applied System Analysis of National Technical University of Ukraine "Igor Sikorsky Kiev Polytechnic Institute", Kiev
Andrey V. Fedorov
Institute of Applied System analysis of National Technical University of Ukraine "Kiev Polytechnical Institute", Kiev, Ukraine

SINOPSIS

Two types of mathematical models are proposed to forecast the process of stock price formation on gold. To ensure the insightful analysis of the nonstationary processes of this kind, the probabilistic dynamic Bayesian network is proposed. GMDH and autoregressive model that supplemented the probabilistic model improved the quality of decisions taken while stock exchange operations. The comparative analysis is performed and the best models are selected for the processes analyzed. The model for a short-term forecast of the conditional variance of the process is constructed.


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