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Journal of Automation and Information Sciences

Publicou 12 edições por ano

ISSN Imprimir: 1064-2315

ISSN On-line: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

Indexed in

Comparative Analysis of Some Forecasting Methods on Nonstationary Processes

Volume 40, Edição 3, 2008, pp. 59-69
DOI: 10.1615/JAutomatInfScien.v40.i3.60
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RESUMO

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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