Journal of Automation and Information Sciences
年間 12 号発行
ISSN 印刷: 1064-2315
ISSN オンライン: 2163-9337
SJR:
0.173
SNIP:
0.588
CiteScore™::
2
Indexed in
Comparative Analysis of Some Forecasting Methods on Nonstationary Processes
巻 40,
発行 3, 2008,
pp. 59-69
DOI: 10.1615/JAutomatInfScien.v40.i3.60
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要約
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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