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• W2891873405 startingPage "e0202209" @default.
• W2891873405 abstract "Analyzing and predicting the trend of price fluctuation has been receiving more and more attention, as price risk has become the focus of risk control research in heating oil futures market. A novel time series prediction model combined with the complex network method is put forward in the paper. First of all, this paper counts the cumulative time interval of different nodes in the network, and fits its growth trend with the Fourier model. Then a novel price fluctuation prediction model is established based on the effective information such as some topology properties extracted from the network. The results show that the Fourier model can predict the emergence time of new nodes in the next stage, and the established price fluctuation prediction model can infer the names of nodes in the prediction interval, so as to determine the forward-looking behavior of price evolution. Besides, liken to the NAR neural network, the prediction results obtained by the proposed method also show superiority, which has important theoretical value and academic significance for early warning and prediction of price behavior in the heating oil futures market." @default.
• W2891873405 created "2018-09-27" @default.
• W2891873405 creator A5008304437 @default.
• W2891873405 creator A5078632164 @default.
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• W2891873405 date "2018-09-05" @default.
• W2891873405 modified "2023-09-23" @default.
• W2891873405 title "Research on the forward-looking behavior judgment of heating oil price evolution based on complex networks" @default.
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• W2891873405 doi "https://doi.org/10.1371/journal.pone.0202209" @default.
• W2891873405 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6124714" @default.
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