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Research on the forward-looking behavior judgment of heating oil price evolution based on complex networks

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  • Lixin Tian
  • Huan Chen
  • Zaili Zhen

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.

Suggested Citation

  • Lixin Tian & Huan Chen & Zaili Zhen, 2018. "Research on the forward-looking behavior judgment of heating oil price evolution based on complex networks," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-18, September.
    • Handle: RePEc:plo:pone00:0202209
    DOI: 10.1371/journal.pone.0202209
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    as
    1. Pagani, Giuliano Andrea & Aiello, Marco, 2014. "Power grid complex network evolutions for the smart grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 248-266.
    2. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    3. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    4. Wang, Minggang & Tian, Lixin, 2016. "From time series to complex networks: The phase space coarse graining," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 456-468.
    5. Feng, Shumin & Hu, Baoyu & Nie, Cen & Shen, Xianghao, 2016. "Empirical study on a directed and weighted bus transport network in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 85-92.
    6. Fenghua Wen & Jihong Xiao & Chuangxia Huang & Xiaohua Xia, 2018. "Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 319-334, January.
    7. Huan Chen & Lixin Tian & Minggang Wang & Zaili Zhen, 2017. "Analysis of the Dynamic Evolutionary Behavior of American Heating Oil Spot and Futures Price Fluctuation Networks," Sustainability, MDPI, vol. 9(4), pages 1-29, April.
    8. Hu, Jianming & Wang, Jianzhou & Zeng, Guowei, 2013. "A hybrid forecasting approach applied to wind speed time series," Renewable Energy, Elsevier, vol. 60(C), pages 185-194.
    9. An, Haizhong & Gao, Xiangyun & Fang, Wei & Ding, Yinghui & Zhong, Weiqiong, 2014. "Research on patterns in the fluctuation of the co-movement between crude oil futures and spot prices: A complex network approach," Applied Energy, Elsevier, vol. 136(C), pages 1067-1075.
    10. Min Zhou & Xiaoqun Liu & Bin Pan & Xin Yang & Fenghua Wen & Xiaohua Xia, 2017. "Effect of Tourism Building Investments on Tourist Revenues in China: A Spatial Panel Econometric Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 53(9), pages 1973-1987, September.
    11. Jovani, Roger & Fortuna, Miguel A., 2007. "The shape of the past in the World Wide Web: Scale-free patterns and dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 683-688.
    12. Alam, Sheraz & Sohail, M. Farhan & Ghauri, Sajjad A. & Qureshi, I.M. & Aqdas, Naveed, 2017. "Cognitive radio based Smart Grid Communication Network," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 535-548.
    13. Chunyan Hu & Xinheng Liu & Bin Pan & Bin Chen & Xiaohua Xia, 2018. "Asymmetric Impact of Oil Price Shock on Stock Market in China: A Combination Analysis Based on SVAR Model and NARDL Model," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(8), pages 1693-1705, June.
    14. Kashyap, Yashwant & Bansal, Ankit & Sao, Anil K., 2015. "Solar radiation forecasting with multiple parameters neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 825-835.
    15. Richard J. Williams & Neo D. Martinez, 2000. "Simple rules yield complex food webs," Nature, Nature, vol. 404(6774), pages 180-183, March.
    16. Yan, Ying & Zhang, Shen & Tang, Jinjun & Wang, Xiaofei, 2017. "Understanding characteristics in multivariate traffic flow time series from complex network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 149-160.
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    Cited by:

    1. Donghua Wang & Tianhui Fang, 2022. "Forecasting Crude Oil Prices with a WT-FNN Model," Energies, MDPI, vol. 15(6), pages 1-21, March.

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