IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0202209.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0202209
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0202209&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0202209?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Richard J. Williams & Neo D. Martinez, 2000. "Simple rules yield complex food webs," Nature, Nature, vol. 404(6774), pages 180-183, March.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiao, Jihong & Zhou, Min & Wen, Fengming & Wen, Fenghua, 2018. "Asymmetric impacts of oil price uncertainty on Chinese stock returns under different market conditions: Evidence from oil volatility index," Energy Economics, Elsevier, vol. 74(C), pages 777-786.
    2. Jihong Xiao & Xuehong Zhu & Chuangxia Huang & Xiaoguang Yang & Fenghua Wen & Meirui Zhong, 2019. "A New Approach for Stock Price Analysis and Prediction Based on SSA and SVM," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 287-310, January.
    3. Wen, Fenghua & Wu, Nan & Gong, Xu, 2020. "China's carbon emissions trading and stock returns," Energy Economics, Elsevier, vol. 86(C).
    4. Wen, Fenghua & Zhao, Cong & Hu, Chunyan, 2019. "Time-varying effects of international copper price shocks on China's producer price index," Resources Policy, Elsevier, vol. 62(C), pages 507-514.
    5. Shihui Tian & Guowei Hua & T. C. E. Cheng, 2019. "Optimal Deployment of Charging Piles for Electric Vehicles Under the Indirect Network Effects," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(01), pages 1-17, February.
    6. Guangyong Zhang & Lixin Tian & Wenbin Zhang & Xu Yan & Bingyue Wan & Zaili Zhen, 2020. "A Study on the Similarities and Differences of the Conventional Gasoline Spot Price Fluctuation Network between Different Harbors," Sustainability, MDPI, vol. 12(2), pages 1-25, January.
    7. Li, Wenlan & Cheng, Yuxiang & Fang, Qiang, 2020. "Forecast on silver futures linked with structural breaks and day-of-the-week effect," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    8. Wang, Minggang & Zhao, Longfeng & Du, Ruijin & Wang, Chao & Chen, Lin & Tian, Lixin & Eugene Stanley, H., 2018. "A novel hybrid method of forecasting crude oil prices using complex network science and artificial intelligence algorithms," Applied Energy, Elsevier, vol. 220(C), pages 480-495.
    9. He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
    10. Zhujia Yin & Yantuan Yu & Jianhuan Huang, 2018. "Evaluation and evolution of bank efficiency considering heterogeneity technology: An empirical study from China," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-19, October.
    11. Min Zhou & Xiaoqun Liu & Guoan Tang, 2018. "Effect of urban tourist satisfaction on urban macroeconomics in China: A spatial panel econometric analysis with a spatial Durbin model," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-24, October.
    12. Wang, Minggang & Xu, Hua & Tian, Lixin & Eugene Stanley, H., 2018. "Degree distributions and motif profiles of limited penetrable horizontal visibility graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 620-634.
    13. Chunlin Luo & Xin Tian & Xiaobing Mao & Qiang Cai, 2018. "Coordinating Supply Chain with Buy-Back Contracts in the Presence of Risk Aversion," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(02), pages 1-19, April.
    14. Liu, Renren & Chen, Jianzhong & Wen, Fenghua, 2021. "The nonlinear effect of oil price shocks on financial stress: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    15. Liu, Hong & Wang, Chang & Tian, Meiyu & Wen, Fenghua, 2019. "Analysis of regional difference decomposition of changes in energy consumption in China during 1995–2015," Energy, Elsevier, vol. 171(C), pages 1139-1149.
    16. Wen, Fenghua & Zhang, Keli & Gong, Xu, 2021. "The effects of oil price shocks on inflation in the G7 countries," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    17. Xiao, Jihong & Hu, Chunyan & Ouyang, Guangda & Wen, Fenghua, 2019. "Impacts of oil implied volatility shocks on stock implied volatility in China: Empirical evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 80(C), pages 297-309.
    18. Jin‐Yu Chen & Xue‐Hong Zhu & Mei‐Rui Zhong, 2021. "Time‐varying effects and structural change of oil price shocks on industrial output: Evidence from China's oil industrial chain," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3460-3472, July.
    19. Xu, Hua & Wang, Minggang & Jiang, Shumin & Yang, Weiguo, 2020. "Carbon price forecasting with complex network and extreme learning machine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    20. Jeng-Bau Lin & Chin-Chia Liang & Wei Tsai, 2019. "Nonlinear Relationships between Oil Prices and Implied Volatilities: Providing More Valuable Information," Sustainability, MDPI, vol. 11(14), pages 1-15, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0202209. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.