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Research on the Transmission Ability of China’s Thermal Coal Price Information Based on Directed Limited Penetrable Interdependent Network

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  • Guangyong Zhang

    (Energy Development and Environmental Protection Strategy Research Center, Jiangsu University, Zhenjiang 212013, China)

  • Lixin Tian

    (Energy Development and Environmental Protection Strategy Research Center, Jiangsu University, Zhenjiang 212013, China
    Energy Interdependence Behavior and Strategy Research Center, School of Mathematical Sciences, Nanjing Normal University, Nanjing 210046, China)

  • Min Fu

    (Energy Development and Environmental Protection Strategy Research Center, Jiangsu University, Zhenjiang 212013, China)

  • Bingyue Wan

    (Energy Development and Environmental Protection Strategy Research Center, Jiangsu University, Zhenjiang 212013, China)

  • Wenbin Zhang

    (Energy Development and Environmental Protection Strategy Research Center, Jiangsu University, Zhenjiang 212013, China
    School of Mathematical Science, Taizhou Institute of Sci. & Tech., NUST, Taizhou 225300, China)

Abstract

According to the criterion of the visibility graph and the irreversibility of the time series, this paper proposes a new perspective to construct the directed limited penetrable interdependent network (DLPIN) for thermal coal between the opening and closing price series after the Johansen cointegration test. The results of the statistical research and cointegration analysis show that there is a cointegration relationship between the opening and the closing price series, and the relationship between them does not follow a normal distribution. By analyzing the topological characteristic of the DLPIN, the results indicate that there is an obvious "community structure" and scale-free features, which show that there are groups and differences among the thermal coal price, and most of them have a weak transmission ability of the thermal coal price information; only a few of them have a strong transmission ability. The differences of the in-degree and out-degree show that some thermal coal prices have a weak influence on the other prices but are strongly affected by the other prices. In addition, most of the thermal coal prices are far away from the infectious source of the price information; only a few are close to the infectious source of the price information to a certain extent. Obviously, the influence of the thermal coal price has a certain range, which is closely related in a short distance. Furthermore, these results can reveal the internal laws of the main price fluctuation and information transmission for the thermal coal, and some references can be provided to reduce risk investment and improve capital return for the related investors.

Suggested Citation

  • Guangyong Zhang & Lixin Tian & Min Fu & Bingyue Wan & Wenbin Zhang, 2020. "Research on the Transmission Ability of China’s Thermal Coal Price Information Based on Directed Limited Penetrable Interdependent Network," Sustainability, MDPI, vol. 12(18), pages 1-23, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7815-:d:417211
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    References listed on IDEAS

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    1. Chen, Zhan-Ming, 2014. "Inflationary effect of coal price change on the Chinese economy," Applied Energy, Elsevier, vol. 114(C), pages 301-309.
    2. Zaklan, Aleksandar & Cullmann, Astrid & Neumann, Anne & von Hirschhausen, Christian, 2012. "The globalization of steam coal markets and the role of logistics: An empirical analysis," Energy Economics, Elsevier, vol. 34(1), pages 105-116.
    3. Ellerman, A Denny, 1995. "The world price of coal," Energy Policy, Elsevier, vol. 23(6), pages 499-506, June.
    4. Alameer, Zakaria & Fathalla, Ahmed & Li, Kenli & Ye, Haiwang & Jianhua, Zhang, 2020. "Multistep-ahead forecasting of coal prices using a hybrid deep learning model," Resources Policy, Elsevier, vol. 65(C).
    5. Papież, Monika & Śmiech, Sławomir, 2013. "Causality-in-mean and causality-in-variance within the international steam coal market," Energy Economics, Elsevier, vol. 36(C), pages 594-604.
    6. Matyjaszek, Marta & Riesgo Fernández, Pedro & Krzemień, Alicja & Wodarski, Krzysztof & Fidalgo Valverde, Gregorio, 2019. "Forecasting coking coal prices by means of ARIMA models and neural networks, considering the transgenic time series theory," Resources Policy, Elsevier, vol. 61(C), pages 283-292.
    7. Yang, Chi-Jen & Xuan, Xiaowei & Jackson, Robert B., 2012. "China's coal price disturbances: Observations, explanations, and implications for global energy economies," Energy Policy, Elsevier, vol. 51(C), pages 720-727.
    8. Batten, Jonathan A. & Brzeszczynski, Janusz & Ciner, Cetin & Lau, Marco C.K. & Lucey, Brian & Yarovaya, Larisa, 2019. "Price and volatility spillovers across the international steam coal market," Energy Economics, Elsevier, vol. 77(C), pages 119-138.
    9. David Humphreys & Keith Welham, 2000. "The restructuring of the international coal industry," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 13(4), pages 333-347.
    10. Guo, Jin & Zheng, Xinye & Chen, Zhan-Ming, 2016. "How does coal price drive up inflation? Reexamining the relationship between coal price and general price level in China," Energy Economics, Elsevier, vol. 57(C), pages 265-276.
    11. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    12. Haftendorn, C. & Kemfert, C. & Holz, F., 2012. "What about coal? Interactions between climate policies and the global steam coal market until 2030," Energy Policy, Elsevier, vol. 48(C), pages 274-283.
    13. Papież, Monika & Śmiech, Sławomir, 2015. "Dynamic steam coal market integration: Evidence from rolling cointegration analysis," Energy Economics, Elsevier, vol. 51(C), pages 510-520.
    14. Cui, Herui & Wei, Pengbang, 2017. "Analysis of thermal coal pricing and the coal price distortion in China from the perspective of market forces," Energy Policy, Elsevier, vol. 106(C), pages 148-154.
    15. Warell, Linda, 2005. "Defining geographic coal markets using price data and shipments data," Energy Policy, Elsevier, vol. 33(17), pages 2216-2230, November.
    16. Clemens Haftendorn & Franziska Holz, 2010. "Modeling and Analysis of the International Steam Coal Trade," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 205-230.
    17. Raymond Li & Roselyne Joyeux & Ronald D. Ripple, 2010. "International Steam Coal Market Integration," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 181-202.
    18. Sun, Qi & Xu, Weijun & Xiao, Weilin, 2013. "An empirical estimation for mean-reverting coal prices with long memory," Economic Modelling, Elsevier, vol. 33(C), pages 174-181.
    19. Ekawan, Rudianto & Duchene, Michel, 2006. "The evolution of hard coal trade in the Atlantic market," Energy Policy, Elsevier, vol. 34(13), pages 1487-1498, September.
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