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How is China's coke price related with the world oil price? The role of extreme movements

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  • Guo, Yanfeng
  • Wen, Xiaoqian
  • Wu, Yanrui
  • Guo, Xiumei

Abstract

This paper focuses on the relationship between the world oil price and China's coke price, particularly with respect to extreme movements in the world oil price. Based on a daily sample from 2009 to 2015 and the ARJI-GARCH models and copulas, our empirical results show that China's coke price and the world oil price are characterized by GARCH volatility and jump behaviors. Specifically, negative oil price shocks lead to falls in China's coke returns on the following day while positive oil prices have no significant effects. In addition, current coke returns positively respond to the very recent oil price jump intensity, and a time-varying and volatile lower tail dependence is found between the world oil price and China's coke price. Our results are expected to have implications for coke producers and users and policy makers.

Suggested Citation

  • Guo, Yanfeng & Wen, Xiaoqian & Wu, Yanrui & Guo, Xiumei, 2016. "How is China's coke price related with the world oil price? The role of extreme movements," Economic Modelling, Elsevier, vol. 58(C), pages 22-33.
    • Handle: RePEc:eee:ecmode:v:58:y:2016:i:c:p:22-33
    DOI: 10.1016/j.econmod.2016.05.018
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    8. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2017. "Can energy commodity futures add to the value of carbon assets?," Economic Modelling, Elsevier, vol. 62(C), pages 194-206.
    9. Liu, Feng & Shao, Shuai & Zhang, Chuanguo, 2020. "How do China's petrochemical markets react to oil price jumps? A comparative analysis of stocks and commodities," Energy Economics, Elsevier, vol. 92(C).
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    11. Zhang, Chuanguo & Liu, Feng & Yu, Danlin, 2018. "Dynamic jumps in global oil price and its impacts on China's bulk commodities," Energy Economics, Elsevier, vol. 70(C), pages 297-306.
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    More about this item

    Keywords

    World oil price; China's coke price; ARJI-GARCH; Copulas;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • Q38 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Government Policy (includes OPEC Policy)
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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