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The influence of the Shanghai crude oil futures on the global and domestic oil markets

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  • Wang, Jianli
  • Qiu, Shushu
  • Yick, Ho Yin

Abstract

The newly established Shanghai crude oil futures market provides a natural experimental setting for studying the price cointegration and causal relationships between the Chinese domestic benchmark (Daqing) and international benchmarks (West Texas Intermediate and Brent). We find a significant change in the relationships between domestic and global oil prices before and after the launch of the Shanghai market. Moreover, using a Johansen cointegration test and a vector error correction model, we find long-term equilibrium and short-term relationships between the Shanghai market and global benchmarks. Shanghai crude oil futures prices also play a leading role in the price discovery of domestic crude oil spot prices, reflecting their dominant influence on the domestic market. The prices of the domestic crude oil market are thus becoming less influenced by global benchmarks but more influenced by the Shanghai crude oil futures market. The examined results of dynamic ARDL simulations model support the long run and short run relations between the Shanghai market and global benchmarks. The results also shows that the Shanghai crude oil futures market has response lags relative to those benchmarks.

Suggested Citation

  • Wang, Jianli & Qiu, Shushu & Yick, Ho Yin, 2022. "The influence of the Shanghai crude oil futures on the global and domestic oil markets," Energy, Elsevier, vol. 245(C).
  • Handle: RePEc:eee:energy:v:245:y:2022:i:c:s0360544222001748
    DOI: 10.1016/j.energy.2022.123271
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    1. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Market Efficiency of Oil Spot and Futures: A Stochastic Dominance Approach," CIRJE F-Series CIRJE-F-705, CIRJE, Faculty of Economics, University of Tokyo.
    2. Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LP, vol. 23(4), pages 983-1019, December.
    3. Arouri, Mohamed El Hédi & Lahiani, Amine & Lévy, Aldo & Nguyen, Duc Khuong, 2012. "Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models," Energy Economics, Elsevier, vol. 34(1), pages 283-293.
    4. Muhammad Kamran Khan & Jian-Zhou Teng & Muhammad Imran Khan, 2019. "Asymmetric impact of oil prices on stock returns in Shanghai stock exchange: Evidence from asymmetric ARDL model," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-14, June.
    5. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2010. "Market efficiency of oil spot and futures: A mean-variance and stochastic dominance approach," Energy Economics, Elsevier, vol. 32(5), pages 979-986, September.
    6. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    7. Jiang, Zhi-Qiang & Xie, Wen-Jie & Zhou, Wei-Xing, 2014. "Testing the weak-form efficiency of the WTI crude oil futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 235-244.
    8. Fasanya, Ismail & Akinbowale, Seun, 2019. "Modelling the return and volatility spillovers of crude oil and food prices in Nigeria," Energy, Elsevier, vol. 169(C), pages 186-205.
    9. Liu, Xiang-dong & Pan, Fei & Yuan, Lin & Chen, Yu-wang, 2019. "The dependence structure between crude oil futures prices and Chinese agricultural commodity futures prices: Measurement based on Markov-switching GRG copula," Energy, Elsevier, vol. 182(C), pages 999-1012.
    10. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    11. M. Hashem Pesaran & Yongcheol Shin, 2002. "Long-Run Structural Modelling," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 49-87.
    12. Muhammad Kamran Khan & Jian-Zhou Teng & Javed Pervaiz & Sunil Kumar Chaudhary, 2017. "Nexuses between Economic Factors and Stock Returns in China," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(9), pages 182-191, September.
    13. Gregory, Allan W. & Hansen, Bruce E., 1996. "Residual-based tests for cointegration in models with regime shifts," Journal of Econometrics, Elsevier, vol. 70(1), pages 99-126, January.
    14. Khan, Muhammad Imran & Teng, Jian-Zhou & Khan, Muhammad Kamran & Jadoon, Arshad Ullah & Khan, Muhammad Fayaz, 2021. "The impact of oil prices on stock market development in Pakistan: Evidence with a novel dynamic simulated ARDL approach," Resources Policy, Elsevier, vol. 70(C).
    15. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    16. 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.
    17. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    18. Gebre-Mariam, Yohannes Kebede, 2011. "Testing for unit roots, causality, cointegration, and efficiency: The case of the northwest US natural gas market," Energy, Elsevier, vol. 36(5), pages 3489-3500.
    19. Ji, Qiang & Zhang, Dayong, 2019. "China’s crude oil futures: Introduction and some stylized facts," Finance Research Letters, Elsevier, vol. 28(C), pages 376-380.
    20. Soren Jordan & Andrew Q. Philips, 2018. "Cointegration testing and dynamic simulations of autoregressive distributed lag modelsJournal: Stata Journal," Stata Journal, StataCorp LP, vol. 18(4), pages 902-923, December.
    21. Brahmasrene, Tantatape & Huang, Jui-Chi & Sissoko, Yaya, 2014. "Crude oil prices and exchange rates: Causality, variance decomposition and impulse response," Energy Economics, Elsevier, vol. 44(C), pages 407-412.
    22. Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LP, vol. 23(4), pages 983-1019, December.
    23. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality," Energy Economics, Elsevier, vol. 30(5), pages 2673-2685, September.
    24. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    25. Lyu, Yongjian & Wei, Yu & Hu, Yingyi & Yang, Mo, 2021. "Good volatility, bad volatility and economic uncertainty: Evidence from the crude oil futures market," Energy, Elsevier, vol. 222(C).
    26. AlKathiri, Nader & Al-Rashed, Yazeed & Doshi, Tilak K. & Murphy, Frederic H., 2017. "“Asian premium” or “North Atlantic discount”: Does geographical diversification in oil trade always impose costs?," Energy Economics, Elsevier, vol. 66(C), pages 411-420.
    27. Zhang, Dayong & Ji, Qiang & Kutan, Ali M., 2019. "Dynamic transmission mechanisms in global crude oil prices: Estimation and implications," Energy, Elsevier, vol. 175(C), pages 1181-1193.
    28. Gregory, Allan W & Hansen, Bruce E, 1996. "Tests for Cointegration in Models with Regime and Trend Shifts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(3), pages 555-560, August.
    29. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2015. "Preferences of risk-averse and risk-seeking investors for oil spot and futures before, during and after the Global Financial Crisis," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 204-216.
    30. Wang, Yudong & Wu, Chongfeng, 2013. "Are crude oil spot and futures prices cointegrated? Not always!," Economic Modelling, Elsevier, vol. 33(C), pages 641-650.
    31. Klein, Tony, 2018. "Trends and contagion in WTI and Brent crude oil spot and futures markets - The role of OPEC in the last decade," Energy Economics, Elsevier, vol. 75(C), pages 636-646.
    32. Elder, John & Miao, Hong & Ramchander, Sanjay, 2014. "Price discovery in crude oil futures," Energy Economics, Elsevier, vol. 46(S1), pages 18-27.
    33. An, Sufang & Gao, Xiangyun & An, Haizhong & An, Feng & Sun, Qingru & Liu, Siyao, 2020. "Windowed volatility spillover effects among crude oil prices," Energy, Elsevier, vol. 200(C).
    34. Sadorsky, Perry, 2000. "The empirical relationship between energy futures prices and exchange rates," Energy Economics, Elsevier, vol. 22(2), pages 253-266, April.
    35. Maslyuk, Svetlana & Smyth, Russell, 2009. "Cointegration between oil spot and future prices of the same and different grades in the presence of structural change," Energy Policy, Elsevier, vol. 37(5), pages 1687-1693, May.
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    Cited by:

    1. Cui, Jinxin & Maghyereh, Aktham, 2023. "Time-frequency dependence and connectedness among global oil markets: Fresh evidence from higher-order moment perspective," Journal of Commodity Markets, Elsevier, vol. 30(C).
    2. Viviana Fanelli & Claudio Fontana & Francesco Rotondi, 2023. "A hidden Markov model for statistical arbitrage in international crude oil futures markets," Papers 2309.00875, arXiv.org.
    3. Huang, Wenyang & Gao, Tianxiao & Hao, Yun & Wang, Xiuqing, 2023. "Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices," Energy Economics, Elsevier, vol. 127(PA).
    4. Lee, Chien-Chiang & Zhou, Hegang & Xu, Chao & Zhang, Xiaoming, 2023. "Dynamic spillover effects among international crude oil markets from the time-frequency perspective," Resources Policy, Elsevier, vol. 80(C).
    5. Cui, Jinxin & Maghyereh, Aktham, 2023. "Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," International Review of Financial Analysis, Elsevier, vol. 86(C).

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    More about this item

    Keywords

    Shanghai crude oil futures; Price cointegration; Market efficiency;
    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
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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