IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v26y2021i2p2414-2435.html
   My bibliography  Save this article

Exploring the dynamic price discovery, risk transfer and spillover among INE, WTI and Brent crude oil futures markets: Evidence from the high‐frequency data

Author

Listed:
  • Yue‐Jun Zhang
  • Shu‐Jiao Ma

Abstract

In order to test whether Chinese crude oil futures (INE) has already played the role of futures market and whether it has had a significant impact on international benchmark market, we construct the permanent temporary model and Information Share model based on 15 min of high‐frequency trading data from March 26, 2018 to October 30, 2018 to inspect the proportions of new information in INE and Brent markets, and use the Garbade‐Silber model to measure the risk transfer effect. Furthermore, the generalised spillover index is proposed to examine the effects of return and volatility spillovers among INE, WTI and Brent futures markets. The results reveal that: firstly, during the sample period, INE is not yet a promoter of international benchmark crude oil prices, but more obvious followers. Secondly, although INE has begun to display the price discovery function, it is weaker than that of Brent, and the risk transfer function between them does not appear strong. Finally, INE market mainly acts as a net transmitter of return spillover before August 2018, but it has almost always been the net transmitter of volatility spillover during the full sample period. These findings are of interest to policy makers as well as investors for risk hedging and asset allocation of crude oil portfolios.

Suggested Citation

  • Yue‐Jun Zhang & Shu‐Jiao Ma, 2021. "Exploring the dynamic price discovery, risk transfer and spillover among INE, WTI and Brent crude oil futures markets: Evidence from the high‐frequency data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2414-2435, April.
    • Handle: RePEc:wly:ijfiec:v:26:y:2021:i:2:p:2414-2435
    DOI: 10.1002/ijfe.1914
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.1914
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ijfe.1914?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. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    4. Su, Qian & Chong, Terence Tai-Leung, 2007. "Determining the contributions to price discovery for Chinese cross-listed stocks," Pacific-Basin Finance Journal, Elsevier, vol. 15(2), pages 140-153, April.
    5. Zhifu Mi & Jing Meng & Dabo Guan & Yuli Shan & Malin Song & Yi-Ming Wei & Zhu Liu & Klaus Hubacek, 2017. "Chinese CO2 emission flows have reversed since the global financial crisis," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    6. Zhang, Dayong & Wang, Tiantian & Shi, Xunpeng & Liu, Jia, 2018. "Is hub-based pricing a better choice than oil indexation for natural gas? Evidence from a multiple bubble test," Energy Economics, Elsevier, vol. 76(C), pages 495-503.
    7. Imad A. Moosa, 2002. "Price Discovery and Risk Transfer in the Crude Oil Futures Market: Some Structural Time Series Evidence," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 31(1), pages 155-165, February.
    8. Silvério, Renan & Szklo, Alexandre, 2012. "The effect of the financial sector on the evolution of oil prices: Analysis of the contribution of the futures market to the price discovery process in the WTI spot market," Energy Economics, Elsevier, vol. 34(6), pages 1799-1808.
    9. Hock Tsen Wong, 2019. "Real Exchange Rate Returns And Real Stock Price Returns In The Stock Market Of Malaysia," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(05), pages 1319-1349, December.
    10. Garbade, Kenneth D & Silber, William L, 1983. "Price Movements and Price Discovery in Futures and Cash Markets," The Review of Economics and Statistics, MIT Press, vol. 65(2), pages 289-297, May.
    11. Zhi-Fu Mi & Yi-Ming Wei & Bao-Jun Tang & Rong-Gang Cong & Hao Yu & Hong Cao & Dabo Guan, 2017. "Risk assessment of oil price from static and dynamic modelling approaches," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 929-939, February.
    12. Shen, Yifan & Shi, Xunpeng & Variam, Hari Malamakkavu Padinjare, 2018. "Risk transmission mechanism between energy markets: A VAR for VaR approach," Energy Economics, Elsevier, vol. 75(C), pages 377-388.
    13. Lu‐Tao Zhao & Ya Meng & Yue‐Jun Zhang & Yun‐Tao Li, 2019. "The optimal hedge strategy of crude oil spot and futures markets: Evidence from a novel method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 186-203, January.
    14. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    15. Yue-Jun Zhang & Shu-Hui Li, 2019. "The impact of investor sentiment on crude oil market risks: evidence from the wavelet approach," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1357-1371, August.
    16. Mi, Zhifu & Zheng, Jiali & Meng, Jing & Zheng, Heran & Li, Xian & Coffman, D'Maris & Woltjer, Johan & Wang, Shouyang & Guan, Dabo, 2019. "Carbon emissions of cities from a consumption-based perspective," Applied Energy, Elsevier, vol. 235(C), pages 509-518.
    17. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    18. Figuerola-Ferretti, Isabel & Gonzalo, Jesús, 2010. "Modelling and measuring price discovery in commodity markets," Journal of Econometrics, Elsevier, vol. 158(1), pages 95-107, September.
    19. Zhang, Yue-Jun & Lin, Jia-Juan, 2019. "Can the VAR model outperform MRS model for asset allocation in commodity market under different risk preferences of investors?," International Review of Financial Analysis, Elsevier, vol. 66(C).
    20. Ge Gao & Mo Chen & Jiayu Wang & Kexin Yang & Yujiao Xian & Xunpeng Shi & Ke Wang, 2019. "Sufficient or insufficient: Assessment on the Intended Nationally Determined Contributions (INDCs) of world¡¯s major emitters," CEEP-BIT Working Papers 125, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    21. Chai, Jian & Xing, Li-Min & Zhou, Xiao-Yang & Zhang, Zhe George & Li, Jie-Xun, 2018. "Forecasting the WTI crude oil price by a hybrid-refined method," Energy Economics, Elsevier, vol. 71(C), pages 114-127.
    22. Wang, Yudong & Guo, Zhuangyue, 2018. "The dynamic spillover between carbon and energy markets: New evidence," Energy, Elsevier, vol. 149(C), pages 24-33.
    23. Baillie, Richard T. & Geoffrey Booth, G. & Tse, Yiuman & Zabotina, Tatyana, 2002. "Price discovery and common factor models," Journal of Financial Markets, Elsevier, vol. 5(3), pages 309-321, July.
    24. Xu, Feng & Wan, Difang, 2015. "The impacts of institutional and individual investors on the price discovery in stock index futures market: Evidence from China," Finance Research Letters, Elsevier, vol. 15(C), pages 221-231.
    25. Hock Tsen Wong, 2019. "Volatility spillovers between real exchange rate returns and real stock price returns in Malaysia," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 131-149, January.
    26. 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.
    27. Elder, John & Miao, Hong & Ramchander, Sanjay, 2014. "Price discovery in crude oil futures," Energy Economics, Elsevier, vol. 46(S1), pages 18-27.
    28. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    29. Sarveshwar Kumar Inani, 2018. "Price Discovery and Efficiency of Indian Agricultural Commodity Futures Market: An Empirical Investigation," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 129-154, March.
    30. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "The crude oil market and the gold market: Evidence for cointegration, causality and price discovery," Resources Policy, Elsevier, vol. 35(3), pages 168-177, September.
    31. Shi, Xunpeng & Sun, Sizhong, 2017. "Energy price, regulatory price distortion and economic growth: A case study of China," Energy Economics, Elsevier, vol. 63(C), pages 261-271.
    32. 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.
    33. Zhang, Yue-Jun & Wang, Zi-Yi, 2013. "Investigating the price discovery and risk transfer functions in the crude oil and gasoline futures markets: Some empirical evidence," Applied Energy, Elsevier, vol. 104(C), pages 220-228.
    34. Zhang, Dayong & Shi, Min & Shi, Xunpeng, 2018. "Oil indexation, market fundamentals, and natural gas prices: An investigation of the Asian premium in natural gas trade," Energy Economics, Elsevier, vol. 69(C), pages 33-41.
    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. NICOLAE Simona & GRIGORE George-Eduard & MUȘETESCU Radu-Cristian, 2022. "The Use of GARCH Autoregressive Models in Estimating and Forecasting the Crude Oil Volatility," European Journal of Interdisciplinary Studies, Bucharest Economic Academy, issue 01, March.
    2. Faheem Aslam & Paulo Ferreira & Haider Ali, 2022. "Analysis of the Impact of COVID-19 Pandemic on the Intraday Efficiency of Agricultural Futures Markets," JRFM, MDPI, vol. 15(12), pages 1-18, December.
    3. Zhang, Jiaming & Guo, Songlin & Dou, Bin & Xie, Bingyuan, 2023. "Evidence of the internationalization of China's crude oil futures: Asymmetric linkages to global financial risks," Energy Economics, Elsevier, vol. 127(PA).
    4. Li, Jingyu & Liu, Ranran & Yao, Yanzhen & Xie, Qiwei, 2022. "Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19," Resources Policy, Elsevier, vol. 77(C).
    5. Alexander Koch & Toan Luu Duc Huynh & Mei Wang, 2024. "News sentiment and international equity markets during BREXIT period: A textual and connectedness analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 5-34, January.
    6. Shao Ying-Hui & Liu Ying-Lin & Yang Yan-Hong, 2022. "The short-term effect of COVID-19 pandemic on China's crude oil futures market: A study based on multifractal analysis," Papers 2204.05199, arXiv.org.

    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. Wei, Yu & Zhang, Yaojie & Wang, Yudong, 2022. "Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent," International Review of Financial Analysis, Elsevier, vol. 81(C).
    2. Ederington, Louis H. & Fernando, Chitru S. & Hoelscher, Seth A. & Lee, Thomas K. & Linn, Scott C., 2019. "Characteristics of petroleum product prices: A survey," Journal of Commodity Markets, Elsevier, vol. 14(C), pages 1-15.
    3. Yang, Chen & Lv, Fei & Fang, Libing & Shang, Xingxing, 2020. "The pricing efficiency of crude oil futures in the Shanghai International Exchange," Finance Research Letters, Elsevier, vol. 36(C).
    4. Wang, Tiantian & Wu, Fei & Zhang, Dayong & Ji, Qiang, 2023. "Energy market reforms in China and the time-varying connectedness of domestic and international markets," Energy Economics, Elsevier, vol. 117(C).
    5. Shao, Mingao & Hua, Yongjun, 2022. "Price discovery efficiency of China's crude oil futures: Evidence from the Shanghai crude oil futures market," Energy Economics, Elsevier, vol. 112(C).
    6. Geng, Jiang-Bo & Chen, Fu-Rui & Ji, Qiang & Liu, Bing-Yue, 2021. "Network connectedness between natural gas markets, uncertainty and stock markets," Energy Economics, Elsevier, vol. 95(C).
    7. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    8. Guglielmo Maria Caporale & Davide Ciferri & Alessandro Girardi, 2014. "Time-Varying Spot and Futures Oil Price Dynamics," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(1), pages 78-97, February.
    9. Apostolakis, George N. & Floros, Christos & Gkillas, Konstantinos & Wohar, Mark, 2024. "Volatility spillovers across the spot and futures oil markets after news announcements," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    10. Liang, Chao & Goodell, John W. & Li, Xiafei, 2024. "Impacts of carbon market and climate policy uncertainties on financial and economic stability: Evidence from connectedness network analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    11. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2021. "How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques," Resources Policy, Elsevier, vol. 70(C).
    12. Tangyong Liu & Xu Gong & Boqiang Lin, 2021. "Analyzing the frequency dynamics of volatility spillovers across precious and industrial metal markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1375-1396, September.
    13. Nishimura, Yusaku & Tsutsui, Yoshiro & Hirayama, Kenjiro, 2018. "Do international investors cause stock market spillovers? Comparing responses of cross-listed stocks between accessible and inaccessible markets," Economic Modelling, Elsevier, vol. 69(C), pages 237-248.
    14. Amar, Amine Ben & Goutte, Stéphane & Isleimeyyeh, Mohammad & Benkraiem, Ramzi, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    15. Sun, Qingru & Gao, Xiangyun & An, Haizhong & Guo, Sui & Liu, Xueyong & Wang, Ze, 2021. "Which time-frequency domain dominates spillover in the Chinese energy stock market?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    16. Luo, Keyu & Guo, Qiang & Li, Xiafei, 2022. "Can the return connectedness indices from grey energy to natural gas help to forecast the natural gas returns?," Energy Economics, Elsevier, vol. 109(C).
    17. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    18. Ma, Rufei & Liu, Zhenhua & Zhai, Pengxiang, 2022. "Does economic policy uncertainty drive volatility spillovers in electricity markets: Time and frequency evidence," Energy Economics, Elsevier, vol. 107(C).
    19. 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).
    20. Narayan, Seema & Smyth, Russell, 2015. "The financial econometrics of price discovery and predictability," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 380-393.

    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:wly:ijfiec:v:26:y:2021:i:2:p:2414-2435. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.