IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v179y2022ics0040162522001743.html
   My bibliography  Save this article

Return and volatility linkages between international energy markets and Chinese commodity market

Author

Listed:
  • Sun, Guanglin
  • Li, Jianfeng
  • Shang, Zezhong

Abstract

This research investigates the return and volatility linkages between international energy markets and Chinese commodity market at the micro and macro level by employing the Vector Autoregressive combined with BEKK Autoregressive Conditional Heteroskedasticity model (VAR-BEKK-GARCH). Furthermore, this paper also analyzes the changes in return and volatility linkages stepping across the China's exchange rate regime reform in 2015 by splitting the sample into 2 stages: the Pre-reform period (19 June 2010-10 August 2015), and the Post-reform period (11 August 2015-31 December 2021). The empirical results show significant return and volatility spillovers between the international energy markets and China's commodity market, nevertheless, the return spillover effects has been weakened significantly and the vaolatility spillovers have been strengthened significantly after the 2015 China's exchange rate regime reform. The empirical results also provide evidence that the international energy market can effectively hedge the risks of China's commodity market, but the portfolio diversification strategies should be modified across time. Due to the decline in price co-movement, investors have been able to hedge risk in China's commodity market at a lower cost since the reform of the RMB exchange rate system in 2015. However, the efficiency of risk diversification has also declined due to the increased risk linkage between domestic and international markets. In the future, if another reform of the exchange rate system is ought to be initiated, price shocks coming from the external energy markets as well as the risk linkages are all factors needed to be taken into control. Finally, our research also provides a clear way for investors to hedge domestic commodity market risk through international energy markets.

Suggested Citation

  • Sun, Guanglin & Li, Jianfeng & Shang, Zezhong, 2022. "Return and volatility linkages between international energy markets and Chinese commodity market," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    • Handle: RePEc:eee:tefoso:v:179:y:2022:i:c:s0040162522001743
    DOI: 10.1016/j.techfore.2022.121642
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162522001743
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2022.121642?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ahmed, Abdullahi D. & Huo, Rui, 2021. "Volatility transmissions across international oil market, commodity futures and stock markets: Empirical evidence from China," Energy Economics, Elsevier, vol. 93(C).
    2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    3. Christopher L. Gilbert, 2010. "How to Understand High Food Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(2), pages 398-425, June.
    4. Li, Xue & Liu, Yanghui & Li, Hanxu & Li, Jie, 2021. "Onshore spot and offshore forward markets for RMB: Evidence from the “8.11” exchange rate regime reform," China Economic Review, Elsevier, vol. 67(C).
    5. Ahmadi, Maryam & Bashiri Behmiri, Niaz & Manera, Matteo, 2016. "How is volatility in commodity markets linked to oil price shocks?," Energy Economics, Elsevier, vol. 59(C), pages 11-23.
    6. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
    7. Hu, May & Li, Yunfeng & Yang, Jingjing & Chao, Chi-Chur, 2016. "Actual intervention and verbal intervention in the Chinese RMB exchange rate," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 499-508.
    8. Adams, Zeno & Glück, Thorsten, 2015. "Financialization in commodity markets: A passing trend or the new normal?," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 93-111.
    9. 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.
    10. Wan, Li & Han, Liyan & Xu, Yang & Matousek, Roman, 2021. "Dynamic linkage between the Chinese and global stock markets: A normal mixture approach," Emerging Markets Review, Elsevier, vol. 49(C).
    11. Li, Jianfeng & Lu, Xinsheng & Qu, Ling, 2019. "Effectiveness of the RMB exchange rate regime reform: A new perspective from MF-DMA and MF-X-DMA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    12. Li, Jianfeng & Lu, Xinsheng & Zhou, Ying, 2016. "Cross-correlations between crude oil and exchange markets for selected oil rich economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 131-143.
    13. Shahbaz, Muhammad & Zakaria, Muhammad & Shahzad, Syed Jawad Hussain & Mahalik, Mantu Kumar, 2018. "The energy consumption and economic growth nexus in top ten energy-consuming countries: Fresh evidence from using the quantile-on-quantile approach," Energy Economics, Elsevier, vol. 71(C), pages 282-301.
    14. Ben Ameur, Hachmi & Ftiti, Zied & Louhichi, Waël, 2021. "Intraday spillover between commodity markets," Resources Policy, Elsevier, vol. 74(C).
    15. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
    16. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    17. Wan, Xiaoli & Yan, Yuruo & Zeng, Zhixiong, 2020. "Exchange rate regimes and market integration: evidence from the dynamic relations between renminbi onshore and offshore markets," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    18. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    19. 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.
    20. Cui, Jinxin & Goh, Mark & Zou, Huiwen, 2021. "Coherence, extreme risk spillovers, and dynamic linkages between oil and China’s commodity futures markets," Energy, Elsevier, vol. 225(C).
    21. Jiang, Yonghong & Jiang, Cheng & Nie, He & Mo, Bin, 2019. "The time-varying linkages between global oil market and China's commodity sectors: Evidence from DCC-GJR-GARCH analyses," Energy, Elsevier, vol. 166(C), pages 577-586.
    22. Ding, Liang & Vo, Minh, 2012. "Exchange rates and oil prices: A multivariate stochastic volatility analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 15-37.
    23. Fowowe, Babajide, 2016. "Do oil prices drive agricultural commodity prices? Evidence from South Africa," Energy, Elsevier, vol. 104(C), pages 149-157.
    24. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Hedström, Axel, 2018. "Multivariate dependence and spillover effects across energy commodities and diversification potentials of carbon assets," Energy Economics, Elsevier, vol. 71(C), pages 35-46.
    25. Chkir, Imed & Guesmi, Khaled & Brayek, Angham Ben & Naoui, Kamel, 2020. "Modelling the nonlinear relationship between oil prices, stock markets, and exchange rates in oil-exporting and oil-importing countries," Research in International Business and Finance, Elsevier, vol. 54(C).
    26. Yang, Kun & Wei, Yu & Li, Shouwei & He, Jianmin, 2020. "Asymmetric risk spillovers between Shanghai and Hong Kong stock markets under China’s capital account liberalization," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    27. Adekunle, Wasiu & Bagudo, Abubakar M. & Odumosu, Monsuru & Inuolaji, Suraj B., 2020. "Predicting stock returns using crude oil prices: A firm level analysis of Nigeria's oil and gas sector," Resources Policy, Elsevier, vol. 68(C).
    28. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    29. Lin, Boqiang & Xu, Bin, 2019. "How to effectively stabilize China's commodity price fluctuations?," Energy Economics, Elsevier, vol. 84(C).
    30. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    31. Li, Xiafei & Li, Bo & Wei, Guiwu & Bai, Lan & Wei, Yu & Liang, Chao, 2021. "Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US," Resources Policy, Elsevier, vol. 73(C).
    32. Bouri, Elie I, 2014. "Israeli-Hezbollah War and Global Financial Crisis in the Middle East and North African Equity Markets," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 29, pages 1-19.
    33. Wang, Yudong & Guo, Zhuangyue, 2018. "The dynamic spillover between carbon and energy markets: New evidence," Energy, Elsevier, vol. 149(C), pages 24-33.
    34. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    35. 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.
    36. Lu, Xinsheng & Li, Jianfeng & Zhou, Ying & Qian, Yubo, 2017. "Cross-correlations between RMB exchange rate and international commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 168-182.
    37. Adams, Zeno & Glueck, Thorsten, 2014. "Financialization in Commodity Markets: A Passing Trend or the New Normal?," Working Papers on Finance 1413, University of St. Gallen, School of Finance, revised Aug 2015.
    38. Salisu, Afees A. & Mobolaji, Hakeem, 2013. "Modeling returns and volatility transmission between oil price and US–Nigeria exchange rate," Energy Economics, Elsevier, vol. 39(C), pages 169-176.
    39. Hasanov, Akram Shavkatovich & Do, Hung Xuan & Shaiban, Mohammed Sharaf, 2016. "Fossil fuel price uncertainty and feedstock edible oil prices: Evidence from MGARCH-M and VIRF analysis," Energy Economics, Elsevier, vol. 57(C), pages 16-27.
    40. Mensi, Walid & Tiwari, Aviral & Bouri, Elie & Roubaud, David & Al-Yahyaee, Khamis H., 2017. "The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indexes," Energy Economics, Elsevier, vol. 66(C), pages 122-139.
    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. 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).

    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. Meng, Juan & Nie, He & Mo, Bin & Jiang, Yonghong, 2020. "Risk spillover effects from global crude oil market to China’s commodity sectors," Energy, Elsevier, vol. 202(C).
    2. Cui, Jinxin & Maghyereh, Aktham & Goh, Mark & Zou, Huiwen, 2022. "Risk spillovers and time-varying links between international oil and China’s commodity futures markets: Fresh evidence from the higher-order moments," Energy, Elsevier, vol. 238(PB).
    3. Maitra, Debasish & Guhathakurta, Kousik & Kang, Sang Hoon, 2021. "The good, the bad and the ugly relation between oil and commodities: An analysis of asymmetric volatility connectedness and portfolio implications," Energy Economics, Elsevier, vol. 94(C).
    4. Guhathakurta, Kousik & Dash, Saumya Ranjan & Maitra, Debasish, 2020. "Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications," Energy Economics, Elsevier, vol. 85(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).
    6. Zhu, Huiming & Chen, Weiyan & Hau, Liya & Chen, Qitong, 2021. "Time-frequency connectedness of crude oil, economic policy uncertainty and Chinese commodity markets: Evidence from rolling window analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    7. Cheng, Natalie Fang Ling & Hasanov, Akram Shavkatovich & Poon, Wai Ching & Bouri, Elie, 2023. "The US-China trade war and the volatility linkages between energy and agricultural commodities," Energy Economics, Elsevier, vol. 120(C).
    8. Albulescu, Claudiu Tiberiu & Tiwari, Aviral Kumar & Ji, Qiang, 2020. "Copula-based local dependence among energy, agriculture and metal commodities markets," Energy, Elsevier, vol. 202(C).
    9. Claudiu Albulescu & Aviral Tiwari & Qiang Ji, 2020. "Copula-based local dependence between energy, agriculture and metal commodity markets," Papers 2003.04007, arXiv.org.
    10. Cui, Jinxin & Goh, Mark & Zou, Huiwen, 2021. "Coherence, extreme risk spillovers, and dynamic linkages between oil and China’s commodity futures markets," Energy, Elsevier, vol. 225(C).
    11. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    12. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
    13. Raza, Syed Ali & Guesmi, Khaled & Belaid, Fateh & Shah, Nida, 2022. "Time-frequency causality and connectedness between oil price shocks and the world food prices," Research in International Business and Finance, Elsevier, vol. 62(C).
    14. Soni, Rajat Kumar & Nandan, Tanuj, 2022. "Modeling Covid-19 contagious effect between asset markets and commodity futures in India," Resources Policy, Elsevier, vol. 79(C).
    15. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    16. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    17. Hau, Liya & Zhu, Huiming & Huang, Rui & Ma, Xiang, 2020. "Heterogeneous dependence between crude oil price volatility and China’s agriculture commodity futures: Evidence from quantile-on-quantile regression," Energy, Elsevier, vol. 213(C).
    18. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Nguyen, Duc Khuong, 2020. "Dynamic volatility spillover effects between oil and agricultural products," International Review of Financial Analysis, Elsevier, vol. 69(C).
    19. Vellachami, Sanggetha & Hasanov, Akram Shavkatovich & Brooks, Robert, 2023. "Risk transmission from the energy markets to the carbon market: Evidence from the recursive window approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
    20. Yang, Baochen & Pu, Yingjian & Su, Yunpeng, 2020. "The financialization of Chinese commodity markets," Finance Research Letters, Elsevier, vol. 34(C).

    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:eee:tefoso:v:179:y:2022:i:c:s0040162522001743. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.