IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v44y2024i5p699-719.html
   My bibliography  Save this article

The time‐varying volatility spillover effects between China's coal and metal market

Author

Listed:
  • Boqiang Lin
  • Tianxu Lan

Abstract

This study employs a time‐varying parameter vector autoregression methodology with the Diebold and Yilmaz spillover index to scrutinize the temporal fluctuations in volatility spillovers between the Chinese coal and metal markets. The analysis is conducted from the dual perspectives of security indices and futures prices. The findings reveal a robust correlation between the coal and metal markets, with the coal market serving as a primary conduit for volatility spillover into the metal market. Furthermore, this study investigates the time‐specific impacts of coal decommissioning policies, the COVID‐19 pandemic, and the coal supply crisis on the coal–metal market volatility spillovers. The findings indicate that these three unique shocks significantly increase the overall risk spillover index between the coal and metal markets. Moreover, during these exceptional events, the extent or role of risk spillover in the coal–metal market undergoes varying degrees of change. On the basis of these findings, this article presents pertinent policy recommendations.

Suggested Citation

  • Boqiang Lin & Tianxu Lan, 2024. "The time‐varying volatility spillover effects between China's coal and metal market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(5), pages 699-719, May.
  • Handle: RePEc:wly:jfutmk:v:44:y:2024:i:5:p:699-719
    DOI: 10.1002/fut.22488
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.22488
    Download Restriction: no

    File URL: https://libkey.io/10.1002/fut.22488?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. Lee, Chi-Chuan & Lee, Chien-Chiang, 2019. "Oil price shocks and Chinese banking performance: Do country risks matter?," Energy Economics, Elsevier, vol. 77(C), pages 46-53.
    2. 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.
    3. He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
    4. 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.
    5. Sun, Chuanwang & Min, Jialin & Sun, Jiacheng & Gong, Xu, 2023. "The role of China's crude oil futures in world oil futures market and China's financial market," Energy Economics, Elsevier, vol. 120(C).
    6. Pierre L. Siklos & Martin Stefan & Claudia Wellenreuther, 2020. "Metal prices made in China? A network analysis of industrial metal futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1354-1374, September.
    7. Mhd Ruslan, Siti Marsila & Mokhtar, Kasypi, 2021. "Stock market volatility on shipping stock prices: GARCH models approach," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    8. Madina Khudaykulova & He Yuanqiong & Akmal Khudaykulov, 2022. "Economic Consequences and Implications of the Ukraine-Russia War," International Journal of Management Science and Business Administration, Inovatus Services Ltd., vol. 8(4), pages 44-52, May.
    9. Klaus Adam & Albert Marcet & Johannes Beutel, 2017. "Stock Price Booms and Expected Capital Gains," American Economic Review, American Economic Association, vol. 107(8), pages 2352-2408, August.
    10. Zheng, Biao & Zhang, Yuquan & Chen, Yufeng, 2021. "Asymmetric connectedness and dynamic spillovers between renewable energy and rare earth markets in China: Evidence from firms’ high-frequency data," Resources Policy, Elsevier, vol. 71(C).
    11. Huang, Jianbai & Dong, Xuesong & Chen, Jinyu & Zhong, Meirui, 2022. "Do oil prices and economic policy uncertainty matter for precious metal returns? New insights from a TVP-VAR framework," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 433-445.
    12. Wen, Fenghua & Cao, Jiahui & Liu, Zhen & Wang, Xiong, 2021. "Dynamic volatility spillovers and investment strategies between the Chinese stock market and commodity markets," International Review of Financial Analysis, Elsevier, vol. 76(C).
    13. Adam, Klaus & Matveev, Dmitry & Nagel, Stefan, 2021. "Do survey expectations of stock returns reflect risk adjustments?," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 723-740.
    14. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Risk spillovers and diversification between oil and non-ferrous metals during bear and bull market states," Resources Policy, Elsevier, vol. 72(C).
    15. Zhang, Yanfang & Shi, Xunpeng & Qian, Xiangyan & Chen, Sai & Nie, Rui, 2021. "Macroeconomic effect of energy transition to carbon neutrality: Evidence from China's coal capacity cut policy," Energy Policy, Elsevier, vol. 155(C).
    16. Chris Brooks & Marcel Prokopczuk, 2013. "The dynamics of commodity prices," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 527-542, March.
    17. Gogolin, Fabian & Kearney, Fearghal & Lucey, Brian M. & Peat, Maurice & Vigne, Samuel A., 2018. "Uncovering long term relationships between oil prices and the economy: A time-varying cointegration analysis," Energy Economics, Elsevier, vol. 76(C), pages 584-593.
    18. Li, Jianglong & Xie, Chunping & Long, Houyin, 2019. "The roles of inter-fuel substitution and inter-market contagion in driving energy prices: evidences from China’s coal market," LSE Research Online Documents on Economics 102540, London School of Economics and Political Science, LSE Library.
    19. Fan, Xinghua & Wang, Li & Li, Shasha, 2016. "Predicting chaotic coal prices using a multi-layer perceptron network model," Resources Policy, Elsevier, vol. 50(C), pages 86-92.
    20. Wei, Yu & Bai, Lan & Li, Xiafei, 2022. "Normal and extreme interactions among nonferrous metal futures: A new quantile-frequency connectedness approach," Finance Research Letters, Elsevier, vol. 47(PB).
    21. Husain, Shaiara & Tiwari, Aviral Kumar & Sohag, Kazi & Shahbaz, Muhammad, 2019. "Connectedness among crude oil prices, stock index and metal prices: An application of network approach in the USA," Resources Policy, Elsevier, vol. 62(C), pages 57-65.
    22. Sensoy, Ahmet & Hacihasanoglu, Erk & Nguyen, Duc Khuong, 2015. "Dynamic convergence of commodity futures: Not all types of commodities are alike," Resources Policy, Elsevier, vol. 44(C), pages 150-160.
    23. Su, Xianfang, 2020. "Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    24. Zhang, Dayong & Broadstock, David C., 2020. "Global financial crisis and rising connectedness in the international commodity markets," International Review of Financial Analysis, Elsevier, vol. 68(C).
    25. Liu, Feng & Zhang, Chuanguo & Tang, Mengying, 2021. "The impacts of oil price shocks and jumps on China's nonferrous metal markets," Resources Policy, Elsevier, vol. 73(C).
    26. Zhang, Chuanguo & Tu, Xiaohua, 2016. "The effect of global oil price shocks on China's metal markets," Energy Policy, Elsevier, vol. 90(C), pages 131-139.
    27. 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.
    28. Bouri, Elie & Lei, Xiaojie & Xu, Yahua & Zhang, Hongwei, 2023. "Connectedness in implied higher-order moments of precious metals and energy markets," Energy, Elsevier, vol. 263(PB).
    29. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    30. Ma, Feng & Liao, Yin & Zhang, Yaojie & Cao, Yang, 2019. "Harnessing jump component for crude oil volatility forecasting in the presence of extreme shocks," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 40-55.
    31. Duan, Xiaoping & Xiao, Ya & Ren, Xiaohang & Taghizadeh-Hesary, Farhad & Duan, Kun, 2023. "Dynamic spillover between traditional energy markets and emerging green markets: Implications for sustainable development," Resources Policy, Elsevier, vol. 82(C).
    32. 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.
    33. Olivier J. Blanchard & Jordi Gali, 2007. "The Macroeconomic Effects of Oil Shocks: Why are the 2000s So Different from the 1970s?," NBER Working Papers 13368, National Bureau of Economic Research, Inc.
    34. Kilian, Lutz & Rebucci, Alessandro & Spatafora, Nikola, 2009. "Oil shocks and external balances," Journal of International Economics, Elsevier, vol. 77(2), pages 181-194, April.
    35. Ivan Indriawan & Qingfu Liu & Yiuman Tse, 2019. "Market quality and the connectedness of steel rebar and other industrial metal futures in China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(11), pages 1383-1393, November.
    36. 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).
    37. Yahya, Muhammad & Ghosh, Sajal & Kanjilal, Kakali & Dutta, Anupam & Uddin, Gazi Salah, 2020. "Evaluation of cross-quantile dependence and causality between non-ferrous metals and clean energy indexes," Energy, Elsevier, vol. 202(C).
    38. repec:bla:jfinan:v:59:y:2004:i:3:p:1367-1404 is not listed on IDEAS
    39. Saleh Alodayni, 2016. "Oil Prices, Credit Risks in Banking Systems, and Macro-Financial Linkages across GCC Oil Exporters," IJFS, MDPI, vol. 4(4), pages 1-14, November.
    40. Hammoudeh, Shawkat & Yuan, Yuan, 2008. "Metal volatility in presence of oil and interest rate shocks," Energy Economics, Elsevier, vol. 30(2), pages 606-620, March.
    41. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    42. Kostrzewski, Maciej & Kostrzewska, Jadwiga, 2019. "Probabilistic electricity price forecasting with Bayesian stochastic volatility models," Energy Economics, Elsevier, vol. 80(C), pages 610-620.
    43. Mishra, Aswini Kumar & Arunachalam, Vairam & Olson, Dennis & Patnaik, Debasis, 2023. "Dynamic connectedness in commodity futures markets during Covid-19 in India: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 82(C).
    44. 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.
    45. Aguilera, Roberto F. & Radetzki, Marian, 2017. "The synchronized and exceptional price performance of oil and gold: Explanations and prospects," Resources Policy, Elsevier, vol. 54(C), pages 81-87.
    46. Li, Jianglong & Xie, Chunping & Long, Houyin, 2019. "The roles of inter-fuel substitution and inter-market contagion in driving energy prices: Evidences from China’s coal market," Energy Economics, Elsevier, vol. 84(C).
    47. Chang, Lei & Mohsin, Muhammad & Gao, Zhennan & Taghizadeh-Hesary, Farhad, 2023. "Asymmetric impact of oil price on current account balance: Evidence from oil importing countries," Energy Economics, Elsevier, vol. 123(C).
    48. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    49. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
    50. Steven Kou & Cindy Yu & Haowen Zhong, 2017. "Jumps in Equity Index Returns Before and During the Recent Financial Crisis: A Bayesian Analysis," Management Science, INFORMS, vol. 63(4), pages 988-1010, April.
    51. Chen, Jinyu & Liang, Zhipeng & Ding, Qian & Liu, Zhenhua, 2022. "Extreme spillovers among fossil energy, clean energy, and metals markets: Evidence from a quantile-based analysis," Energy Economics, Elsevier, vol. 107(C).
    52. Mokni, Khaled & Hammoudeh, Shawkat & Ajmi, Ahdi Noomen & Youssef, Manel, 2020. "Does economic policy uncertainty drive the dynamic connectedness between oil price shocks and gold price?," Resources Policy, Elsevier, vol. 69(C).
    53. Qin, Yun & Hong, Kairong & Chen, Jinyu & Zhang, Zitao, 2020. "Asymmetric effects of geopolitical risks on energy returns and volatility under different market conditions," Energy Economics, Elsevier, vol. 90(C).
    Full references (including those not matched with items on IDEAS)

    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. 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).
    2. Chen, Jinyu & Liang, Zhipeng & Ding, Qian & Liu, Zhenhua, 2022. "Extreme spillovers among fossil energy, clean energy, and metals markets: Evidence from a quantile-based analysis," Energy Economics, Elsevier, vol. 107(C).
    3. Chen, Jinyu & Liang, Zhipeng & Ding, Qian & Liu, Zhenhua, 2022. "Quantile connectedness between energy, metal, and carbon markets," International Review of Financial Analysis, Elsevier, vol. 83(C).
    4. Gong, Xu & Xu, Jun & Liu, Tangyong & Zhou, Zicheng, 2022. "Dynamic volatility connectedness between industrial metal markets," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    5. Cagli, Efe Caglar, 2023. "The volatility spillover between battery metals and future mobility stocks: Evidence from the time-varying frequency connectedness approach," Resources Policy, Elsevier, vol. 86(PA).
    6. Zhou, Xiaoran & Enilov, Martin & Parhi, Mamata, 2024. "Does oil spin the commodity wheel? Quantile connectedness with a common factor error structure across energy and agricultural markets," Energy Economics, Elsevier, vol. 132(C).
    7. Sun, Chuanwang & Min, Jialin & Sun, Jiacheng & Gong, Xu, 2023. "The role of China's crude oil futures in world oil futures market and China's financial market," Energy Economics, Elsevier, vol. 120(C).
    8. Dai, Zhifeng & Zhu, Haoyang, 2023. "Dynamic risk spillover among crude oil, economic policy uncertainty and Chinese financial sectors," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 421-450.
    9. Mishra, Aswini Kumar & Ghate, Kshitish, 2022. "Dynamic connectedness in non-ferrous commodity markets: Evidence from India using TVP-VAR and DCC-GARCH approaches," Resources Policy, Elsevier, vol. 76(C).
    10. Zhang, Jiahao & Zhang, Yifeng & Wei, Yu & Wang, Zhuo, 2024. "Normal and extreme impact and connectedness between fossil energy futures markets and uncertainties: Does El Niño-Southern Oscillation matter?," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 188-215.
    11. Chen, Ying & Zhu, Xuehong & Chen, Jinyu, 2022. "Spillovers and hedging effectiveness of non-ferrous metals and sub-sectoral clean energy stocks in time and frequency domain," Energy Economics, Elsevier, vol. 111(C).
    12. Jiang, Wei & Chen, Yunfei, 2022. "The time-frequency connectedness among metal, energy and carbon markets pre and during COVID-19 outbreak," Resources Policy, Elsevier, vol. 77(C).
    13. 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).
    14. Zhou, Mei-Jing & Huang, Jian-Bai & Chen, Jin-Yu, 2022. "Time and frequency spillovers between political risk and the stock returns of China's rare earths," Resources Policy, Elsevier, vol. 75(C).
    15. Alomari, Mohammad & Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Extreme return spillovers and connectedness between crude oil and precious metals futures markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 79(C).
    16. Umar, Zaghum & Nasreen, Samia & Solarin, Sakiru Adebola & Tiwari, Aviral Kumar, 2019. "Exploring the time and frequency domain connectedness of oil prices and metal prices," Resources Policy, Elsevier, vol. 64(C).
    17. Mokni, Khaled & Al-Shboul, Mohammed & Assaf, Ata, 2021. "Economic policy uncertainty and dynamic spillover among precious metals under market conditions: Does COVID-19 have any effects?," Resources Policy, Elsevier, vol. 74(C).
    18. 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).
    19. Zhongzheng, Wang, 2023. "Extreme risk transmission mechanism between oil, green bonds and new energy vehicles," Innovation and Green Development, Elsevier, vol. 2(3).
    20. Dai, Zhifeng & Zhang, Xiaotong & Yin, Zhujia, 2023. "Extreme time-varying spillovers between high carbon emission stocks, green bond and crude oil: Evidence from a quantile-based analysis," Energy Economics, Elsevier, vol. 118(C).

    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:jfutmk:v:44:y:2024:i:5:p:699-719. 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/0270-7314/ .

    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.