IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v29y2024i1p903-926.html
   My bibliography  Save this article

Dynamic connectedness between China's commodity markets and China's sectoral stock markets: A multidimensional analysis

Author

Listed:
  • Liuguo Shao
  • Hua Zhang
  • Senfeng Chang
  • Ziyang Wang

Abstract

Considering the heterogeneity of China's different sectoral stock markets, this paper adopts the time‐domain spillover index model, extreme spillover index model, and frequency‐domain spillover model to analyse the spillover effects of China's commodity and sectoral stock markets under normal conditions, extreme conditions, and frequency‐domain conditions. The empirical results highlight three interesting and noteworthy aspects for investors and regulators: first, the spillover behaviours of China's sectoral stock markets reveal significant heterogeneity. The Energy, Materials, Industries, Optional, Consumption, Information, and PublicUtilities markets are net transmitters, while the Pharmaceutical, Finance, and Telecom ones are net receivers. Second, the spillover effects between China's commodity and sectoral stock markets are enhanced under extreme conditions and are approximately 18.49% higher than those under normal conditions, and there is asymmetry between left‐tail and right‐tail spillovers, which was observed during China's stock market crash. Finally, the spillover effect between China's commodity and sectoral stock markets is dominated by short‐term spillovers, and there is a positive correlation between short‐term and long‐term spillovers.

Suggested Citation

  • Liuguo Shao & Hua Zhang & Senfeng Chang & Ziyang Wang, 2024. "Dynamic connectedness between China's commodity markets and China's sectoral stock markets: A multidimensional analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 903-926, January.
  • Handle: RePEc:wly:ijfiec:v:29:y:2024:i:1:p:903-926
    DOI: 10.1002/ijfe.2713
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.2713
    Download Restriction: no

    File URL: https://libkey.io/10.1002/ijfe.2713?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. 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. 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. Chen, Xian & Li, Yang & Xiao, Jihong & Wen, Fenghua, 2020. "Oil shocks, competition, and corporate investment: Evidence from China," Energy Economics, Elsevier, vol. 89(C).
    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. 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.
    6. Lin, Boqiang & Chen, Yufang, 2019. "Dynamic linkages and spillover effects between CET market, coal market and stock market of new energy companies: A case of Beijing CET market in China," Energy, Elsevier, vol. 172(C), pages 1198-1210.
    7. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan & Plakandaras, Vasilios, 2018. "Dynamic connectedness of uncertainty across developed economies: A time-varying approach," Economics Letters, Elsevier, vol. 166(C), pages 63-75.
    8. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "Time-varying dependence dynamics between international commodity prices and Australian industry stock returns: a Perspective for portfolio diversification," Energy Economics, Elsevier, vol. 108(C).
    9. 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).
    10. Saeed, Tareq & Bouri, Elie & Alsulami, Hamed, 2021. "Extreme return connectedness and its determinants between clean/green and dirty energy investments," Energy Economics, Elsevier, vol. 96(C).
    11. Yonghong Jiang & Jinqi Mu & He Nie & Lanxin Wu, 2022. "Time‐frequency analysis of risk spillovers from oil to BRICS stock markets: A long‐memory Copula‐CoVaR‐MODWT method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3386-3404, July.
    12. Panos Pouliasis & Ioannis Kyriakou & Nikos Papapostolou, 2017. "On equity risk prediction and tail spillovers," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(4), pages 379-393, October.
    13. İrfan Civcir & Uğur Akkoç, 2021. "Dynamic volatility linkages and hedging between commodities and sectoral stock returns in Turkey: Evidence from SVAR‐cDCC‐GARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1978-1992, April.
    14. Tian, Meiyu & Li, Wanyang & Wen, Fenghua, 2021. "The dynamic impact of oil price shocks on the stock market and the USD/RMB exchange rate: Evidence from implied volatility indices," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    15. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    16. Fenghua Wen & Kaiyan Weng & Wei-Xing Zhou, 2020. "Measuring the contribution of Chinese financial institutions to systemic risk: an extended asymmetric CoVaR approach," Risk Management, Palgrave Macmillan, vol. 22(4), pages 310-337, December.
    17. Rehman, Mobeen Ur & Zeitun, Rami & Mardani, Abbas & Vo, Xuan Vinh & Eraslan, Veysel, 2022. "Asymmetric pass through of energy commodities to US sectoral returns," Resources Policy, Elsevier, vol. 76(C).
    18. Elie Bouri & Kakali Kanjilal & Sajal Ghosh & David Roubaud & Tareq Saeed, 2021. "Rare earth and allied sectors in stock markets: extreme dependence of return and volatility," Applied Economics, Taylor & Francis Journals, vol. 53(49), pages 5710-5730, October.
    19. Hassan, Kamrul & Hoque, Ariful & Wali, Muammer & Gasbarro, Dominic, 2020. "Islamic stocks, conventional stocks, and crude oil: Directional volatility spillover analysis in BRICS," Energy Economics, Elsevier, vol. 92(C).
    20. Shao, Liuguo & Zhang, Hua & Chen, Jinyu & Zhu, Xuehong, 2021. "Effect of oil price uncertainty on clean energy metal stocks in China: Evidence from a nonparametric causality-in-quantiles approach," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 407-419.
    21. Ding, Qian & Huang, Jianbai & Chen, Jinyu, 2021. "Dynamic and frequency-domain risk spillovers among oil, gold, and foreign exchange markets: Evidence from implied volatility," Energy Economics, Elsevier, vol. 102(C).
    22. Ji, Qiang & Bouri, Elie & Roubaud, David, 2018. "Dynamic network of implied volatility transmission among US equities, strategic commodities, and BRICS equities," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 1-12.
    23. Zhang, Chuanguo & Mou, Xinjie & Ye, Shuping, 2022. "How do dynamic jumps in global crude oil prices impact China's industrial sector?," Energy, Elsevier, vol. 249(C).
    24. Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    25. 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.
    26. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    27. Shao, Liuguo & Zhang, Hua, 2020. "The impact of oil price on the clean energy metal prices: A multi-scale perspective," Resources Policy, Elsevier, vol. 68(C).
    28. Shahzad, Syed Jawad Hussain & Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie, 2021. "Asymmetric volatility spillover among Chinese sectors during COVID-19," International Review of Financial Analysis, Elsevier, vol. 75(C).
    29. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets," Energy Economics, Elsevier, vol. 98(C).
    30. Zhang, Hua & Chen, Jinyu & Shao, Liuguo, 2021. "Dynamic spillovers between energy and stock markets and their implications in the context of COVID-19," International Review of Financial Analysis, Elsevier, vol. 77(C).
    31. Ji, Qiang & Liu, Bing-Yue & Zhao, Wan-Li & Fan, Ying, 2020. "Modelling dynamic dependence and risk spillover between all oil price shocks and stock market returns in the BRICS," International Review of Financial Analysis, Elsevier, vol. 68(C).
    32. Mensi, Walid & Hernandez, Jose Arroeola & Yoon, Seong-Min & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Spillovers and connectedness between major precious metals and major currency markets: The role of frequency factor," International Review of Financial Analysis, Elsevier, vol. 74(C).
    33. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    34. Chan, Kam C. & Fung, Hung-Gay & Thapa, Samanta, 2007. "China financial research: A review and synthesis," International Review of Economics & Finance, Elsevier, vol. 16(3), pages 416-428.
    35. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    36. Tiwari, Aviral Kumar & Mishra, Bibhuti Ranjan & Solarin, Sakiru Adebola, 2021. "Analysing the spillovers between crude oil prices, stock prices and metal prices: The importance of frequency domain in USA," Energy, Elsevier, vol. 220(C).
    37. 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).
    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. 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).
    2. 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).
    3. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    4. 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.
    5. Asadi, Mehrad & Roudari, Soheil & Tiwari, Aviral Kumar & Roubaud, David, 2023. "Scrutinizing commodity markets by quantile spillovers: A case study of the Australian economy," Energy Economics, Elsevier, vol. 118(C).
    6. Dai, Zhifeng & Zhu, Haoyang & Zhang, Xinhua, 2022. "Dynamic spillover effects and portfolio strategies between crude oil, gold and Chinese stock markets related to new energy vehicle," Energy Economics, Elsevier, vol. 109(C).
    7. Li, Hailing & Li, Yuxin & Zhang, Hua, 2023. "The spillover effects among the traditional energy markets, metal markets and sub-sector clean energy markets," Energy, Elsevier, vol. 275(C).
    8. 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).
    9. 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).
    10. Dai, Zhifeng & Zhu, Haoyang, 2022. "Time-varying spillover effects and investment strategies between WTI crude oil, natural gas and Chinese stock markets related to belt and road initiative," Energy Economics, Elsevier, vol. 108(C).
    11. Mensi, Walid & Vo, Xuan Vinh & Ko, Hee-Un & Kang, Sang Hoon, 2023. "Frequency spillovers between green bonds, global factors and stock market before and during COVID-19 crisis," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 558-580.
    12. 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).
    13. Guangxi Cao & Fei Xie, 2024. "Extreme risk spillovers across energy and carbon markets: Evidence from the quantile extended joint connectedness approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2155-2175, April.
    14. Hu, Yang & Lang, Chunlin & Corbet, Shaen & Hou, Yang (Greg) & Oxley, Les, 2023. "Exploring the dynamic behaviour of commodity market tail risk connectedness during the negative WTI pricing event," Energy Economics, Elsevier, vol. 125(C).
    15. 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).
    16. Song, Huiling & Wang, Chang & Lei, Xiaojie & Zhang, Hongwei, 2022. "Dynamic dependence between main-byproduct metals and the role of clean energy market," Energy Economics, Elsevier, vol. 108(C).
    17. Gong, Xiao-Li & Zhao, Min & Wu, Zhuo-Cheng & Jia, Kai-Wen & Xiong, Xiong, 2023. "Research on tail risk contagion in international energy markets—The quantile time-frequency volatility spillover perspective," Energy Economics, Elsevier, vol. 121(C).
    18. Su, Chi-Wei & Pang, Li-Dong & Qin, Meng & Lobonţ, Oana-Ramona & Umar, Muhammad, 2023. "The spillover effects among fossil fuel, renewables and carbon markets: Evidence under the dual dilemma of climate change and energy crises," Energy, Elsevier, vol. 274(C).
    19. Wei, Yu & Zhang, Jiahao & Bai, Lan & Wang, Yizhi, 2023. "Connectedness among El Niño-Southern Oscillation, carbon emission allowance, crude oil and renewable energy stock markets: Time- and frequency-domain evidence based on TVP-VAR model," Renewable Energy, Elsevier, vol. 202(C), pages 289-309.
    20. Billah, Mabruk & Karim, Sitara & Naeem, Muhammad Abubakr & Vigne, Samuel A., 2022. "Return and volatility spillovers between energy and BRIC markets: Evidence from quantile connectedness," Research in International Business and Finance, Elsevier, vol. 62(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:ijfiec:v:29:y:2024:i:1:p:903-926. 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.