IDEAS home Printed from https://ideas.repec.org/a/eee/jocoma/v29y2023ics2405851323000028.html
   My bibliography  Save this article

Tail dependence, dynamic linkages, and extreme spillover between the stock and China's commodity markets

Author

Listed:
  • Wang, Suhui

Abstract

Cross-market linkage and spillover effects under extreme risk scenarios have recently attracted widespread attention from scholars. However, few studies have focused on tail dependence and extreme spillovers between the stock and the Chinese commodity markets. For the first time, this paper investigates the tail dependence, dynamic linkages, and extreme return spillovers between the stock market and China's commodity markets, employing the novel quantile coherency, DCC-FIGARCH model, and quantile connectedness approach. The empirical results demonstrate that chemical commodities and non-ferrous metals exhibit relatively stronger linkages with the US and Chinese stock markets. Lower return quantiles of the stock markets exhibit higher coherency with the lower return quantiles of Chinese commodity markets in the long-term time horizon. The quantile coherency in the long-term (yearly) is higher than that in the middle (monthly) and short-term (weekly) time horizons. The dynamic linkages and return spillovers change over time and are vulnerable to major crises, particularly during the COVID-19 pandemic. The return spillovers at the extreme lower quantile are stronger than the spillovers at the extreme upper and median quantiles. Chemical commodity and non-ferrous metal sectors (grain commodity and noble metal sectors) are the two key net transmitters (recipients) of the return spillovers. The Chinese and US stock markets mainly act as the net recipients of the extreme spillovers.

Suggested Citation

  • Wang, Suhui, 2023. "Tail dependence, dynamic linkages, and extreme spillover between the stock and China's commodity markets," Journal of Commodity Markets, Elsevier, vol. 29(C).
  • Handle: RePEc:eee:jocoma:v:29:y:2023:i:c:s2405851323000028
    DOI: 10.1016/j.jcomm.2023.100312
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2405851323000028
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jcomm.2023.100312?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. Maghyereh, Aktham & Abdoh, Hussein, 2020. "Tail dependence between Bitcoin and financial assets: Evidence from a quantile cross-spectral approach," International Review of Financial Analysis, Elsevier, vol. 71(C).
    3. 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.
    4. Tiwari, Aviral Kumar & Trabelsi, Nader & Alqahtani, Faisal & Bachmeier, Lance, 2019. "Modelling systemic risk and dependence structure between the prices of crude oil and exchange rates in BRICS economies: Evidence using quantile coherency and NGCoVaR approaches," Energy Economics, Elsevier, vol. 81(C), pages 1011-1028.
    5. Mensi, Walid & Hammoudeh, Shawkat & Al-Jarrah, Idries Mohammad Wanas & Sensoy, Ahmet & Kang, Sang Hoon, 2017. "Dynamic risk spillovers between gold, oil prices and conventional, sustainability and Islamic equity aggregates and sectors with portfolio implications," Energy Economics, Elsevier, vol. 67(C), pages 454-475.
    6. Mensi, Walid & Hammoudeh, Shawkat & Al-Jarrah, Idries Mohammad Wanas & Al-Yahyaee, Khamis Hamed & Kang, Sang Hoon, 2019. "Risk spillovers and hedging effectiveness between major commodities, and Islamic and conventional GCC banks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 60(C), pages 68-88.
    7. Guo, Yanhong & Li, Ping & Li, Aihua, 2021. "Tail risk contagion between international financial markets during COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 73(C).
    8. 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).
    9. Bekiros, Stelios & Boubaker, Sabri & Nguyen, Duc Khuong & Uddin, Gazi Salah, 2017. "Black swan events and safe havens: The role of gold in globally integrated emerging markets," Journal of International Money and Finance, Elsevier, vol. 73(PB), pages 317-334.
    10. Mensi, Walid & Beljid, Makram & Boubaker, Adel & Managi, Shunsuke, 2013. "Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold," Economic Modelling, Elsevier, vol. 32(C), pages 15-22.
    11. 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).
    12. Liu, Xiaoxing & Shehzad, Khurram & Kocak, Emrah & Zaman, Umer, 2022. "Dynamic correlations and portfolio implications across stock and commodity markets before and during the COVID-19 era: A key role of gold," Resources Policy, Elsevier, vol. 79(C).
    13. Robinson, P.M. & Henry, M., 1999. "Long And Short Memory Conditional Heteroskedasticity In Estimating The Memory Parameter Of Levels," Econometric Theory, Cambridge University Press, vol. 15(3), pages 299-336, June.
    14. Maghyereh, Aktham & Abdoh, Hussein, 2021. "Time–frequency quantile dependence between Bitcoin and global equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    15. 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).
    16. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    17. Mensi, Walid & Yousaf, Imran & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillover and network connectedness between gold, BRENT oil and EU subsector markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    18. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2020. "Extreme spillovers across Asian-Pacific currencies: A quantile-based analysis," International Review of Financial Analysis, Elsevier, vol. 72(C).
    19. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Shahbaz, Muhammad, 2017. "Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 258-279.
    20. Suleyman Basak & Anna Pavlova, 2016. "A Model of Financialization of Commodities," Journal of Finance, American Finance Association, vol. 71(4), pages 1511-1556, August.
    21. Maghyereh, Aktham & Abdoh, Hussein, 2021. "Tail dependence between gold and Islamic securities," Finance Research Letters, Elsevier, vol. 38(C).
    22. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 119-129.
    23. Wen, Danyan & Wang, Yudong, 2021. "Volatility linkages between stock and commodity markets revisited: Industry perspective and portfolio implications," Resources Policy, Elsevier, vol. 74(C).
    24. Maghyereh, Aktham & Abdoh, Hussein, 2021. "The impact of extreme structural oil-price shocks on clean energy and oil stocks," Energy, Elsevier, vol. 225(C).
    25. 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).
    26. Tiwari, Aviral Kumar & Trabelsi, Nader & Alqahtani, Faisal & Hammoudeh, Shawkat, 2019. "Analysing systemic risk and time-frequency quantile dependence between crude oil prices and BRICS equity markets indices: A new look," Energy Economics, Elsevier, vol. 83(C), pages 445-466.
    27. 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).
    28. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2022. "Spillover effects between commodity and stock markets: A SDSES approach," Resources Policy, Elsevier, vol. 79(C).
    29. Maghyereh, Aktham & Abdoh, Hussein, 2020. "The tail dependence structure between investor sentiment and commodity markets," Resources Policy, Elsevier, vol. 68(C).
    30. Chen, Peng & He, Limin & Yang, Xuan, 2021. "On interdependence structure of China's commodity market," Resources Policy, Elsevier, vol. 74(C).
    31. Sadorsky, Perry, 2014. "Modeling volatility and correlations between emerging market stock prices and the prices of copper, oil and wheat," Energy Economics, Elsevier, vol. 43(C), pages 72-81.
    32. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    33. Mensi, Walid & Aslan, Aylin & Vo, Xuan Vinh & Kang, Sang Hoon, 2023. "Time-frequency spillovers and connectedness between precious metals, oil futures and financial markets: Hedge and safe haven implications," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 219-232.
    34. 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).
    35. 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.
    36. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    37. John Geweke & Susan Porter‐Hudak, 1983. "The Estimation And Application Of Long Memory Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 221-238, July.
    38. Sang Hoon Kang & Seong‐Min Yoon, 2020. "Dynamic correlation and volatility spillovers across Chinese stock and commodity futures markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(2), pages 261-273, April.
    39. Khalfaoui, Rabeh & Tiwari, Aviral Kumar & Kablan, Sandrine & Hammoudeh, Shawkat, 2021. "Interdependence and lead-lag relationships between the oil price and metal markets: Fresh insights from the wavelet and quantile coherency approaches," Energy Economics, Elsevier, vol. 101(C).
    40. Wu, Bi-Bo, 2021. "The dynamics of oil on China’s commodity sectors: What can we learn from a quantile perspective?," Journal of Commodity Markets, Elsevier, vol. 23(C).
    41. Shahzad, Syed Jawad Hussain & Hernandez, Jose Arreola & Al-Yahyaee, Khamis Hamed & Jammazi, Rania, 2018. "Asymmetric risk spillovers between oil and agricultural commodities," Energy Policy, Elsevier, vol. 118(C), pages 182-198.
    42. Jiang, Yonghong & Lie, Jiayi & Wang, Jieru & Mu, Jinqi, 2021. "Revisiting the roles of cryptocurrencies in stock markets: A quantile coherency perspective," Economic Modelling, Elsevier, vol. 95(C), pages 21-34.
    43. 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).
    44. Wen, Fenghua & Liu, Zhen & Dai, Zhifeng & He, Shaoyi & Liu, Wenhua, 2022. "Multi-scale risk contagion among international oil market, Chinese commodity market and Chinese stock market: A MODWT-Vine quantile regression approach," Energy Economics, Elsevier, vol. 109(C).
    45. Lin, Boqiang & Su, Tong, 2021. "Does COVID-19 open a Pandora's box of changing the connectedness in energy commodities?," Research in International Business and Finance, Elsevier, vol. 56(C).
    46. Hung, Ngo Thai, 2021. "Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Resources Policy, Elsevier, vol. 73(C).
    47. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    48. Dutta, Anupam & Bouri, Elie & Noor, Md Hasib, 2021. "Climate bond, stock, gold, and oil markets: Dynamic correlations and hedging analyses during the COVID-19 outbreak," Resources Policy, Elsevier, vol. 74(C).
    49. 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.
    50. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    51. Akkoc, Ugur & Civcir, Irfan, 2019. "Dynamic linkages between strategic commodities and stock market in Turkey: Evidence from SVAR-DCC-GARCH model," Resources Policy, Elsevier, vol. 62(C), pages 231-239.
    52. Lin, Boqiang & Xu, Bin, 2019. "How to effectively stabilize China's commodity price fluctuations?," Energy Economics, Elsevier, vol. 84(C).
    53. Niu, Hongli & Hu, Ziang, 2021. "Information transmission and entropy-based network between Chinese stock market and commodity futures market," Resources Policy, Elsevier, vol. 74(C).
    54. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Adewuyi, Adeolu O. & Lee, Chien-Chiang, 2022. "Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Energy Economics, Elsevier, vol. 113(C).
    55. Li, Wenqi, 2021. "COVID-19 and asymmetric volatility spillovers across global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    56. Jiang, Kunliang & Ye, Wuyi, 2022. "Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?," Economic Modelling, Elsevier, vol. 117(C).
    57. repec:ipg:wpaper:2014-561 is not listed on IDEAS
    58. Zaghum Umar & Francisco Jareño & Ana Escribano, 2022. "Dynamic return and volatility connectedness for dominant agricultural commodity markets during the COVID-19 pandemic era," Applied Economics, Taylor & Francis Journals, vol. 54(9), pages 1030-1054, February.
    59. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Reboredo, Juan Carlos & Wen, Xiaoqian, 2014. "Dependence of stock and commodity futures markets in China: Implications for portfolio investment," Emerging Markets Review, Elsevier, vol. 21(C), pages 183-200.
    60. Kang, Sang Hoon & Yoon, Seong-Min, 2019. "Financial crises and dynamic spillovers among Chinese stock and commodity futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    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. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    2. Qian, Chenqi & Zhang, Tianding & Li, Jie, 2023. "The impact of international commodity price shocks on macroeconomic fundamentals: Evidence from the US and China," Resources Policy, Elsevier, vol. 85(PB).

    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 & 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).
    2. 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).
    3. 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).
    4. Chen, Hao & Xu, Chao & Peng, Yun, 2022. "Time-frequency connectedness between energy and nonenergy commodity markets during COVID-19: Evidence from China," Resources Policy, Elsevier, vol. 78(C).
    5. Wang, Zi-Xin & Liu, Bing-Yue & Fan, Ying, 2023. "Network connectedness between China's crude oil futures and sector stock indices," Energy Economics, Elsevier, vol. 125(C).
    6. Dai, Zhifeng & Zhu, Junxin & Zhang, Xinhua, 2022. "Time-frequency connectedness and cross-quantile dependence between crude oil, Chinese commodity market, stock market and investor sentiment," Energy Economics, Elsevier, vol. 114(C).
    7. 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).
    8. Khalfaoui, Rabeh & Shahzad, Umer & Ghaemi Asl, Mahdi & Ben Jabeur, Sami, 2023. "Investigating the spillovers between energy, food, and agricultural commodity markets: New insights from the quantile coherency approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 63-80.
    9. 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).
    10. Zhenghui Li & Zhiming Ao & Bin Mo, 2021. "Revisiting the Valuable Roles of Global Financial Assets for International Stock Markets: Quantile Coherence and Causality-in-Quantiles Approaches," Mathematics, MDPI, vol. 9(15), pages 1-18, July.
    11. Rehman, Mobeen Ur & Vo, Xuan Vinh & Ko, Hee-Un & Ahmad, Nasir & Kang, Sang Hoon, 2023. "Quantile connectedness between Chinese stock and commodity futures markets," Research in International Business and Finance, Elsevier, vol. 64(C).
    12. Qi, Haozhi & Ma, Lijun & Peng, Pin & Chen, Hao & Li, Kang, 2022. "Dynamic connectedness between clean energy stock markets and energy commodity markets during times of COVID-19: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    13. Qi, Haozhi & Wu, Tiantian & Chen, Hao & Lu, Xiuling, 2023. "Time-frequency connectedness and cross-quantile dependence between carbon emission trading and commodity markets: Evidence from China," Resources Policy, Elsevier, vol. 82(C).
    14. 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).
    15. 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).
    16. Shahzad, Umer & Ghaemi Asl, Mahdi & Tedeschi, Marco, 2023. "Is there any market state-dependent contribution from Blockchain-enabled solutions to ESG investments? Evidence from conventional and Islamic ESG stocks," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 139-154.
    17. Zhang, Hongwei & Jin, Chen & Bouri, Elie & Gao, Wang & Xu, Yahua, 2023. "Realized higher-order moments spillovers between commodity and stock markets: Evidence from China," Journal of Commodity Markets, Elsevier, vol. 30(C).
    18. Farid, Saqib & Naeem, Muhammad Abubakr & Paltrinieri, Andrea & Nepal, Rabindra, 2022. "Impact of COVID-19 on the quantile connectedness between energy, metals and agriculture commodities," Energy Economics, Elsevier, vol. 109(C).
    19. Guannan Wang & Juan Meng & Bin Mo, 2023. "Dynamic Volatility Spillover Effects and Portfolio Strategies among Crude Oil, Gold, and Chinese Electricity Companies," Mathematics, MDPI, vol. 11(4), pages 1-25, February.
    20. 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.

    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:jocoma:v:29:y:2023:i:c:s2405851323000028. 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.elsevier.com/locate/jcomm .

    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.