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Dependence structure between oil and other commodity futures in China based on extreme value theory and copulas

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  • Saiful Izzuan Hussain
  • Steven Li

Abstract

This paper examines the dependence structure between oil futures with other major commodities including gold, copper, zinc, aluminium, rubber, corn, cotton and sugar in China. To this end, we apply the extreme value theory (EVT) and dynamic copula approach, which allows for measuring both average and tail dependence. Contrary to the findings in the literature on stock markets, this paper reveals significant right tail dependence rather than left tail dependence between oil futures and most of the other eight commodities. These findings provide a new insight regarding the behaviour of oil and other major commodities. This paper thus has some significant implications for investors, risk managers and policymakers.

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  • Saiful Izzuan Hussain & Steven Li, 2022. "Dependence structure between oil and other commodity futures in China based on extreme value theory and copulas," The World Economy, Wiley Blackwell, vol. 45(1), pages 317-335, January.
    • Handle: RePEc:bla:worlde:v:45:y:2022:i:1:p:317-335
    DOI: 10.1111/twec.13123
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    References listed on IDEAS

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    1. Saiful Izzuan Hussain & Steven Li, 2018. "The dynamic dependence between stock markets in the greater China economic area: a study based on extreme values and copulas," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(2), pages 207-233, May.
    2. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    3. Bashar, Omar H.M.N. & Wadud, I.K.M. Mokhtarul & Ali Ahmed, Huson Joher, 2013. "Oil price uncertainty, monetary policy and the macroeconomy: The Canadian perspective," Economic Modelling, Elsevier, vol. 35(C), pages 249-259.
    4. Baffes, John, 2007. "Oil spills on other commodities," Resources Policy, Elsevier, vol. 32(3), pages 126-134, September.
    5. Hammoudeh, Shawkat & Dibooglu, Sel & Aleisa, Eisa, 2004. "Relationships among U.S. oil prices and oil industry equity indices," International Review of Economics & Finance, Elsevier, vol. 13(4), pages 427-453.
    6. Hussain, Saiful Izzuan & Li, Steven, 2018. "The dependence structure between Chinese and other major stock markets using extreme values and copulas," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 421-437.
    7. Daskalaki, Charoula & Skiadopoulos, George, 2011. "Should investors include commodities in their portfolios after all? New evidence," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2606-2626, October.
    8. Yang, Ming-Yuan & Li, Sai-Ping & Wu, Yue & Tang, Jingtai & Ren, Fei, 2019. "Do government rescue policies reduce the market volatility after crash? Evidence from the Shanghai stock market," Finance Research Letters, Elsevier, vol. 29(C), pages 117-124.
    9. Paul Embrechts & Sidney Resnick & Gennady Samorodnitsky, 1999. "Extreme Value Theory as a Risk Management Tool," North American Actuarial Journal, Taylor & Francis Journals, vol. 3(2), pages 30-41.
    10. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    11. Fowowe, Babajide, 2016. "Do oil prices drive agricultural commodity prices? Evidence from South Africa," Energy, Elsevier, vol. 104(C), pages 149-157.
    12. Brown, Stephen P. A. & Yucel, Mine K., 2002. "Energy prices and aggregate economic activity: an interpretative survey," The Quarterly Review of Economics and Finance, Elsevier, vol. 42(2), pages 193-208.
    13. Wang, Xiao & Zhang, Chuanguo, 2014. "The impacts of global oil price shocks on China׳s fundamental industries," Energy Policy, Elsevier, vol. 68(C), pages 394-402.
    14. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    15. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    16. Chen, Sheng-Tung & Kuo, Hsiao-I & Chen, Chi-Chung, 2010. "Modeling the relationship between the oil price and global food prices," Applied Energy, Elsevier, vol. 87(8), pages 2517-2525, August.
    17. Zibin Zhang & Luanne Lohr & Cesar Escalante & Michael Wetzstein, 2009. "Ethanol, Corn, and Soybean Price Relations in a Volatile Vehicle-Fuels Market," Energies, MDPI, vol. 2(2), pages 1-20, June.
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    Cited by:

    1. 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).

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