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Modeling the volatility of futures return in rubber and oil—A Copula-based GARCH model approach


  • Li, Meng
  • Yang, Liang


This paper attempts to make use of a Copula-based GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) Model to find out the relationships between the volatility of rubber futures returns in the Agricultural Futures Exchange of Thailand (AFET) and other four main markets, namely, the volatility of rubber futures returns in the Singapore Commodity Exchange (SICOM), the volatility of rubber futures returns, crude oil returns, and gas oil returns in the Tokyo Commodity Exchange (TOCOM). The results illustrate that the Student-t dependence only shows better explanatory power than the Gaussian dependence structure and the persistence pertaining to the dependence structure between rubber futures returns in AFET and oil futures returns, namely, crude oil futures returns and gas oil futures returns in TOCOM. Whereas, the Gaussian dependence shows better explanatory ability between rubber futures returns in AFET and other rubber futures returns, namely, the volatility of rubber futures in SICOM and TOCOM. For the multivariate Copula model, all the parameters between AFET and other variables are significant. Based on these results, with the liberalization of agricultural trade and the withdrawal of government support to agricultural producers, there is in many countries a new need for price discovery and even physical trading mechanisms, a need that can often be met by commodity futures exchanges. Hence, this paper recommends that the government supports the hedge mutual funds that can be invested in every commodities futures exchange in the world. It can also put the funds together that will contribute farmers to invest in each commodities futures market.

Suggested Citation

  • Li, Meng & Yang, Liang, 2013. "Modeling the volatility of futures return in rubber and oil—A Copula-based GARCH model approach," Economic Modelling, Elsevier, vol. 35(C), pages 576-581.
  • Handle: RePEc:eee:ecmode:v:35:y:2013:i:c:p:576-581
    DOI: 10.1016/j.econmod.2013.07.016

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    References listed on IDEAS

    1. Masih, Rumi & Masih, Abul M. M., 2001. "Long and short term dynamic causal transmission amongst international stock markets," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 563-587, August.
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    4. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Panayiotis Theodossiou & Unro Lee, 1993. "Mean And Volatility Spillovers Across Major National Stock Markets: Further Empirical Evidence," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 16(4), pages 337-350, December.
    7. Li, Meng & Yang, Liang, 2012. "Rigid wage-setting and the effect of a supply shock, fiscal and monetary policies on Chinese economy by a CGE analysis," Economic Modelling, Elsevier, vol. 29(5), pages 1858-1869.
    8. 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.
    9. Kearney, Colm, 2000. "The determination and international transmission of stock market volatility," Global Finance Journal, Elsevier, vol. 11(1-2), pages 31-52.
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    Cited by:

    1. Stanisław Wanat & Sławomir Śmiech & Monika Papież, 2016. "In Search Of Hedges And Safe Havens In Global Financial Markets," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 557-574, September.
    2. Arthur Charpentier, 2015. "Prévision avec des copules en finance," Working Papers hal-01151233, HAL.
    3. Wanat, Stanisław & Papież, Monika & Śmiech, Sławomir, 2014. "The conditional dependence structure between precious metals: a copula-GARCH approach," MPRA Paper 56664, University Library of Munich, Germany.
    4. Kentaro Iwatsubo & Clinton Watkins, 2018. "Who Influences the Fundamental Value of Commodity Futures in Japan?," Discussion Papers 1830, Graduate School of Economics, Kobe University.
    5. repec:eee:ecmode:v:64:y:2017:i:c:p:409-418 is not listed on IDEAS


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