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Vines climbing higher: Risk management for commodity futures markets using a regular vine copula approach

Author

Listed:
  • Hemei Li
  • Zhenya Liu

    (CERGAM - Centre d'Études et de Recherche en Gestion d'Aix-Marseille - AMU - Aix Marseille Université - UTLN - Université de Toulon)

  • Shixuan Wang

Abstract

The volume of trading activity relating to China's commodity futures has grown rapidly over the course of the last decade. To improve risk management in China's commodity futures markets, this paper employs a regular vine (R‐vine) copula model to study the dependence structure of commodity futures and to enhance Value‐at‐Risk (VaR) forecast. In doing so, we find that China's commodity futures market is not centred on one category of commodity futures and the tail dependence between different categories of commodity futures varies significantly. Based on the dependence structure analysed using the R‐vine copula model, we forecast the VaR of individual indices, which are formed of several commodity futures, as well as forecasting the VaR of an equally‐weighted portfolio. Our method can outperform the standard GARCH‐VaR method in terms of VaR backtesting. The tool developed within this study will enable those involved in commodity futures markets to improve their risk management.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Hemei Li & Zhenya Liu & Shixuan Wang, 2020. "Vines climbing higher: Risk management for commodity futures markets using a regular vine copula approach," Post-Print hal-03513413, HAL.
  • Handle: RePEc:hal:journl:hal-03513413
    DOI: 10.1002/ijfe.2280
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    Cited by:

    1. Yao, Yinhong & Chen, Xiuwen & Chen, Zhensong, 2025. "Portfolio tail risk forecasting for international financial assets: A GARCH-MIDAS-R-Vine copula model," The North American Journal of Economics and Finance, Elsevier, vol. 77(C).
    2. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    3. Han, Xuyuan & Liu, Zhenya & Wang, Shixuan, 2022. "An R-vine copula analysis of non-ferrous metal futures with application in Value-at-Risk forecasting," Journal of Commodity Markets, Elsevier, vol. 25(C).
    4. Lazar, Emese & Pan, Jingqi & Wang, Shixuan, 2024. "On the estimation of Value-at-Risk and Expected Shortfall at extreme levels," Journal of Commodity Markets, Elsevier, vol. 34(C).
    5. Jain, Prachi & Maitra, Debasish, 2023. "Risk implications of dependence in the commodities: A copula-based analysis," Global Finance Journal, Elsevier, vol. 57(C).

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