IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v182y2019icp999-1012.html
   My bibliography  Save this article

The dependence structure between crude oil futures prices and Chinese agricultural commodity futures prices: Measurement based on Markov-switching GRG copula

Author

Listed:
  • Liu, Xiang-dong
  • Pan, Fei
  • Yuan, Lin
  • Chen, Yu-wang

Abstract

The relational measurement based on Markov-switching GRG copula constructed by this paper is harnessed to analyze the dependence structure between WTI (BRENT) crude oil futures price and 12 kinds of Chinese agricultural commodity futures prices. The empirical results show that there exist two structural states of Markov switching between the futures prices of different agricultural commodities and crude oil futures price. The two states have different duration periods, and the degree of correlation with crude oil futures prices varies under different agricultural commodity futures prices. Among all the 12 kinds of agricultural commodity futures, 11 kinds of agricultural commodity futures prices mainly present positive correlations with crude oil futures prices, although the positive correlation differs between non-extreme and extreme conditions. The remaining agricultural commodity futures price is not related to crude oil futures prices.

Suggested Citation

  • Liu, Xiang-dong & Pan, Fei & Yuan, Lin & Chen, Yu-wang, 2019. "The dependence structure between crude oil futures prices and Chinese agricultural commodity futures prices: Measurement based on Markov-switching GRG copula," Energy, Elsevier, vol. 182(C), pages 999-1012.
    • Handle: RePEc:eee:energy:v:182:y:2019:i:c:p:999-1012
    DOI: 10.1016/j.energy.2019.06.071
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219312022
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.06.071?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Waseem Khan & Vishal Sharma & Saghir Ahmad Ansari, 2022. "Modeling the dynamics of oil and agricultural commodity price nexus in linear and nonlinear frameworks: A case of emerging economy," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1733-1784, August.
    2. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "COVID-19 and stock returns: Evidence from the Markov switching dependence approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    3. Albulescu, Claudiu Tiberiu & Tiwari, Aviral Kumar & Ji, Qiang, 2020. "Copula-based local dependence among energy, agriculture and metal commodities markets," Energy, Elsevier, vol. 202(C).
    4. Claudiu Albulescu & Aviral Tiwari & Qiang Ji, 2020. "Copula-based local dependence between energy, agriculture and metal commodity markets," Papers 2003.04007, arXiv.org.
    5. Tiwari, Aviral Kumar & Boachie, Micheal Kofi & Suleman, Muhammed Tahir & Gupta, Rangan, 2021. "Structure dependence between oil and agricultural commodities returns: The role of geopolitical risks," Energy, Elsevier, vol. 219(C).
    6. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
    7. Agus Widarjono & Indah Susantun & Sarastri M. Ruchba & Ari Rudatin, 2020. "Oil and Food Prices for a Net Oil Importing-country: How Are Related in Indonesia?," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 255-263.
    8. Liu, Xiang-dong & Pan, Fei & Cai, Wen-li & Peng, Rui, 2020. "Correlation and risk measurement modeling: A Markov-switching mixed Clayton copula approach," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    9. Wang, Yu-Min & Lin, Che-Chun & Tsai, I-Chun, 2023. "State transformation of information spillover in asset markets and effective dynamic hedging strategies," International Review of Financial Analysis, Elsevier, vol. 89(C).
    10. 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).
    11. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    12. Yang, Dong-Xiao & Wu, Bi-Bo & Tong, Jing-Yang, 2021. "Dynamics and causality of oil price shocks on commodities: Quantile-on-quantile and causality-in-quantiles methods," Resources Policy, Elsevier, vol. 74(C).
    13. Feng, Yun & Yang, Jie & Huang, Qian, 2023. "Multiscale correlation analysis of Sino-US corn futures markets and the impact of international crude oil price: A new perspective from the multifractal method," Finance Research Letters, Elsevier, vol. 53(C).
    14. Wei Jiang & Ruijie Gao & Chao Lu, 2022. "The Analysis of Causality and Risk Spillover between Crude Oil and China’s Agricultural Futures," IJERPH, MDPI, vol. 19(17), pages 1-16, August.
    15. Dai, Peng-Fei & Xiong, Xiong & Zhang, Jin & Zhou, Wei-Xing, 2022. "The role of global economic policy uncertainty in predicting crude oil futures volatility: Evidence from a two-factor GARCH-MIDAS model," Resources Policy, Elsevier, vol. 78(C).
    16. Wang, Kai-Hua & Kan, Jia-Min & Qiu, Lianhong & Xu, Shulin, 2023. "Climate policy uncertainty, oil price and agricultural commodity: From quantile and time perspective," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 256-272.
    17. Aye, Goodness C. & Odhiambo, Nicholas M., 2021. "Oil prices and agricultural growth in South Africa: A threshold analysis," Resources Policy, Elsevier, vol. 73(C).
    18. Mishra, Aswini Kumar & Arunachalam, Vairam & Olson, Dennis & Patnaik, Debasis, 2023. "Dynamic connectedness in commodity futures markets during Covid-19 in India: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 82(C).
    19. Wang, Jianli & Qiu, Shushu & Yick, Ho Yin, 2022. "The influence of the Shanghai crude oil futures on the global and domestic oil markets," Energy, Elsevier, vol. 245(C).
    20. Liu, Siyao & Fang, Wei & Gao, Xiangyun & Wang, Ze & An, Feng & Wen, Shaobo, 2020. "Self-similar behaviors in the crude oil market," Energy, Elsevier, vol. 211(C).
    21. Hau, Liya & Zhu, Huiming & Huang, Rui & Ma, Xiang, 2020. "Heterogeneous dependence between crude oil price volatility and China’s agriculture commodity futures: Evidence from quantile-on-quantile regression," Energy, Elsevier, vol. 213(C).
    22. 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).

    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:energy:v:182:y:2019:i:c:p:999-1012. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.journals.elsevier.com/energy .

    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.