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Investigating the impact of geopolitical risks on the commodity futures

Author

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  • Sokratis Mitsas
  • Petros Golitsis
  • Khurshid Khudoykulov

Abstract

This paper examines the effect of real-time global geopolitical risks (GPRs), acts (GPAs), and threats (GPTs) indices on monthly returns and volatility of several American commodity futures. By modeling volatility via an Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH), we provide evidence that GPRs and GPTs do not only impact but trigger adverse effects on the returns of crude oil, gold, platinum, and silver, while GPAs negatively affect the returns of crude oil, heating oil, platinum, and sugar futures. Furthermore, GPTs have a weak positive effect on corn futures volatility. Overall, our findings provide portfolio diversification benefits by showing how the impact of global GPRs, GPAs and GPTs on portfolio returns could be mitigated.

Suggested Citation

  • Sokratis Mitsas & Petros Golitsis & Khurshid Khudoykulov, 2022. "Investigating the impact of geopolitical risks on the commodity futures," Cogent Economics & Finance, Taylor & Francis Journals, vol. 10(1), pages 2049477-204, December.
  • Handle: RePEc:taf:oaefxx:v:10:y:2022:i:1:p:2049477
    DOI: 10.1080/23322039.2022.2049477
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    Citations

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    Cited by:

    1. Cui, Jinxin & Maghyereh, Aktham, 2024. "Unveiling interconnectedness: Exploring higher-order moments among energy, precious metals, industrial metals, and agricultural commodities in the context of geopolitical risks and systemic stress," Journal of Commodity Markets, Elsevier, vol. 33(C).
    2. Naeem, Muhammad Abubakr & Hamouda, Foued & Karim, Sitara & Vigne, Samuel A., 2023. "Return and volatility spillovers among global assets: Comparing health crisis with geopolitical crisis," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 557-575.
    3. Foglia, Matteo & Palomba, Giulio & Tedeschi, Marco, 2023. "Disentangling the geopolitical risk and its effects on commodities. Evidence from a panel of G8 countries," Resources Policy, Elsevier, vol. 85(PB).
    4. Tin Hei Alpha Yuen & Wai Kee Thomas Yuen, 2022. "Relationship Between Geopolitical Risk In Major Oil Producing Countries and Oil Price," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 117-123, September.
    5. Golitsis, Petros & Gkasis, Pavlos & Bellos, Sotirios K., 2022. "Dynamic spillovers and linkages between gold, crude oil, S&P 500, and other economic and financial variables. Evidence from the USA," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    6. Aloui, Donia & Benkraiem, Ramzi & Guesmi, Khaled & Mzoughi, Hela, 2023. "Managing natural resource prices in a geopolitical risk environment," Resources Policy, Elsevier, vol. 83(C).
    7. Ghaemi Asl, Mahdi & Ben Jabeur, Sami, 2024. "Could the Russia-Ukraine war stir up the persistent memory of interconnectivity among Islamic equity markets, energy commodities, and environmental factors?," Research in International Business and Finance, Elsevier, vol. 69(C).
    8. Jana, Rabin K. & Ghosh, Indranil, 2023. "Time-varying relationship between geopolitical uncertainty and agricultural investment," Finance Research Letters, Elsevier, vol. 52(C).
    9. Kristína Hudecová & Miroslava Rajčániová, 2023. "The impact of geopolitical risk on agricultural commodity prices," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(4), pages 129-139.
    10. Madina Khudaykulova & He Yuanqiong & Akmal Khudaykulov, 2022. "Economic Consequences and Implications of the Ukraine-Russia War," International Journal of Management Science and Business Administration, Inovatus Services Ltd., vol. 8(4), pages 44-52, May.
    11. Zhao, Jing, 2023. "Time-varying impact of geopolitical risk on natural resources prices: Evidence from the hybrid TVP-VAR model with large system," Resources Policy, Elsevier, vol. 82(C).
    12. Evrim Mandaci, Pınar & Azimli, Asil & Mandaci, Nazif, 2023. "The impact of geopolitical risks on connectedness among natural resource commodities: A quantile vector autoregressive approach," Resources Policy, Elsevier, vol. 85(PA).

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