IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v85y2023ipas0301420723006360.html
   My bibliography  Save this article

Geopolitical risk on energy, agriculture, livestock, precious and industrial metals: New insights from a Markov Switching model

Author

Listed:
  • Abid, Ilyes
  • Dhaoui, Abderrazak
  • Kaabia, Olfa
  • Tarchella, Salma

Abstract

This paper delineates a novel approach to analyze the dynamic effects of a Geopolitical Risk (GPR) shock on five types of commodities (energy, precious metals, agriculture, industrial metals, and livestock products). Covering a period of 10 years, from 2013 to 2023, we use a Markov-Switching model with two regimes (low and high volatility). The findings indicate that a Markov-Switching model with a t-distribution for the errors is the most suitable to analyze the impact of GPR shocks on commodity markets. All commodities react to a GPR shock but differently. The energy market is the most reactive market and livestock is the less sensitive one. Our results suggest that investors may want to consider the impact of geopolitical risk on different types of commodities before making investment decisions. Market participants should pay attention to changes in the Geopolitical Risk Index during high volatility regimes to better understand the behavior of commodity markets.

Suggested Citation

  • Abid, Ilyes & Dhaoui, Abderrazak & Kaabia, Olfa & Tarchella, Salma, 2023. "Geopolitical risk on energy, agriculture, livestock, precious and industrial metals: New insights from a Markov Switching model," Resources Policy, Elsevier, vol. 85(PA).
    • Handle: RePEc:eee:jrpoli:v:85:y:2023:i:pa:s0301420723006360
    DOI: 10.1016/j.resourpol.2023.103925
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420723006360
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2023.103925?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.

    References listed on IDEAS

    as
    1. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    2. Joëts, Marc & Mignon, Valérie & Razafindrabe, Tovonony, 2017. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 313-326.
    3. Ilyes Abid & Abderrazak Dhaoui & Stéphane Goutte & Khaled Guesmi, 2020. "Hedging and diversification across commodity assets," Applied Economics, Taylor & Francis Journals, vol. 52(23), pages 2472-2492, May.
    4. Ahmadi, Maryam & Bashiri Behmiri, Niaz & Manera, Matteo, 2016. "How is volatility in commodity markets linked to oil price shocks?," Energy Economics, Elsevier, vol. 59(C), pages 11-23.
    5. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
    6. Shahzad, Umer & Mohammed, Kamel Si & Tiwari, Sunil & Nakonieczny, Joanna & Nesterowicz, Renata, 2023. "Connectedness between geopolitical risk, financial instability indices and precious metals markets: Novel findings from Russia Ukraine conflict perspective," Resources Policy, Elsevier, vol. 80(C).
    7. Lutz Kilian & Cheolbeom Park, 2009. "The Impact Of Oil Price Shocks On The U.S. Stock Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(4), pages 1267-1287, November.
    8. Christos Kollias & Stephanos Papadamou & Vangelis Arvanitis, 2013. "Symposium - Does Terrorism Affect the Stock-Bond Covariance? Evidence from European Countries," Southern Economic Journal, John Wiley & Sons, vol. 79(4), pages 832-848, April.
    9. Tarchella, Salma & Dhaoui, Abderrazak, 2021. "Chinese jigsaw: Solving the equity market response to the COVID-19 crisis: Do alternative asset provide effective hedging performance?," Research in International Business and Finance, Elsevier, vol. 58(C).
    10. Ilyes Abid & Abderrazak Dhaoui & Khaled Guesmi & Olfa Kaabia, 2020. "Hedging strategy for financial variables and commodities," Economics Bulletin, AccessEcon, vol. 40(2), pages 1368-1379.
    11. Huang, Chuangxia & Deng, Yunke & Yang, Xiaoguang & Cao, Jinde & Yang, Xin, 2021. "A network perspective of comovement and structural change: Evidence from the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 76(C).
    12. Su, Chi-Wei & Khan, Khalid & Tao, Ran & Nicoleta-Claudia, Moldovan, 2019. "Does geopolitical risk strengthen or depress oil prices and financial liquidity? Evidence from Saudi Arabia," Energy, Elsevier, vol. 187(C).
    13. Hany Abdel-Latif & Mahmoud El-Gamal, 2019. "Antecedents of war: the geopolitics of low oil prices and decelerating financial liquidity," Applied Economics Letters, Taylor & Francis Journals, vol. 26(9), pages 765-769, May.
    14. Bhatia, Vaneet & Das, Debojyoti & Kumar, Surya Bhushan, 2020. "Hedging effectiveness of precious metals across frequencies: Evidence from Wavelet based Dynamic Conditional Correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    15. Salisu, Afees A. & Vo, Xuan Vinh & Lawal, Adedoyin, 2021. "Hedging oil price risk with gold during COVID-19 pandemic," Resources Policy, Elsevier, vol. 70(C).
    16. Cheng, Sheng & Zhang, Zongyou & Cao, Yan, 2022. "Can precious metals hedge geopolitical risk? Fresh sight using wavelet coherence analysis," Resources Policy, Elsevier, vol. 79(C).
    17. Vesco, Paola & Dasgupta, Shouro & De Cian, Enrica & Carraro, Carlo, 2020. "Natural resources and conflict: A meta-analysis of the empirical literature," Ecological Economics, Elsevier, vol. 172(C).
    18. Wang, Yihan & Bouri, Elie & Fareed, Zeeshan & Dai, Yuhui, 2022. "Geopolitical risk and the systemic risk in the commodity markets under the war in Ukraine," Finance Research Letters, Elsevier, vol. 49(C).
    19. Bollerslev, Tim & Zhou, Hao, 2006. "Volatility puzzles: a simple framework for gauging return-volatility regressions," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 123-150.
    20. Wen, Fenghua & Shui, Aojie & Cheng, Yuxiang & Gong, Xu, 2022. "Monetary policy uncertainty and stock returns in G7 and BRICS countries: A quantile-on-quantile approach," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 457-482.
    21. Christos Kollias & Stephanos Papadamou & Vangelis Arvanitis, 2013. "Does Terrorism Affect the Stock‐Bond Covariance? Evidence from European Countries," Southern Economic Journal, John Wiley & Sons, vol. 79(4), pages 832-848, April.
    22. Khusrav Gaibulloev & Todd Sandler, 2008. "Growth Consequences of Terrorism in Western Europe," Kyklos, Wiley Blackwell, vol. 61(3), pages 411-424, August.
    23. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    24. Mehmet Balcilar & Rangan Gupta & Clement Kyei, 2015. "South African Stock Returns Predictability using Domestic and Global Economic Policy Uncertainty: Evidence from a Nonparametric Causality-in-Quantiles Approach," Working Papers 201570, University of Pretoria, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.
    2. Zhang, Bin & Liu, Zuyao & Wang, Zhaohua & Zhang, Shuang, 2023. "The impact of geopolitical risk on energy security: Evidence from a GMM panel VAR approach," Resources Policy, Elsevier, vol. 86(PB).
    3. Polat, Onur & Ertuğrul, Hasan Murat & Sakarya, Burçhan & Akgül, Ali, 2024. "TVP-VAR based time and frequency domain food & energy commodities connectedness an analysis for financial/geopolitical turmoil episodes," Applied Energy, Elsevier, vol. 357(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    3. Li, Houjian & Huang, Xinya & Guo, Lili, 2023. "Extreme risk dependence and time-varying spillover between crude oil, commodity market and inflation in China," Energy Economics, Elsevier, vol. 127(PB).
    4. Juncal Cunado & David Gabauer & Rangan Gupta, 2024. "Realized volatility spillovers between energy and metal markets: a time-varying connectedness approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-17, December.
    5. Ahmed, Abdullahi D. & Huo, Rui, 2021. "Volatility transmissions across international oil market, commodity futures and stock markets: Empirical evidence from China," Energy Economics, Elsevier, vol. 93(C).
    6. Naif Alsagr & Stefan F. Van Hemmen Almazor, 2020. "Oil Rent, Geopolitical Risk and Banking Sector Performance," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 305-314.
    7. Umar, Zaghum & Jareño, Francisco & Escribano, Ana, 2021. "Oil price shocks and the return and volatility spillover between industrial and precious metals," Energy Economics, Elsevier, vol. 99(C).
    8. 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).
    9. Alomari, Mohammad & Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Extreme return spillovers and connectedness between crude oil and precious metals futures markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 79(C).
    10. Ding, Qian & Huang, Jianbai & Zhang, Hongwei, 2021. "The time-varying effects of financial and geopolitical uncertainties on commodity market dynamics: A TVP-SVAR-SV analysis," Resources Policy, Elsevier, vol. 72(C).
    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. Cheng, Sheng & Zhang, Zongyou & Cao, Yan, 2022. "Can precious metals hedge geopolitical risk? Fresh sight using wavelet coherence analysis," Resources Policy, Elsevier, vol. 79(C).
    13. Tarchella, Salma & Dhaoui, Abderrazak, 2021. "Chinese jigsaw: Solving the equity market response to the COVID-19 crisis: Do alternative asset provide effective hedging performance?," Research in International Business and Finance, Elsevier, vol. 58(C).
    14. Soni, Rajat Kumar & Nandan, Tanuj, 2022. "Modeling Covid-19 contagious effect between asset markets and commodity futures in India," Resources Policy, Elsevier, vol. 79(C).
    15. Sun, Guanglin & Li, Jianfeng & Shang, Zezhong, 2022. "Return and volatility linkages between international energy markets and Chinese commodity market," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    16. Shahzad, Umer & Mohammed, Kamel Si & Tiwari, Sunil & Nakonieczny, Joanna & Nesterowicz, Renata, 2023. "Connectedness between geopolitical risk, financial instability indices and precious metals markets: Novel findings from Russia Ukraine conflict perspective," Resources Policy, Elsevier, vol. 80(C).
    17. Bouri, Elie & Gök, Remzi & Gemi̇ci̇, Eray & Kara, Erkan, 2024. "Do geopolitical risk, economic policy uncertainty, and oil implied volatility drive assets across quantiles and time-horizons?," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 137-154.
    18. Li, Sufang & Tu, Dalun & Zeng, Yan & Gong, Chenggang & Yuan, Di, 2022. "Does geopolitical risk matter in crude oil and stock markets? Evidence from disaggregated data," Energy Economics, Elsevier, vol. 113(C).
    19. Nasreen, Samia & Tiwari, Aviral Kumar & Goodell, John W. & Tedeschi, Marco, 2024. "Asymmetric and frequency-domain spillover effects among industrial metals, precious metals, and energy futures markets," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1556-1592.
    20. Yang, Cai & Niu, Zibo & Gao, Wang, 2022. "The time-varying effects of trade policy uncertainty and geopolitical risks shocks on the commodity market prices: Evidence from the TVP-VAR-SV approach," Resources Policy, Elsevier, vol. 76(C).

    More about this item

    Keywords

    Commodity prices; Geopolitical risk; Investors’ sentiment;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

    Statistics

    Access and download statistics

    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:jrpoli:v:85:y:2023:i:pa:s0301420723006360. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.elsevier.com/locate/inca/30467 .

    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.