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Financial Contagion of the Commodity Markets from the Stock Market during Pandemic and New Sanctions Shocks

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  • Marina Yu. Malkina

Abstract

In the context of financial globalization, there is an increasing transmission of global turbulence between different markets, which enhances overall financial instability. The purpose of this study is to identify the financial contagion of the commodity market from the stock market in the 1920s. The research hypothesis is that contagion manifested itself during the period of pandemic shocks of 2020-2021 and new sanctions shocks of 2022-2023. Based on 2016-2023 data on the intersessional average daily return of the S&P GLOBAL 100 index and 22 commodity futures, DCC GARCH models are built. Significant increases in these correlations during periods of external shocks indicate potential contagion. A dynamic Student's t-test for the equality of correlations in the pre-shock period and in the sliding window within the shock and inter-shock periods is used to definitively prove the presence or absence of contagion. The study confirmed the contagion of 22 commodity markets from the stock market of varying strength and duration, both during the pandemic and new sanctions shocks. It proved that the metals market, especially the gold market, was the most susceptible to contagion during the period under review. Copper and zinc turned out to be risk dampers during the period of new sanctions. Among food products, the sugar market has demonstrated the greatest propensity to contagion, but during a period of relative stability it has proven its ability to mitigate systemic risks. A number of agricultural commodities (e.g., soybeans and soybean products, corn, wheat), as well as Brent oil, have shown relative resistance to contagion and are recommended as hedging tools. The results and conclusions of the study can be useful to investors in managing optimal portfolios, and to the state when adjusting anti-crisis financial policy during the period of external shocks affecting the economy.

Suggested Citation

  • Marina Yu. Malkina, 2024. "Financial Contagion of the Commodity Markets from the Stock Market during Pandemic and New Sanctions Shocks," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 23(2), pages 452-475.
  • Handle: RePEc:aiy:jnjaer:v:23:y:2024:i:2:p:452-475
    DOI: https://doi.org/10.15826/vestnik.2024.23.2.018
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    as
    1. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2021. "Time-varying general dynamic factor models and the measurement of financial connectedness," Journal of Econometrics, Elsevier, vol. 222(1), pages 324-343.
    2. Renée Fry-McKibbin & Cody Yu-Ling Hsiao, 2018. "Extremal dependence tests for contagion," Econometric Reviews, Taylor & Francis Journals, vol. 37(6), pages 626-649, July.
    3. Ayadi, Ahmed & Gana, Marjène & Goutte, Stéphane & Guesmi, Khaled, 2021. "Equity-commodity contagion during four recent crises: Evidence from the USA, Europe and the BRICS," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 376-423.
    4. Mishra, Aswini Kumar & Ghate, Kshitish, 2022. "Dynamic connectedness in non-ferrous commodity markets: Evidence from India using TVP-VAR and DCC-GARCH approaches," Resources Policy, Elsevier, vol. 76(C).
    5. Bei, Zeyun & Lin, Juan & Zhou, Yinggang, 2024. "No safe haven, only diversification and contagion — Intraday evidence around the COVID-19 pandemic," Journal of International Money and Finance, Elsevier, vol. 143(C).
    6. Fry-McKibbin, Renée & Greenwood-Nimmo, Matthew & Hsiao, Cody Yu-Ling & Qi, Lin, 2022. "Higher-order comoment contagion among G20 equity markets during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    7. Wang, Xinya & Liu, Huifang & Huang, Shupei & Lucey, Brian, 2019. "Identifying the multiscale financial contagion in precious metal markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 209-219.
    8. Ben Salem, Leila & Zayati, Montassar & Nouira, Ridha & Rault, Christophe, 2024. "Volatility spillover between oil prices and main exchange rates: Evidence from a DCC-GARCH-connectedness approach," Resources Policy, Elsevier, vol. 91(C).
    9. He, Zhipeng & Zhang, Shuguang, 2024. "Risk contagion and diversification among sovereign CDS, stock, foreign exchange and commodity markets: Fresh evidence from G7 and BRICS countries," Finance Research Letters, Elsevier, vol. 62(PB).
    10. Akhtaruzzaman, Md & Boubaker, Sabri & Goodell, John W., 2023. "Did the collapse of Silicon Valley Bank catalyze financial contagion?," Finance Research Letters, Elsevier, vol. 56(C).
    11. Guidolin, Massimo & Pedio, Manuela, 2017. "Identifying and measuring the contagion channels at work in the European financial crises," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 117-134.
    12. Chiang, Thomas C. & Jeon, Bang Nam & Li, Huimin, 2007. "Dynamic correlation analysis of financial contagion: Evidence from Asian markets," Journal of International Money and Finance, Elsevier, vol. 26(7), pages 1206-1228, November.
    13. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).
    14. Si Mohammed, Kamel & Tedeschi, Marco & Mallek, Sabrine & Tarczyńska-Łuniewska, Małgorzata & Zhang, Anqi, 2023. "Realized semi variance quantile connectedness between oil prices and stock market: Spillover from Russian-Ukraine clash," Resources Policy, Elsevier, vol. 85(PA).
    15. Roy, Rudra Prosad & Sinha Roy, Saikat, 2017. "Financial contagion and volatility spillover: An exploration into Indian commodity derivative market," Economic Modelling, Elsevier, vol. 67(C), pages 368-380.
    16. Chen, Yufeng & Xu, Jing & Miao, Jiafeng, 2023. "Dynamic volatility contagion across the Baltic dry index, iron ore price and crude oil price under the COVID-19: A copula-VAR-BEKK-GARCH-X approach," Resources Policy, Elsevier, vol. 81(C).
    17. Syllignakis, Manolis N. & Kouretas, Georgios P., 2011. "Dynamic correlation analysis of financial contagion: Evidence from the Central and Eastern European markets," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 717-732, October.
    18. Kayani, Umar Nawaz & Hassan, M. Kabir & Moussa, Faten & Hossain, Gazi Farid, 2023. "Oil in crisis: What can we learn," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    19. Grillini, Stefano & Ozkan, Aydin & Sharma, Abhijit, 2022. "Static and dynamic liquidity spillovers in the Eurozone: The role of financial contagion and the Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 83(C).
    20. Hemche, Omar & Jawadi, Fredj & Maliki, Samir B. & Cheffou, Abdoulkarim Idi, 2016. "On the study of contagion in the context of the subprime crisis: A dynamic conditional correlation–multivariate GARCH approach," Economic Modelling, Elsevier, vol. 52(PA), pages 292-299.
    21. Ozcelebi, Oguzhan & Kang, Sang Hoon, 2024. "Extreme connectedness and network across financial assets and commodity futures markets," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    22. Mejri, Sami & Aloui, Chaker & Khan, Nasir, 2024. "The gold stock nexus: Assessing the causality dynamics based on advanced multiscale approaches," Resources Policy, Elsevier, vol. 88(C).
    23. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
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    More about this item

    Keywords

    cross-market contagion effects; commodity futures; S&P GLOBAL 100 index; DCC GARCH model; COVID-19 pandemic; sanctions.;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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