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Dynamic return and volatility connectedness for dominant agricultural commodity markets during the COVID-19 pandemic era

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  • Zaghum Umar
  • Francisco Jareño
  • Ana Escribano

Abstract

This paper explores the dynamic return and volatility connectedness for the three most relevant agricultural and livestock commodity indexes (Softs, Grains and Livestock) and a media sentiment index as the Coronavirus Media Coverage Index (MCI). To that purpose, we apply the fresh time-varying parameter vector autoregression methodology during the sample period between 1 January 2020 and 30 April 2021, that is, covering the three waves of the COVID-19 pandemic crisis. Interesting results are found in this research. First, dynamic total return and volatility connectedness fluctuate over time, reaching a peak during both the first and the third waves of the global pandemic crisis. Second, in the dynamic connectedness TO the system, we observe significant differences between markets at the level of the return connectedness measure. However, in the dynamic volatility connectedness TO, there are very few differences between some elements of the system. The Coronavirus MCI appears as the less relevant receiver FROM the system, not only in terms of dynamic return connectedness but also in volatility. Finally, regarding the net dynamic total connectedness, the Coronavirus MCI shows the highest values in return and volatility, during most of the sample period analysed.

Suggested Citation

  • Zaghum Umar & Francisco Jareño & Ana Escribano, 2022. "Dynamic return and volatility connectedness for dominant agricultural commodity markets during the COVID-19 pandemic era," Applied Economics, Taylor & Francis Journals, vol. 54(9), pages 1030-1054, February.
  • Handle: RePEc:taf:applec:v:54:y:2022:i:9:p:1030-1054
    DOI: 10.1080/00036846.2021.1973949
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    Citations

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    Cited by:

    1. Celia Sama-Berrocal & Beatriz Corchuelo Martínez-Azúa, 2022. "How Has the COVID-19 Pandemic Affected the Different Branches of the Agri-Food Industry in Extremadura (Spain)?," Land, MDPI, vol. 11(6), pages 1-29, June.
    2. Wang, Suhui, 2023. "Tail dependence, dynamic linkages, and extreme spillover between the stock and China's commodity markets," Journal of Commodity Markets, Elsevier, vol. 29(C).
    3. Chishti, Muhammad Zubair & Khalid, Ali Awais & Sana, Moniba, 2023. "Conflict vs sustainability of global energy, agricultural and metal markets: A lesson from Ukraine-Russia war," Resources Policy, Elsevier, vol. 84(C).
    4. Umar, Zaghum & Mokni, Khaled & Escribano, Ana, 2022. "Connectedness between the COVID-19 related media coverage and Islamic equities: The role of economic policy uncertainty," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    5. Akyildirim, Erdinc & Cepni, Oguzhan & Pham, Linh & Uddin, Gazi Salah, 2022. "How connected is the agricultural commodity market to the news-based investor sentiment?," Energy Economics, Elsevier, vol. 113(C).
    6. Umar, Zaghum & Polat, Onur & Choi, Sun-Yong & Teplova, Tamara, 2022. "Dynamic connectedness between non-fungible tokens, decentralized finance, and conventional financial assets in a time-frequency framework," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    7. Ruano, Fábio & Barros, Victor, 2022. "Commodities and portfolio diversification: Myth or fact?," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 281-295.

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