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Extreme downside risk co-movement in commodity markets during distress periods: a multidimensional scaling approach

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  • Gema Fernández-Avilés
  • José-María Montero
  • Lidia Sanchis-Marco

Abstract

We analyze the co-movement of a number of commodity markets in extreme financial episodes worldwide. More specifically, we provide extreme downside risk co-movement maps of these markets during six recent distress periods. We follow an expected shortfall-multidimensional scaling approach, which allows for an easy classification of markets according to their dynamics in risky episodes. No clear risk co-movement patterns are observed, nor spillover effects are detected. Financialization and speculation might have played some role in the dynamics of price and risk only in food commodity markets during the oil price increase 2007–2008.

Suggested Citation

  • Gema Fernández-Avilés & José-María Montero & Lidia Sanchis-Marco, 2020. "Extreme downside risk co-movement in commodity markets during distress periods: a multidimensional scaling approach," The European Journal of Finance, Taylor & Francis Journals, vol. 26(12), pages 1207-1237, August.
    • Handle: RePEc:taf:eurjfi:v:26:y:2020:i:12:p:1207-1237
    DOI: 10.1080/1351847X.2020.1724171
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    Cited by:

    1. Chun-Xiao Nie, 2021. "Studying the correlation structure based on market geometry," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 411-441, April.
    2. María Nieves López-García & Miguel Angel Sánchez-Granero & Juan Evangelista Trinidad-Segovia & Antonio Manuel Puertas & Francisco Javier De las Nieves, 2021. "Volatility Co-Movement in Stock Markets," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    3. Wadud, Sania & Gronwald, Marc & Durand, Robert B. & Lee, Seungho, 2023. "Co-movement between commodity and equity markets revisited—An application of the Thick Pen method," International Review of Financial Analysis, Elsevier, vol. 87(C).
    4. 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.
    5. Dejan Živkov & Marijana Joksimović & Suzana Balaban, 2021. "Measuring parametric and semiparametric downside risks of selected agricultural commodities," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(8), pages 305-315.
    6. Dejan Živkov & Jasmina Đurašković & Marina Gajić‐Glamočlija, 2022. "Multiscale downside risk interdependence between the major agricultural commodities," Agribusiness, John Wiley & Sons, Ltd., vol. 38(4), pages 990-1011, October.
    7. Celina Löwen & Bilal Kchouri & Thorsten Lehnert, 2021. "Is this time really different? Flight-to-safety and the COVID-19 crisis," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-17, May.
    8. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
    9. Chen, James Ming & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Clustering commodity markets in space and time: Clarifying returns, volatility, and trading regimes through unsupervised machine learning," Resources Policy, Elsevier, vol. 73(C).
    10. Dejan Živkov & Boris Kuzman & Jonel Subić, 2023. "Multi-frequency downside risk interconnectedness between soft agricultural commodities," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(8), pages 332-342.
    11. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2022. "Spillover effects between commodity and stock markets: A SDSES approach," Resources Policy, Elsevier, vol. 79(C).
    12. Cui, Jinxin & Maghyereh, Aktham, 2023. "Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," International Review of Financial Analysis, Elsevier, vol. 86(C).

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