IDEAS home Printed from https://ideas.repec.org/a/taf/eurjfi/v26y2020i12p1207-1237.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1351847X.2020.1724171
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/1351847X.2020.1724171?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.

    Citations

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


    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).

    More about this item

    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:taf:eurjfi:v:26:y:2020:i:12:p:1207-1237. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/REJF20 .

    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.