IDEAS home Printed from https://ideas.repec.org/a/hin/jnddns/1030567.html
   My bibliography  Save this article

Do Volatilities Matter in the Interconnectedness between World Energy Commodities and Stock Markets of BRICS?

Author

Listed:
  • Gilbert K. Amoako
  • Emmanuel Asafo-Adjei
  • Kofi Mintah Oware
  • Anokye M. Adam
  • Stefan Cristian Gherghina

Abstract

Financial markets integration has resulted in high interconnectedness among the BRICS stock markets, which minimizes diversification potentials. This has increased investors’ interest in the financialization of commodities to minimize their portfolio risks. However, the comovements between these assets do not operate in a vacuum, which requires that the role of volatilities be considered in tandem. The purpose of this study is to explore the interdependencies between energy commodities and stock markets of BRICS in the midst of relevant volatilities. For this reason, the wavelet techniques, biwavelet and partial wavelet, are employed. We find that positive comovements between energy commodities and stock markets of BRICS become stronger in the long-term. Furthermore, volatility has a long-term impact on the correlations between energy commodities and the BRICS stock market. We argue that the US Volatility Index, which measures investor anxiety and volatility in stock markets, has the biggest impact on the relationship between energy commodities and BRICS stock markets. Surprisingly, the correlations between energy commodities and Russian stock markets were strong enough to withstand the effects of volatilities. Hence, investors can use volatilities to hedge portfolio risks in energy commodities and stock markets in Brazil, India, China, and South Africa.

Suggested Citation

  • Gilbert K. Amoako & Emmanuel Asafo-Adjei & Kofi Mintah Oware & Anokye M. Adam & Stefan Cristian Gherghina, 2022. "Do Volatilities Matter in the Interconnectedness between World Energy Commodities and Stock Markets of BRICS?," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-13, April.
    • Handle: RePEc:hin:jnddns:1030567
    DOI: 10.1155/2022/1030567
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/ddns/2022/1030567.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/ddns/2022/1030567.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/1030567?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
    ---><---

    Citations

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


    Cited by:

    1. Qi, Haozhi & Ma, Lijun & Peng, Pin & Chen, Hao & Li, Kang, 2022. "Dynamic connectedness between clean energy stock markets and energy commodity markets during times of COVID-19: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    2. Thobekile Qabhobho & Emmanuel Asafo-Adjei & Peterson Owusu Junior & Anokye M. Adam, 2022. "Quantifying information transfer between Commodities and Implied Volatilities in the Energy Markets: A Multi-frequency Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 472-481, September.
    3. Thobekile Qabhobho & Anokye M. Adam & Anthony Adu-Asare Idun & Emmanuel Asafo-Adjei & Ebenezer Boateng, 2023. "Exploring the Time-varying Connectedness and Contagion Effects among Exchange Rates of BRICS, Energy Commodities, and Volatilities," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 272-283, March.
    4. Thobekile Qabhobho, 2023. "Assessing the Asymmetric Effect of Local Realized Exchange Rate Volatility and Implied Volatilities in Energy Market on Exchange Rate Returns in BRICS," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 231-239, March.
    5. Kakade, Kshitij & Jain, Ishan & Mishra, Aswini Kumar, 2022. "Value-at-Risk forecasting: A hybrid ensemble learning GARCH-LSTM based approach," Resources Policy, Elsevier, vol. 78(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:hin:jnddns:1030567. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.