IDEAS home Printed from https://ideas.repec.org/a/eee/quaeco/v101y2025ics1062976925000183.html
   My bibliography  Save this article

Dynamics of asymmetric connectedness among magnificent seven technology giants: Insights from QVAR analysis

Author

Listed:
  • Umar, Zaghum
  • Hadad, Elroi
  • Phiri, Andrew
  • Teplova, Tamara

Abstract

This paper studies the return and volatility spillover among the seven largest technology companies (including Apple, Microsoft, Amazon, Alphabet (Google), Meta Platforms (formerly Facebook), Tesla, and Nvidia) referred to as Magnificent seven. We employ a quantile connected approach to study spillover and connectedness under different market conditions. We observe a high degree of interconnectedness in the returns of these firms, with equities transitioning between roles as net receivers and transmitters across various market conditions. Notably, the influence of market size is apparent, with larger-cap firms predominantly acting as net transmitters, while smaller-cap counterparts serve as net receivers. We also identify asymmetry between quantiles, particularly evident in left tails, underscoring the significance of idiosyncratic shocks. Our findings have important implications for policy makers, investors and regulators.

Suggested Citation

  • Umar, Zaghum & Hadad, Elroi & Phiri, Andrew & Teplova, Tamara, 2025. "Dynamics of asymmetric connectedness among magnificent seven technology giants: Insights from QVAR analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 101(C).
    • Handle: RePEc:eee:quaeco:v:101:y:2025:i:c:s1062976925000183
    DOI: 10.1016/j.qref.2025.101977
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062976925000183
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.qref.2025.101977?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.

    More about this item

    Keywords

    Technology; Artificial Intelligence; Magnificent Seven; Quantile connectedness;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:eee:quaeco:v:101:y:2025:i:c:s1062976925000183. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620167 .

    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.