IDEAS home Printed from https://ideas.repec.org/a/eee/riibaf/v69y2024ics0275531924000667.html
   My bibliography  Save this article

Asymmetric dynamics between geopolitical conflict sentiment and cryptomarkets

Author

Listed:
  • Abakah, Emmanuel Joel Aikins
  • Abdullah, Mohammad
  • Tiwari, Aviral Kumar
  • Wali Ullah, G M

Abstract

This study investigates the influence of Russia-Ukraine war and associated economic sanctions sentiments on the returns of cryptocurrencies, NFTs, and DeFi assets. We analyse daily returns of twelve blockchain-based assets by employing quantile-on-quantile regression (QQR) and an asymmetric time-varying parameter vector autoregression (TVP-VAR) connectedness approach. The QQR reveals that the war sentiment has varying effects on the returns of digital assets, with negative (positive) impacts in bullish (bearish) markets. Notably, there is a heterogeneous effect observed in normal market conditions. Results from the TVP-VAR-based asymmetric connectedness approach demonstrate a time-varying influence of war sentiment, particularly heightened post-invasion. The war sentiment emerges as a significant transmitter (receiver) of price shocks in bullish (bearish) market conditions. These findings offer extensive implications for investors and policymakers when modelling market behavior during geopolitical events.

Suggested Citation

  • Abakah, Emmanuel Joel Aikins & Abdullah, Mohammad & Tiwari, Aviral Kumar & Wali Ullah, G M, 2024. "Asymmetric dynamics between geopolitical conflict sentiment and cryptomarkets," Research in International Business and Finance, Elsevier, vol. 69(C).
    • Handle: RePEc:eee:riibaf:v:69:y:2024:i:c:s0275531924000667
    DOI: 10.1016/j.ribaf.2024.102273
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0275531924000667
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ribaf.2024.102273?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

    Cryptocurrency; NFTs; DeFi; Quantile-on-quantile regression; Asymmetric connectedness; Russia-Ukraine war; Sentiment;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General
    • F51 - International Economics - - International Relations, National Security, and International Political Economy - - - International Conflicts; Negotiations; Sanctions

    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:riibaf:v:69:y:2024:i:c:s0275531924000667. 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/ribaf .

    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.