IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v13y2025i4p72-d1629446.html
   My bibliography  Save this article

Can Environmental Variables Predict Cryptocurrency Returns? Evidence from Bitcoin, Ethereum, and Tether Using a Time-Varying Coefficients Vector Autoregression Model

Author

Listed:
  • Kamel Touhami

    (Faculty of Economics and Management of Nabeul, University of Carthage, Tunisia, University Campus Mrezga Route Hammamet, Nabeul 8000, Tunisia
    LIGUE Laboratory, University of Manouba, ISCAE, Manouba University Campus, Manouba 2010, Tunisia)

  • Ilyes Abidi

    (Department of Management Information Systems, Applied College, University of Ha’il, Hail City P.O. Box 2440, Saudi Arabia
    Laboratory of Innovation, Strategy, Entrepreneurship, Finance, and Economics (LISEFE), Faculty of Economic Sciences and Management of Tunis, University of Tunis El Manar, Farhat Hached University Campus of El Manar, P.O. Box 94, Rommana City, Tunis 1068, Tunisia)

  • Mariem Nsaibi

    (Department of Management Information Systems, Applied College, University of Ha’il, Hail City P.O. Box 2440, Saudi Arabia)

  • Maissa Mejri

    (Faculty of Economics and Management of Nabeul, University of Carthage, Tunisia, University Campus Mrezga Route Hammamet, Nabeul 8000, Tunisia)

Abstract

This study investigates the impact of environmental variables, such as carbon emissions and temperature anomalies, on cryptocurrency returns. While existing research has primarily focused on economic and financial determinants, the influence of environmental factors remains underexplored. Using Dynamic Conditional Correlation GARCH (DCC-GARCH) and Time-Varying Coefficients Vector Autoregression (TVC-VAR) models, this study provides empirical evidence that environmental variables significantly affect the volatility and returns of Bitcoin, Ethereum, and Tether. The results show that Bitcoin and Ethereum are highly sensitive to CO 2 emissions and temperature fluctuations, while Tether demonstrates a more moderate response. Moreover, the impact of these environmental factors evolves over time, underscoring their dynamic nature in cryptocurrency valuation. These findings highlight the importance of incorporating environmental variables into forecasting models to enhance risk management and investment strategies. This study contributes to the literature by bridging the gap between environmental concerns and cryptocurrency market behavior, offering valuable insights for investors, regulators, and policymakers.

Suggested Citation

  • Kamel Touhami & Ilyes Abidi & Mariem Nsaibi & Maissa Mejri, 2025. "Can Environmental Variables Predict Cryptocurrency Returns? Evidence from Bitcoin, Ethereum, and Tether Using a Time-Varying Coefficients Vector Autoregression Model," Risks, MDPI, vol. 13(4), pages 1-21, April.
    • Handle: RePEc:gam:jrisks:v:13:y:2025:i:4:p:72-:d:1629446
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/13/4/72/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/13/4/72/
    Download Restriction: no
    ---><---

    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:gam:jrisks:v:13:y:2025:i:4:p:72-:d:1629446. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.