IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v674y2025ics0378437125004042.html
   My bibliography  Save this article

Exploring cryptocurrency price dynamics and predictability with ordinal networks

Author

Listed:
  • Masoudi, Oday
  • Mazzoccoli, Alessandro
  • Vellucci, Pierluigi

Abstract

Ordinal networks represent an innovative and versatile approach for time series analysis, enabling the transformation of data sequences into complex networks based on the relative order of values. This method provides a fresh perspective on uncovering the internal structure of the data, allowing the identification of recurring patterns and predictability dynamics. In our study, we employ ordinal networks and permutation entropy to analyze the predictability and evolving dynamics of four cryptocurrencies: Bitcoin, Ethereum, Litecoin, and Dogecoin. By leveraging this methodology, we investigate the temporal relationships and ordinal transitions that characterize the price fluctuations and volatility of each cryptocurrency, offering deeper insights into their dynamic complexity and predictive potential in cryptocurrency markets.

Suggested Citation

  • Masoudi, Oday & Mazzoccoli, Alessandro & Vellucci, Pierluigi, 2025. "Exploring cryptocurrency price dynamics and predictability with ordinal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 674(C).
  • Handle: RePEc:eee:phsmap:v:674:y:2025:i:c:s0378437125004042
    DOI: 10.1016/j.physa.2025.130752
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437125004042
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2025.130752?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:phsmap:v:674:y:2025:i:c:s0378437125004042. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.