IDEAS home Printed from https://ideas.repec.org/a/eee/riibaf/v89y2026ics0275531926002138.html

Using on-chain data to predict Bitcoin cycles

Author

Listed:
  • Grobys, Klaus
  • Näsman, Sebastian
  • Sandretto, Davide

Abstract

There is limited literature studying the predictive power of on-chain data for Bitcoin price cycles. This paper contributes to this literature by assessing whether three on-chain, trading-based measures help predict the Bitcoin price time series across three major market cycles. We find that these indicators outperform both a buy-and-hold benchmark and random-entry strategies simulated through Monte Carlo analysis. For example, the Sharpe ratio increases from 0.45 for the buy-and-hold benchmark to 1.28 when using the Market Value to Realized Value Z-score measure. This study contributes to the literature by showing that blockchain-based behavioral data provides predictive value in decentralized markets that lack intrinsic valuation anchors. The findings also have practical implications for investors, traders, and regulators, and they challenge traditional notions of market efficiency by providing evidence of recurring behavioral patterns embedded in publicly observable blockchain activity.

Suggested Citation

  • Grobys, Klaus & Näsman, Sebastian & Sandretto, Davide, 2026. "Using on-chain data to predict Bitcoin cycles," Research in International Business and Finance, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:riibaf:v:89:y:2026:i:c:s0275531926002138
    DOI: 10.1016/j.ribaf.2026.103486
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0275531926002138
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ribaf.2026.103486?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

    ;
    ;
    ;
    ;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G40 - Financial Economics - - Behavioral Finance - - - General

    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:89:y:2026:i:c:s0275531926002138. 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.