IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v74y2025ics1544612324017124.html
   My bibliography  Save this article

Multifractality and sample size influence on Bitcoin volatility patterns

Author

Listed:
  • Takaishi, Tetsuya

Abstract

The finite sample effect on the Hurst exponent (HE) of realized volatility time series is examined using Bitcoin data. This study finds that the HE decreases as the sampling period Δ increases and a simple finite sample ansatz closely fits the HE data. We obtain HE values of Δ→0, which is smaller than 1/2, indicating rough volatility. The relative error is found to be 1% for the widely used five-minute realized volatility. Performing a multifractal analysis, we find that multifractality in the realized volatility time series is smaller than that of the price-return time series.

Suggested Citation

  • Takaishi, Tetsuya, 2025. "Multifractality and sample size influence on Bitcoin volatility patterns," Finance Research Letters, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:finlet:v:74:y:2025:i:c:s1544612324017124
    DOI: 10.1016/j.frl.2024.106683
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612324017124
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2024.106683?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tetsuya Takaishi, 2025. "Impact of the COVID-19 pandemic on the financial market efficiency of price returns, absolute returns, and volatility increment: Evidence from stock and cryptocurrency markets," Papers 2504.18960, arXiv.org.

    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:finlet:v:74:y:2025:i:c:s1544612324017124. 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/frl .

    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.