IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v29y2022i3p212-218.html
   My bibliography  Save this article

All the frequencies matter in the Bitcoin market: an efficiency analysis

Author

Listed:
  • David Vidal-Tomás

Abstract

Most studies in the Bitcoin literature are focused on daily data without considering other options. Therefore, it is necessary to analyse Bitcoin features at different frequencies. In this letter, we examine Bitcoin efficiency from 1 min to weekly data using the generalized Hurst exponent. Our results show that Bitcoin is more efficient over time regardless of the frequency. In particular, we observe that, since 2016, daily data are generally the most efficient frequency while 1 min and weekly data are the most inefficient. These results are relevant for investors and scholars since we detect the most profitable frequencies and underline the relevance of analysing different frequencies than daily data.

Suggested Citation

  • David Vidal-Tomás, 2022. "All the frequencies matter in the Bitcoin market: an efficiency analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 29(3), pages 212-218, February.
  • Handle: RePEc:taf:apeclt:v:29:y:2022:i:3:p:212-218
    DOI: 10.1080/13504851.2020.1861196
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13504851.2020.1861196
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13504851.2020.1861196?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. Wang, Fang & Gacesa, Marko, 2023. "Semi-strong efficient market of Bitcoin and Twitter: An analysis of semantic vector spaces of extracted keywords and light gradient boosting machine models," International Review of Financial Analysis, Elsevier, vol. 88(C).
    2. Antonio Briola & Tomaso Aste, 2022. "Dependency structures in cryptocurrency market from high to low frequency," Papers 2206.03386, arXiv.org, revised Dec 2022.
    3. Ailie Charteris & Conrad Alexander Steyn, 2023. "The Bank of Japan’s exchange traded fund purchases: a help or hindrance to market efficiency?," Journal of Asset Management, Palgrave Macmillan, vol. 24(3), pages 225-240, May.

    More about this item

    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:taf:apeclt:v:29:y:2022:i:3:p:212-218. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    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.