IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v89y2024ipbp863-912.html
   My bibliography  Save this article

If GPU(time) == money: Sustainable crypto-asset market? Analysis of similarity among crypto-asset financial time series

Author

Listed:
  • Zięba, Damian

Abstract

This study conducts a formal analysis of the price creation mechanisms of Proof-of-Work (PoW) and non-PoW crypto assets revealing that the long-term market trend aligns with the rising production cost of Bitcoin supply. Enabling the utilization of computational power for solving real-world problems, similar to data centers, would facilitate the sustainability of the crypto-asset market. On the other hand, Proof-of-Stake crypto assets may serve as a practical tool for managing the collaboration between startups and venture capitalists. The second part of the analysis proposes a co-movement measure, which might be more efficient than correlation metrics for analyzing the similarity between financial time series of returns.

Suggested Citation

  • Zięba, Damian, 2024. "If GPU(time) == money: Sustainable crypto-asset market? Analysis of similarity among crypto-asset financial time series," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 863-912.
  • Handle: RePEc:eee:reveco:v:89:y:2024:i:pb:p:863-912
    DOI: 10.1016/j.iref.2023.10.036
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056023004069
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2023.10.036?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.

    More about this item

    Keywords

    Cryptocurrency; Sustainability; Correlation; Co-movement; Network analysis;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • F3 - International Economics - - International Finance
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

    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:reveco:v:89:y:2024:i:pb:p:863-912. 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/inca/620165 .

    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.