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On the efficiency and its drivers in the cryptocurrency market: the case of Bitcoin and Ethereum

Author

Listed:
  • Khaled Mokni

    (University of Sousse)

  • Ghassen El Montasser

    (University of Manouba)

  • Ahdi Noomen Ajmi

    (Prince Sattam Bin Abdulaziz University
    Manouba University)

  • Elie Bouri

    (Lebanese American University)

Abstract

Most previous studies on the market efficiency of cryptocurrencies consider time evolution but do not provide insights into the potential driving factors. This study addresses this limitation by examining the time-varying efficiency of the two largest cryptocurrencies, Bitcoin and Ethereum, and the factors that drive efficiency. It uses daily data from August 7, 2016, to February 15, 2023, the adjusted market inefficiency magnitude (AMIMs) measure, and quantile regression. The results show evidence of time variation in the levels of market (in)efficiency for Bitcoin and Ethereum. Interestingly, the quantile regressions indicate that global financial stress negatively affects the AMIMs measures across all quantiles. Notably, cryptocurrency liquidity positively and significantly affects AMIMs irrespective of the level of (in) efficiency, whereas the positive effect of money flow is significant when the markets of both cryptocurrencies are efficient. Finally, the COVID-19 pandemic positively and significantly affected cryptocurrency market inefficiencies across most quantiles.

Suggested Citation

  • Khaled Mokni & Ghassen El Montasser & Ahdi Noomen Ajmi & Elie Bouri, 2024. "On the efficiency and its drivers in the cryptocurrency market: the case of Bitcoin and Ethereum," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-25, December.
    • Handle: RePEc:spr:fininn:v:10:y:2024:i:1:d:10.1186_s40854-023-00566-3
    DOI: 10.1186/s40854-023-00566-3
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    More about this item

    Keywords

    Bitcoin; Ethereum; Time-varying efficiency; AMIMs; Quantile regression; Drivers of efficiency;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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