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The dynamics of market efficiency of major cryptocurrencies

Author

Listed:
  • Aslam, Faheem
  • Memon, Bilal Ahmed
  • Hunjra, Ahmed Imran
  • Bouri, Elie

Abstract

The exponential growth of Fintech innovation has increased the interest in cryptocurrency market informational efficiency given that cryptocurrencies and their underlying blockchain technology represent a profound yet ambiguous facet of Fintech. In this context, this paper examines the dynamic changes in the market efficiency of six major cryptocurrencies using the multifractal detrended fluctuation analysis (MFDFA) approach. The empirical findings confirm a varying degree of multifractal strength in the cryptocurrencies under consideration, which could be related to market inefficiency and fractal market hypothesis verification. Based on the multifractal indices, Bitcoin and Litecoin are the two most inefficient cryptocurrencies, whereas Cardano and Binance Coin exhibit the least inefficiency. Ripple and Ethereum remain in the middle. Overall, the cryptocurrencies exhibit persistence behaviour but show a significant change over time. Finally, we perform a rolling-window analysis and confirm the presence of multifractality, which seems to vary over time, suggesting that market (in)efficiency is an evolving process that can be shaped by market conditions. We argue that these findings could be related to herding behaviour, especially during crisis periods. The findings have policy implications, including the possibility of using active trading for profit-making strategies.

Suggested Citation

  • Aslam, Faheem & Memon, Bilal Ahmed & Hunjra, Ahmed Imran & Bouri, Elie, 2023. "The dynamics of market efficiency of major cryptocurrencies," Global Finance Journal, Elsevier, vol. 58(C).
    • Handle: RePEc:eee:glofin:v:58:y:2023:i:c:s1044028323000947
    DOI: 10.1016/j.gfj.2023.100899
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    Cited by:

    1. BEN ABDALLAH Mohamed & TALBI Omar, 2024. "A Wavelet Analysis of Bitcoin Price Volatility Dynamic," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(1), pages 951-964, January.

    More about this item

    Keywords

    Cryptocurrency; Market efficiency; MF-DFA; Rolling window; Herding behaviour; COVID-19 outbreak;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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