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Are the top six cryptocurrencies efficient? Evidence from time‐varying long memory

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  • Sangram Keshari Jena
  • Aviral Kumar Tiwari
  • Buhari Doğan
  • Shawkat Hammoudeh

Abstract

While gaining more popularity both as a financial asset and a commodity, a number of cryptocurrencies are emerging with a loosely regulated market microstructure which is a challenge to their efficiency. We have ranked 6 out of the top 10 cryptocurrencies based on their inefficiency ratios, using a novel time‐varying generalised Hurst exponent methodology. All the six crypto markets exhibit a time‐varying efficiency throughout the studied period, thus indicating a varying degree of exploitable profitable trading opportunities. The inefficiency ratio indicates that Bitcoin is the third most inefficient market, while the first and second most inefficient markets are DASH and NEM, respectively, thus they provide the most abnormal profit opportunities. However, the most efficient crypto markets are Ethereum and Ripple according to the order of their rankings. Further research could be performed on the factors affecting the inefficiency index to understand the efficiency determination of these cryptocurrency markets.

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  • Sangram Keshari Jena & Aviral Kumar Tiwari & Buhari Doğan & Shawkat Hammoudeh, 2022. "Are the top six cryptocurrencies efficient? Evidence from time‐varying long memory," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3730-3740, July.
    • Handle: RePEc:wly:ijfiec:v:27:y:2022:i:3:p:3730-3740
    DOI: 10.1002/ijfe.2347
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    1. Duan, Kun & Gao, Yang & Mishra, Tapas & Satchell, Stephen, 2023. "Efficiency dynamics across segmented Bitcoin Markets: Evidence from a decomposition strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    2. Abakah, Emmanuel Joel Aikins & Wali Ullah, GM & Adekoya, Oluwasegun B. & Osei Bonsu, Christiana & Abdullah, Mohammad, 2023. "Blockchain market and eco-friendly financial assets: Dynamic price correlation, connectedness and spillovers with portfolio implications," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 218-243.
    3. Jessica Morales Herrera & Ra'ul Salgado-Garc'ia, 2023. "Trend patterns statistics for assessing irreversibility in cryptocurrencies: time-asymmetry versus inefficiency," Papers 2307.08612, arXiv.org.

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