Persistence in the cryptocurrency market: does size matter?


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This paper investigates the persistence in the cryptocurrency market, focusing on five distinct groups categorized by their market capitalization during the sample period from 2020 to 2023. The study aims to test two hypotheses: (H1) The degree of persistence in the cryptocurrency market is contingent on market capitalization, and (H2) The efficiency of the cryptocurrency market has increased in recent years. The methodology employed for this examination is R/S analysis. The results indicate that the cryptocurrency market maintains its inefficiency, and no significant variations in persistence are discerned among different cryptocurrency groups, leading to the rejection of H1. Outcomes related to H2 present a nuanced scenario. Specifically, Litecoin and Ripple exhibit supportive evidence for the Adaptive Market Hypothesis, suggesting an improvement in the efficiency of the cryptocurrency market in recent years. A noteworthy revelation pertains to the anomaly observed in Bitcoin. Despite being the most capitalized and liquid cryptocurrency, it demonstrates inefficiency akin to levels observed five years ago. The implications of this study contribute to the comprehension of cryptocurrency market efficiency. The findings challenge the assumptions of the Efficient Market Hypothesis, favoring instead the Adaptive Market Hypothesis. For practitioners, the results hold significance, providing evidence of price predictability, particularly in the case of Bitcoin. This suggests that trend trading strategies remain viable for generating abnormal profits in the cryptocurrency market.

Alex Plastun gratefully acknowledges financial support from the Ministry of Education and Science of Ukraine (0121U100473).

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    • Figure 1. Results of the dynamic R/S analysis (step = 50, data window = 300)
    • Table 1. Groups and cryptocurrencies (October 18, 2023)
    • Table 2. Results of the R/S analysis for the selected crypto currencies within groups, 2020–2023
    • Table 3. Descriptive statistics for the results of the R/S analysis for the selected crypto currencies within groups, 2020–2023
    • Table 4. Comparative analysis of the current findings with previous research (Caporale et al., 2018)
    • Formal Analysis
      Alex Plastun, Lyudmila Khomutenko
    • Project administration
      Alex Plastun
    • Supervision
      Alex Plastun
    • Writing – original draft
      Alex Plastun, Dmytro Sliusarev, Valentyna Smachylo, Lyudmila Khomutenko
    • Writing – review & editing
      Alex Plastun
    • Conceptualization
      Liudmyla Slіusareva
    • Data curation
      Liudmyla Slіusareva
    • Resources
      Liudmyla Slіusareva, Dmytro Sliusarev
    • Visualization
      Liudmyla Slіusareva
    • Funding acquisition
      Dmytro Sliusarev, Valentyna Smachylo
    • Software
      Dmytro Sliusarev
    • Investigation
      Valentyna Smachylo, Lyudmila Khomutenko
    • Methodology
      Valentyna Smachylo, Lyudmila Khomutenko
    • Validation
      Lyudmila Khomutenko