Purpose: This study focused on evaluating the efficiency of the global cryptocurrency market under the efficient market hypothesis.

Methodology: The study explored the presence of calendar effects in the form of the day-of-the-week and the weekend effect in the top 25 global cryptocurrencies and a constructed index using autocorrelation corrected ARCH family models on the log-returns of prices. Non-normality is tackled through the use of a non-parametric bootstrapped approach in addition to parametric estimation. Additionally, rolling window regression is employed as a dynamic framework.

Findings: The findings of this study showed the presence of calendar effects in terms of higher returns for certain days over others, thereby concluding that the global cryptocurrency market as a whole was not efficient.Practical

Implications: As a result of its informational inadequacies, it was implied that cryptocurrency markets were not even efficient in the weak form. This had practical implications for investors, whose aggressive search and trading tactics appear warranted in the context of market anomalies, as well as other market players, like regulators attempting to comprehend the structure of the cryptocurrency market from an efficiency standpoint and researchers attempting to investigate the efficiency-related behavior and psychology of crypto markets.

Originality: This study is exceptional in that it uses a sample of cryptocurrencies that objectively covers the larger global cryptocurrency markets over the most extended amount of time possible, making it unique both for the participants in the crypto markets and for its contribution to the literature on market efficiency. The study employed an evolutionary methodology, taking into account the time-varying behavior of financial assets. As far as we can tell, this is one of the first studies to use this methodology and model formulation.

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