Examining Cryptocurrency Market Efficiency in Light of the COVID-19 Pandemic: A Comparative Analysis

Abstract

This article delves into the intricacies of financial market efficiency, with a particular emphasis on the impact of long memory on market inefficiency. Contrary to the efficient market hypothesis, the presence of long memory suggests a departure from efficiency, influencing investment decisions and the adaptability of investors. The study transitions its focus to the realm of cryptocurrencies, underscoring their susceptibility to behavioral biases and offering a comparative analysis between Islamic and conventional models. The empirical investigation is anchored in the context of the COVID-19 pandemic, employing the Multifractal Detrended Fluctuation Analysis (MFDFA) methodology to evaluate market efficiency, fractality, and herding behavior within cryptocurrency markets. The findings not only highlight the distinctive characteristics of these markets but also underscore their practical implications for policymakers and financial managers, particularly in light of the pandemic's unprecedented challenges.