This paper aims to delve into the intricate dynamics of the Bitcoin market, combining established financial theories with innovative methodologies to assess market efficiency and identify anomalies.
The paper investigates the efficiency of the Bitcoin market through a diverse set of lenses, using statistical methods such as linear and rank correlations, mean absolute error, mean squared error and introducing a unique copula-based approach for modeling dependence structures. The authors explore the weak form of informational market efficiency, focusing on the period before and after 2014.
Notable findings from this study include evidence of partial inefficiency, the emergence of anomalies, and the presence of predictability, challenging the assumption of a pure martingale. Structured into sections reviewing relevant literature, outlining this empirical methodology, presenting robust empirical results and concluding with insights and implications, this paper contributes to a deeper understanding of Bitcoin’s market behavior.
Despite the extensive literature on market efficiency, the Bitcoin market remains relatively unexplored. This study addresses this gap, offering a nuanced analysis that goes beyond traditional measures. This work emphasizes the relevance of adopting innovative approaches to assess market efficiency in a rapidly evolving financial landscape.
