Is Bitcoin an Efficient Market? A Meta-Analytic Review of Price Dynamics and Efficient Market Hypothesis Tests

This thesis critically examines the efficiency of the Bitcoin market through a meta-analytic review of existing empirical studies testing the Efficient Market Hypothesis (EMH). Synthesizing findings from recent academic literature and analyzing results from various weak-form efficiency tests (including autocorrelation, variance ratio, and unit root tests), the research evaluates whether Bitcoin prices follow a random walk or exhibit predictable patterns. The study integrates the traditional EMH framework with insights from the Adaptive Market Hypothesis (AMH) and behavioral finance to interpret the often conflicting empirical evidence. A conceptual model outlining potential drivers of Bitcoin market efficiency, such as liquidity, volatility, regulatory uncertainty, market maturity, and behavioral biases, is developed and discussed. The synthesis of evidence suggests that the Bitcoin market does not consistently adhere to weak-form efficiency; instead, it exhibits dynamic, time-varying efficiency levels influenced by market conditions, participant behavior, and external shocks, aligning more closely with the AMH. While periods consistent with efficiency may occur, significant evidence points towards predictability, particularly in earlier market phases or during periods of high stress. The findings indicate that a nuanced, adaptive perspective is necessary to understand Bitcoin price dynamics. Limitations related to methodological heterogeneity and the scope of the meta-analytic review are acknowledged, and directions for future research, including comprehensive quantitative meta-analysis and further investigation into semi-strong efficiency and efficiency drivers, are proposed.