Herding Behavior and Evolutionary Equilibrium in Cryptocurrency Markets: A Markov Regime-Switching Analysis

Traditional finance theories rest on the Efficient Market Hypothesis, which assumes that market participants are fully rational and that prices reflect all available information. However, the excessive volatility and speculative bubbles observed in cryptocurrency markets call the validity of these assumptions into question. This study aims to examine the price dynamics of the Bitcoin market from the perspective of Evolutionary Game Theory (EGT) and to empirically test structural shifts in investor behavior. Within this framework, the strategic interaction between “fundamentalists” and “herders” is theoretically modeled and shown to drive the market toward multiple equilibrium points. To analyze this dynamic structure, a Markov regime-switching model is applied to Bitcoin daily return data. The findings reveal that the market exhibits transitions between two distinct regimes: a “low-variance rational pricing” regime and a “high-variance herding” regime. The results indicate that price formation in cryptocurrency markets is not a static equilibrium but rather an evolutionary adaptation process.