On the relationship between market regimes and the evolution of network properties in the Ethereum market

Ethereum’s introduction of smart contracts has significantly expanded blockchain use cases, enabling decentralized applications. Since all transactions are publicly available, the system can be modeled as a complex network, allowing us to uncover emergent user behavior and explore the underlying dynamics of the ecosystem. In this study, we focus on analyzing the structural differences within the Ethereum system across three distinct market regimes: bull, bear, and sideways. To achieve this, we apply a Hidden Markov Model to the log-return time series to uncover the underlying states, revealing three differentiated states, each corresponding to a specific market regime. Next, we investigate the network structural differences across these regimes, finding meaningful variations. During the bear regime, the out-degree distribution is more heterogeneous, with the largest hub exhibiting more extreme out-degree values. Additionally, during the bull and sideways regimes, we observe higher levels of reciprocity, clustering, and modularity compared to the bear regime. These findings suggest that during bull and sideways markets, the interaction patterns are more complex, and the community structure is more cohesive. Overall, our work underscores how market conditions shape trading patterns and the structural properties of the Ethereum transaction network, providing new insights into the interplay between market regimes, network topology, and user behavior in decentralized ecosystems.