Bitcoin Market Return and Volatility Forecasting Using Transaction Network Flow Properties

Abstract

Bitcoin, as the foundation for a secure electronic payment system, has drawn broad interests from researchers in recent years. In this paper, we analyze a comprehensive Bitcoin transaction dataset and investigate the interrelationship between the flow of Bitcoin transactions and its price movement. Using network theory, we examine a few complexity measures of the Bitcoin transaction flow networks, and we model the joint dynamic relationship between these complexity measures and Bitcoin market variables such as returns and volatility. We find that complexity of Bitcoin transaction network is significantly correlated with Bitcoin market volatility. More specifically we document that the popularity of Bitcoin gauged from total system throughput can significantly improve the predictability of Bitcoin market returns and volatility using network flow complexity measures.