Network causality structures among Bitcoin and other financial assets : a directed acyclic graph approach

Abstract

We use a data-driven methodology, namely the directed acyclic graph, to uncover the contemporaneous and lagged relations between Bitcoin and other asset classes. The adopted methodology allows us to identify causal networks based on the measurements of observed correlations and partial correlations, without relying on a priori assumptions. Results from the contemporaneous analysis indicate that the Bitcoin market is quite isolated, and no specific asset plays a dominant role in influencing the Bitcoin market. However, we find evidence of lagged relationships between Bitcoin and some assets, especially during the bear market state of Bitcoin. This finding suggests that the integration between the Bitcoin and other financial assets is a continuous process that varies over time. We conduct forecast error variance decompositions and find that the influence of each of the other assets on Bitcoin over a 20-day horizon does not account for more than 11% of all innovations.