LAUSR

Recurrent interactions between agents play an essential role in the organization of a dynamic complex system. While intensive researches have been done on social systems formed by human interactions, dynamical rules are not well understood in economic systems. Here we study the evolution of financial networks and show that repeated interactions between financial institutions taking place at the daily scale are characterized by social communication patterns of humans emerging at higher time scales. The “social” dynamics of financial interactions are highly stable and little affected by external shocks such as the occurrence of the global financial crisis. A dynamic network model based on random pairwise matching accurately explains the observed daily dynamical patterns. The observed similarity between social and financial interactions gives us previously unknown stylized facts about a financial system, which could lead to a deeper understanding of the fundamental source of systemic risk.