Collective behavior in financial markets

The financial market is an example of a complex system characterized by a highly intricate organization and the emergence of collective behavior. In this paper, this emergent dynamics in the financial market is quantified by using concepts of network synchronization. We consider networks constructed by the correlation matrix of asset returns and study the time evolution of the phase coherence among stock prices. It is verified that during a financial crisis a synchronous state emerges in the system, defining the market's direction. Furthermore, the paper proposes a statistical regression model able to identify the topological features that mostly influence such an emergence. The coefficients of the proposed model indicate that the average shortest path length is the measurement most related to network synchronization. Therefore, during an economic crisis, the stock prices present a similar evolution, which tends to shorten the distances between stocks indicating a collective dynamics