Correlations in Complex Heterogeneous Networks

This research project uses statistical physics and network analysis to understand and explain the contagion and panic effects associated with crises that are unexplained in standard economic models.

The global financial system is an extremely complicated, tightly interwoven network of institutions that compete with, but also depend on, each other. The stability of the financial system depends on the “fitness” of not only the individual institutions but also the whole network of their interactions and correlations. Failure of the most important institutions can bring down the whole system, and so regulation must address this collective property and adapt to its evolution. But which are the most important institutions? This project argues that size (“too big to fail”) or a high degree of connectedness is not sufficient to identify them. In an interacting complex system, strong correlations may emerge that connect a large part of the system into a single, locked-in unit. Stability depends on this strongly correlated cluster of institutions, and these are the ones that should be monitored and regulated particularly carefully in order to avoid repeated systemic meltdowns. This project identifies this strongly correlated cluster by first analyzing and then performing computer simulations of models of the financial network.