The dynamics of financial stability in complex networks

TL;DR

This paper models banking system resilience using statistical physics, revealing how minimum capital levels influence avalanche sizes and the conditions under which large financial crashes can be avoided or exacerbated.

Contribution

It introduces a physics-inspired model of banking networks that captures the impact of capital levels on systemic stability and avalanche dynamics.

Findings

Avalanche size distribution follows a power-law with an exponent dependent on minimum capital.

Increasing minimum capital levels can prevent large crashes if agents accept lower business levels.

Restoring business levels may increase the likelihood of large crises.

Abstract

We address the problem of banking system resilience by applying off-equilibrium statistical physics to a system of particles, representing the economic agents, modelled according to the theoretical foundation of the current banking regulation, the so called Merton-Vasicek model. Economic agents are attracted to each other to exchange `economic energy', forming a network of trades. When the capital level of one economic agent drops below a minimum, the economic agent becomes insolvent. The insolvency of one single economic agent affects the economic energy of all its neighbours which thus become susceptible to insolvency, being able to trigger a chain of insolvencies (avalanche). We show that the distribution of avalanche sizes follows a power-law whose exponent depends on the minimum capital level. Furthermore, we present evidence that under an increase in the minimum capital level, large crashes will be avoided only if one assumes that agents will accept a drop in business levels, while keeping their trading attitudes and policies unchanged. The alternative assumption, that agents will try to restore their business levels, may lead to the unexpected consequence that large crises occur with higher probability.