Risk trading, network topology, and banking regulation

TL;DR

This paper models risk trading among banks using a network-based iterative game, revealing how network topology and regulation parameters influence systemic safety and default rates, with implications for banking regulation policies.

Contribution

It introduces a novel network-based risk trading model to analyze the effects of topology and regulation on systemic safety and default probabilities.

Findings

System safety exhibits a phase transition-like behavior influenced by regulation parameters.

Tighter regulation does not always improve banking system safety.

Local risk-sharing networks have higher default rates than less cyclic networks.

Abstract

In the context of understanding the nature of the risk transformation process of the financial system we propose an iterative risk-trading game between several agents who build their trading strategies based on a general utility setting. The game is studied numerically for different network topologies. Consequences of topology are shown for the wealth time-series of agents, for the safety and efficiency of various types of networks. The proposed setup allows an analysis of the effects of different approaches to banking regulation as currently suggested by the Basle Committee of Banking Supervision. We find a phase transition-like phenomenon, where the Basle parameter plays the role of temperature and system safety serves as the order parameter. This result suggests the existence of an optimal regulation parameter. As a consequence a tightening of the current regulatory framework does not necessarily lead to an improvement of the safety of the banking system. Moreover, we show that banking systems with local risk-sharing cooperations have higher global default rates than systems with low cyclicality.