Default Cascades in Complex Networks: Topology and Systemic Risk

Abstract

The recent crisis has brought to the fore a crucial question that remains still open: what would be the optimal architecture of financial systems? We investigate the stability of several benchmark topologies in a simple default cascading dynamics in bank networks. We analyze the interplay of several crucial drivers, i.e., network topology, banks' capital ratios, market illiquidity, and random vs targeted shocks. We find that, in general, topology matters only – but substantially – when the market is illiquid. No single topology is always superior to others. In particular, scale-free networks can be both more robust and more fragile than homogeneous architectures. This finding has important policy implications. We also apply our methodology to a comprehensive dataset of an interbank market from 1999 to 2011.

Systemic Risk, Contagion, and Financial Networks: A Survey

“…Furthermore, the simulations are parametrized as to model two different economic scenarios: a normal time scenario, where most credit is repaid and returns on investments are higher; and a crisis time scenario, where banks suffer larger losses on their investments. The author finds that -in normal times -different network topologies have a similar performance in terms of systemic risk (a result that was also found in Roukny et al (2013)). However, in times of crisis, network topology do matters.…”

“…The financial system is more likely to be trapped near the threshold at which large cascades occur when the diversification is large, and there exists an optimal level of risk diversification that does not coincide with full diversification. In a more recent contribution, Roukny et al (2013) analyze how different factors interplay in determining the stability of the financial system. That is, network topology, banks' characteristics (including financial robustness), capital and liquidity requirements, and types of shocks all contribute in determining the resilience of the interbank market.…”

Network centrality and funding rates in the e-MID interbank market

“…A number of papers investigate the interplay between financial distress and topological characteristic of interbank networks, focusing on the network resilience to different kinds of shocks (Iori et al (2006), Nier et al (2007), Gai et al (2011), , Anand et al (2012), Lenzu and Tedeschi (2012), Georg (2013), Roukny et al (2013), Acemoglu et al (2015)). While some authors argue that a more interconnected architecture enhances the resilience of the system to failure of an individual bank because credit risk is shared among more creditors, others suggest that a higher density of connections may function as a destabilizing force, facilitating financial distress to spread through the banking system.…”

Interconnectedness as a Source of Uncertainty in Systemic Risk

“…The main focus of the literature has been so far on understanding how the structure of the financial network (along the various aforementioned channels) can mitigate or amplify systemic risk (Elsinger et al, 2006;Gai and Kapadia, 2010;Gai et al, 2011;Georg, 2013;Cont et al, 2013;Roukny et al, 2013;Elliott et al, 2014;Acemoglu et al, 2015b;Glasserman and Young, 2015). Fewer works have been devoted to understanding how the structure of the financial network can instead affect the very ability to assess systemic risk.…”