Rollover risk, network structure and systemic financial crises

Abstract

The breakdown of short-term funding markets was a key feature of the global financial crisis of 2007/8. Combining insights from the literature on global games and network growth, we develop a simple model that sheds light on how network topology interacts with the funding structure of financial institutions to determine system-wide crises. We show how the arrival of bad news about a financial institution leads others to lose confidence in it and how this, in turn, spreads across the entire interbank network. The rate of system-wide bank failure is rendered endogenous, depending crucially on both the rate at which bad news arrives and on the maturity of debt contracts. The conditions under which the financial system makes a sharp transition from a dense network of credit relations to a sparse network where credit freezes readily occur are characterized. Our results also emphasize the role of hysteresis -once broken, credit relations take a long time to re-establish as a result of common knowledge of the equilibrium. Our findings shed light on the nature of public policy responses both during and after the crisis.JEL classification: C72, G01, G21.

Financial crisis dynamics: attempt to define a market instability indicator

“…Benhabib et al (2006) studied multisector real business cycle models and found that the three-sector model has a strong propagation-a prelude to contagion-mechanism. Several recent papers have an interpretation of financial crises similar to that of the authors: the uncontrolled proliferation of financial instruments erodes systemic stability and leads the market to a susceptible critical condition with enhanced correlations (Caccioli et al 2009); the loss of confidence spreads throughout the interbank network structure, and this and debt maturity mismatches contribute to systemic financial crises (Anand et al 2011); the 2007-09þ global financial crisis is modeled as an optimization by the financial agents with a combination of shocks-burst of the housing bubble, the increased cost of borrowing, decreased consumption, and government policy (McKibbin and Stoeckel 2009); and a heavily leveraged investment demonstrates heavy-tailed price fluctuations, and margin calls force the sale of funds in a falling market whose consequent nonlinear feedback amplifies price decreases (Thurner et al 2010). One can find a general overview of agent-based models in Hommes (2008).…”

The Effect of Heterogeneity on Financial Contagion Due to Overlapping Portfolios

“…However, the former has drawn the most attention in the literature. Significant effort has been for instance devoted to studying the role of counterparty and roll-over risks in propagating contagion [20,35,21,5,3,14,2], and to understanding the impact of different interbank network topologies on the resilience of the financial system [41,29,4,32,22]. Other studies have focused on the effect that agents' strategic choices have on the systemic stability (see for instance [6]), or on the characterization of feedback loops between the macroeconomy and the financial system [1,24].…”

Sovereign public debt crisis in Europe. A network analysis

“…Among other topics we can find the accumulation of macroeconomic, fiscal and financial vulnerabilities prior to the financial crisis itself (Wyplosz, 2006;Caruana and Avdkiev, 2012), aspects related to what happened in different asset markets (Dwyer and Tkac, 2009;Melvin and Taylor 2009, among others), policy studies, transmission of shocks and asset pricing (Baba and Packer, 2009;Dimitriou et al, 2013;Morales and Andreosso-O'Callaghan, 2014), the European debt crisis (Lane, 2012;Mody andSandri, 2012, De Grawve, 2010). On the other side, econophysics literature has analyzed different aspects such as; the structure and resilience of financial networks affected by extreme event (Kantar et al, 2012;Preis et al 2012;Peron et al 2012), the network structure and systemic risks (Anand et al, 2012;Pozzi et al, 2013). 2 Data from last quarter 2013.…”