Rethinking Financial Contagion

Abstract

How, and to what extent, does an interconnected financial system endogenously amplify external shocks? This paper attempts to reconcile some apparently different views emerged after the 2008 crisis regarding the nature and the relevance of contagion in financial networks. We develop a common framework encompassing several network contagion models and show that, regardless of the shock distribution and the network topology, precise ordering relationships on the level of aggregate systemic losses hold among models. We argue that the extent of contagion crucially depends on the amount of information that each model assumes to be available to market players. Under no uncertainty about the network structure and values of external assets, the well-known Eisenberg and Noe (2001) model applies, which delivers the lowest level of contagion. This is due to a property of loss conservation: aggregate losses after contagion are equal to the losses incurred by those institutions initially hit by a shock. This property implies that many contagion analyses rule out by construction any loss amplification, treating de facto an interconnected system as a single aggregate entity, where losses are simply mutualised. Under higher levels of uncertainty, as captured for instance by the DebtRank model, losses become non-conservative and get compounded through the network. This has important policy implications: by reducing the levels of uncertainty in times of distress (e.g. by obtaining specific data on the network) policymakers would be able to move towards more conservative scenarios. Empirically, we compare the magnitude of contagion across models on a sample of the largest European banks during the years 2006-2016. In particular, we analyse contagion effects as a function of the size of the shock and the type of external assets shocked.

Distress and default contagion in financial networks

“…Note that the ordering results presented in Visentin, Battiston, and D'Errico (2016) are special cases of the above relationship.…”

Network models of financial systemic risk: a review

“…Otherwise, these discount factors increase losses, introducing costs for bailouts that exceed the initial losses of the financial system. In fact, while EN simply redistributes losses across the financial system, as discussed in [13], Rogers and Veraart clearing procedure recognizes the existence of extra costs, which are exactly the ones that financial regulatory institutions want to minimize. The motivation is that, while external losses coming from economic shocks are driven by scarcely controllable complex economic dynamics, the possible endogenous loss amplification due to the financial system interconnectedness could be avoided by regulators by imposing specific policies.…”

A Financial Macro-Network Approach to Climate Policy Evaluation

“…It may be tempting to think that in the economic system, since one agent's asset is another agent's liability, then, in the aggregate, assets and liabilities can be simply netted out. This intuition is correct under the following conditions: i) there are no bankruptcy costs and no information asymmetry (Visentin et al, 2016;Bardoscia et al, 2016Bardoscia et al, , 2017, or ii) debt contracts are fully collateralized with recovery rate close to one (in case of counterparty's default, Battiston et al, 2016c). However, in general, the above conditions do not hold and, as a result, the intuition about netting out is incorrect in many empirical situations that are relevant to the discussions on distress propagation and the impact of climate policies.…”