Network Structure and Systemic Risk in Banking Systems

Cont, Rama; Moussa, Amal; Santos, Edson Bastos e

doi:10.1017/cbo9781139151184.018

Cited by 217 publications

(79 citation statements)

References 45 publications

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“…Gabrieli (2011) studies the microstructure of an overnight money market network before and after the financial crisis. In a related study, Cont et al (2013) analyse the systemic risk in the Brazilian financial system and highlights the importance of network heterogeneity similar to our findings. Schumacher (2014) uncovers differences between secured and unsecured sections in Swiss foreign-exchange markets using financial network tools.…”

Section: Introductionsupporting

confidence: 85%

When does low interconnectivity cause systemic risk?

Saltoğlu

Yenilmez

2015

Quantitative Finance

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We analysed a systemic liquidity crisis by using a unique money market data-set in which the coded identity of the counterparties of each trade is known. Contrary to recent findings, we did not observe a positive relationship between interconnectivity and systemic risk. We have concluded that our conflicting findings can be related to the degree of market concentration on the borrowing side of the funding market. High level of concentration in the borrowing side led to lower interconnectivity but higher systemic risk prior to the crisis. We conclude that measures of market heterogeneity should be used to generalize the relationship between systemic risk and interconnectivity.

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Section: Introductionsupporting

confidence: 85%

When does low interconnectivity cause systemic risk?

Saltoğlu

Yenilmez

2015

Quantitative Finance

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“…The core comprises 25 among the largest institutions which are densely connected among each other, with average degree 1178. Similar insight can be obtained from the network diagrams of Cont et al (2010), although they do not focus on the core-periphery structure. They report an average in-degree and out-degree around 8, which increases if one would select the top institutions.…”

Section: Appendix C a Simple Calibration Exercisementioning

confidence: 57%

Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk

Battiston

Gatti

Gallegati

et al. 2012

Journal of Economic Dynamics and Control

583

404

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We characterize the evolution over time of a network of credit relations among financial agents as a system of coupled stochastic processes. Each process describes the dynamics of individual financial robustness, while the coupling results from a network of liabilities among agents. The average level of risk diversification of the agents coincides with the density of links in the network. In addition to a process of diffusion of financial distress, we also consider a discrete process of default cascade, due to the re-evaluation of agents' assets. In this framework we investigate the probability of individual defaults as well as the probability of systemic default as a function of the network density. While it is usually thought that diversification of risk always leads to a more stable financial system, in our model a tension emerges between individual risk and systemic risk. As the number of counterparties in the credit network increases beyond a certain value, the default probability, both individual and systemic, starts to increase. This tension originates from the fact that agents are subject to a financial accelerator mechanism. In other words, individual financial fragility feeding back on itself may amplify the effect of an initial shock and lead to a full fledged systemic crisis. The results offer a simple possible explanation for the endogenous emergence of systemic risk in a credit network.

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“…Our approach is related to the framework put forward by (Eisenberg and Noe, 2001) in order to analyze the effects of an agent's default on the cash flows of the counterparties. Such framework has been further studied also in Gai and Kapadia (2010a) and in Cont et al (2010), where the default of a bank decreases the value of the assets of each counterparty in the interbank market. In this approach, the representation of the agents in the credit network is stylized and based on accounting identities.…”

Section: Introductionmentioning

confidence: 99%

Default cascades: When does risk diversification increase stability?

Battiston

Gatti

Gallegati

et al. 2012

Journal of Financial Stability

226

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a b s t r a c tWe explore the dynamics of default cascades in a network of credit interlink-ages in which each agent is at the same time a borrower and a lender. When some counterparties of an agent default, the loss she experiences amounts to her total exposure to those counterparties. A possible conjecture in this context is that individual risk diversification across more numerous counterparties should make also systemic defaults less likely. We show that this view is not always true. In particular, the diversification of credit risk across many borrowers has ambiguous effects on systemic risk in the presence of mechanisms of loss amplifications such as in the presence of potential runs among the short-term lenders of the agents in the network.

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Network Structure and Systemic Risk in Banking Systems

Cited by 217 publications

References 45 publications

When does low interconnectivity cause systemic risk?

When does low interconnectivity cause systemic risk?

Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk

Default cascades: When does risk diversification increase stability?

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