The multiplex structure of interbank networks

Bargigli, Leonardo; Iasio, Giovanni di; Infante, Luigi; Lillo, Fabrizio; Pierobon, Federico

doi:10.1080/14697688.2014.968356

Cited by 227 publications

(164 citation statements)

References 48 publications

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“…The model-implied equivalents are respectively 0.056 and 0.109. Similarly, we find that that both networks exhibit negative assortativity (or disassortativity), confirming the findings of Bargigli et al (2015). 16 The model-implied average assortativity equals -0.55 for the unsecured and -0.48 for the secured market, being modestly lower than what has been confirmed empirically for both market segments.…”

Section: Baseline Resultssupporting

confidence: 87%

“…The small fraction of central hubs in the secured segment can represent the natural emergence of dealer banks which, due to their market perceptions, serve as market makers in the repo transactions (Stigum and Crescenzi, 2007). The unsecured market is also found to be less clustered in the Italian interbank market in short-and long-term transactions (see Bargigli et al, 2015).…”

Section: Baseline Resultsmentioning

confidence: 99%

“…Nevertheless, Bargigli et al (2015) carry out an experiment on the Italian interbank network, analyzing short-and long-term interbank contracts in the unsecured and secured markets. For instance they report that the clustering coefficient in the long-term (longer than 12 months) unsecured and secured markets were respectively 0.056 and 0.135 in 2008.…”

Section: Baseline Resultsmentioning

confidence: 99%

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Interbank loans, collateral and modern monetary policy

Wolski

Leur

2016

Journal of Economic Dynamics and Control

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Section: Baseline Resultssupporting

confidence: 87%

Section: Baseline Resultsmentioning

confidence: 99%

Section: Baseline Resultsmentioning

confidence: 99%

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Interbank loans, collateral and modern monetary policy

Wolski

Leur

2016

Journal of Economic Dynamics and Control

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“…As Langfield and Soramäki (2014) highlight, banks engage in hundreds of different types of transactions with each other, such as interbank lending, repurchase agreements or derivatives. This plethora of possible link types can be captured by multilayer financial networks, where different layers represent different transaction types (Aldasoro and Alves, 2015;Bargigli et al, 2014;Montagna and Kok, 2013). Empirical studies have also provided new insights into the structure of interbank networks.…”

Section: Introductionmentioning

confidence: 99%

Too interconnected to fail: a survey of the interbank networks literature

Hüser¹

2015

JNTF

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A network approach to banking is particularly important for assessing financial stability and systemic risk. This approach can be instrumental in capturing the externalities that the risk associated with a single institution may create for the entire system. Indeed, from a financial stability perspective, banks should neither be too-big-to-fail nor too-interconnected-to-fail. A better understanding of network externalities may facilitate the adoption of a macroprudential framework for financial supervision. Network externalities arise when risk-taking behavior of individual institutions affects other institutions and the system as a whole. To guide policy it becomes necessary, in this context, to measure the systemic importance of individual banks, i.e. their capacity to generate contagion in the rest of the system. The analysis of interbank networks can provide this guidance.Against this background we review the literature on interbank networks, which is part of a growing literature on financial networks. The broader financial networks literature is analyzing connections between financial institutions: banks, but also hedge funds, insurance companies, etc. We restrict the survey's focus on the interbank network literature. This survey presents a systematic overview of our current understanding of the structure of interbank networks, of how network characteristics affect contagion in the banking system and of how banks form connections when faced with the possibility of contagion and systemic risk. In particular, we highlight how the theoretical literature on interbank networks offers a coherent way of studying interconnections, contagion processes and systemic risk, while emphasizing at the same time the many challenges that must be addressed before general results on the link between the structure of the interbank network and financial stability can be established.The theoretical literature has generated a number of insights on the effect of the network structure on contagion. A first result is that the number and magnitude of defaults depend on the network topology. There is now substantial research characterizing those structures that tend to propagate default or alternatively that tend to dampen it. An avenue for further research is to have more realistic network structures on which to analyze contagion. Since empirical studies now provide an increasing number of stylized facts on the interbank network topology, research needs to move beyond deriving results on random networks or on overly simplified structures. Furthermore, the fragility of the system depends on the location in the network of the institution that was initially affected. Intuitively, the failure of core banks is more damaging than the failure of a periphery bank. Finally, another main finding is that there is a trade-off between risk sharing via linkages to other banks and contagion risk due to too many linkages. While the existence of the trade-off is not disputed, there is no consensus on whether a complete network dampens or fuels contag...

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“…For example, we can take a sample of individuals and constitute a social media layer, in which links represent interactions on social media, a kinship layer, a geographical proximity layer, and so on. Examples of studies that have conceptualized real networked systems under the multiplex framework include citation networks [1,2], online social media [3,4], interbank networks [5], airline networks [6], scientific collaboration networks [1,7], and web of connections and interactions in online games [8].…”

Section: Introductionmentioning

confidence: 99%

Growing multiplex networks with arbitrary number of layers

Momeni

Fotouhi

2015

Phys. Rev. E

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This paper focuses on the problem of growing multiplex networks. Currently, the results on the joint degree distribution of growing multiplex networks present in the literature pertain to the case of two layers, and are confined to the special case of homogeneous growth, and are limited to the state state (that is, the limit of infinite size). In the present paper, we obtain closed-form solutions for the joint degree distribution of heterogeneously growing multiplex networks with arbitrary number of layers in the steady state. Heterogeneous growth means that each incoming node establishes different numbers of links in different layers. We consider both uniform and preferential growth. We then extend the analysis of the uniform growth mechanism to arbitrary times. We obtain a closedform solution for the time-dependent joint degree distribution of a growing multiplex network with arbitrary initial conditions. Throughout, theoretical findings are corroborated with Monte Carlo simulations. The results shed light on the effects of the initial network on the transient dynamics of growing multiplex networks, and takes a step towards characterizing the temporal variations of the connectivity of growing multiplex networks, as well as predicting their future structural properties.

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The multiplex structure of interbank networks

Cited by 227 publications

References 48 publications

Interbank loans, collateral and modern monetary policy

Interbank loans, collateral and modern monetary policy

Too interconnected to fail: a survey of the interbank networks literature

Growing multiplex networks with arbitrary number of layers

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