Modeling Emergence of the Interbank Networks

Hałaj, Grzegorz; Kok, Christoffer

doi:10.2139/ssrn.2397106

Cited by 10 publications

(2 citation statements)

References 49 publications

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“…Further studies deal with other aspects of bank interactions, and all use either a highly connected or a fully connected network. Hałaj and Kok (2014) and Degryse and Nguye (2007) model interbank lending and borrowing; Chan-Lau et al (2007) model shock propagation through the network. Finally, Tabak and de Castro Miranda (2013) use a partitioned network to isolate certain nodes.…”

Section: Contagion Effects In Banking Networkmentioning

confidence: 99%

Reputation risk contagion

Mitic¹

2017

JNTF

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The effects of the reputation of any single member of a group of agents on all the others in the group are calculated by modeling the spread of reputation contagion in a DeGroot network. The reputation of individual agents is measured by compiling a reputation index for each agent over an extended period. Transition probabilities within the network are assessed by considering extreme reputational events using a Bayesian approach. The results indicate that consensus is reached quickly, and influential agents can be easily identified. Agents in the network with a very positive reputation serve to mitigate the negative reputation of other agents in the network. Approximately 10-15% of the reputation of any agent in the network is attributable to network effects; positive reputations are deflated and negative reputations are inflated. The network effect on the sales of any single agent can be estimated once the reputation score has been translated to sales.

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Section: Contagion Effects In Banking Networkmentioning

confidence: 99%

Reputation risk contagion

Mitic¹

2017

JNTF

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“…This data is confidential and usually unavailable even for supervisory authorities and central banks. As a solution to these problems, many researchers use various methods, in order to estimate the structure of connections between banks [55,41,64].…”

Section: Introductionmentioning

confidence: 99%

Can banks default overnight? Modelling endogenous contagion on the O/N interbank market

Smaga

Wilinski

Ochnicki

et al. 2018

Quantitative Finance

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We propose a new model of the liquidity driven banking system focusing on overnight interbank loans. This significant branch of the interbank market is commonly neglected in the banking system modeling and systemic risk analysis. We construct a model where banks are allowed to use both the interbank and the securities markets to manage their liquidity demand and supply as driven by prudential requirements in a volatile environment. The network of interbank loans is dynamic and simulated every day. We show how only the intrasystem cash fluctuations, without any external shocks, may lead to systemic defaults, what may be a symptom of the self-organized criticality of the system. We also analyze the impact of different prudential regulations and market conditions on the interbank market resilience. We confirm that central bank's asset purchase programs, limiting the declines in government bond prices, can successfully stabilize bank's liquidity demand. The model can be used to analyze the interbank market impact of macroprudential tools.

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An endogenous network model of banking systems

Xin

2016

Complexity

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In this article, we propose an endogenous network model for banking systems. Starting from the balance sheets of a banking system and its update algorithms, the interbank credit lending was established based on the partner selection mechanism. Through simulation analysis, we find that the endogenous network model displays a structure with multiple liquidity centers, that the in-degree distribution exhibits a Pareto tail, and that the bank asset distribution is a lognormal distribution with a Pareto tail.

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Modeling Emergence of the Interbank Networks

Cited by 10 publications

References 49 publications

Reputation risk contagion

Reputation risk contagion

Can banks default overnight? Modelling endogenous contagion on the O/N interbank market

An endogenous network model of banking systems

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