Contagion in the Interbank Network: An Epidemiological Approach

Toivanen, Mervi

doi:10.2139/ssrn.2331300

Cited by 40 publications

(35 citation statements)

References 70 publications

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“…We can thus conclude that coreness and in/out-degree are more explanatory for systemic risk than the other variables, in line with the recent paradigm shift from "too big to fail" to "too interconnected to fail" [51]. Note that Toivanen [50] reached similar conclusions for its credit-driven contagion model, in which an increase in the connectivity of a bank poses a greater threat to the banking system than an increase in its size.…”

Section: Econometric Analysissupporting

confidence: 73%

“…In particular, by assuming that liquidity shocks propagate as an epidemic disease over the market, we adapt the well-known SIR (Susceptible-Infected-Removed) model [47][48][49] to the specific context of liquidity shocks interbank networks, and cast it as an EDB (Exposed-Distressed-Bankrupted) model. This is close to the work by Toivanen in the context of credit shocks [50]. We simulate such a dynamical model on the Italian interbank network e-MID (electronic market for interbank deposits) [15,27,29,30], analyzing liquidity contagion in relation with the structure and evolution of the network, and defining systemic risk through the resilience of individual banks and of the overall system to liquidity shocks.…”

Section: Introductionmentioning

confidence: 69%

See 1 more Smart Citation

Epidemics of liquidity shortages in interbank markets

Brandi

Clemente

Cimini

2018

Physica A: Statistical Mechanics and its Applications

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Financial contagion from liquidity shocks has being recently ascribed as a prominent driver of systemic risk in interbank lending markets. Building on standard compartment models used in epidemics, in this work we develop an EDB (Exposed-Distressed-Bankrupted) model for the dynamics of liquidity shocks reverberation between banks, and validate it on electronic market for interbank deposits data. We show that the interbank network was highly susceptible to liquidity contagion at the beginning of the 2007/2008 global financial crisis, and that the subsequent micro-prudential and liquidity hoarding policies adopted by banks increased the network resilience to systemic risk-yet with the undesired side effect of drying out liquidity from the market. We finally show that the individual riskiness of a bank is better captured by its network centrality than by its participation to the market, along with the currently debated concept of "too interconnected to fail".

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Section: Econometric Analysissupporting

confidence: 73%

Section: Introductionmentioning

confidence: 69%

Epidemics of liquidity shortages in interbank markets

Brandi

Clemente

Cimini

2018

Physica A: Statistical Mechanics and its Applications

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“… Most models of interbank lending essentially depend on the mechanisms of virus propagation across networks, epidemiological in nature, that trace patterns of susceptibility, infection and recovery. See Toivanen () and Weng, Menczer, and Ahn (). The analogy to the epidemiological models is obvious and correct: as an infected agent circulates on a grid, it transmits the disease to a variety of partners depending on their susceptibility.…”

mentioning

confidence: 99%

Real and financial crises in the Keynes–Kalecki structuralist model: An agent‐based approach

Gibson

Setterfield

2018

Metroeconomica

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Agent‐based models are inherently microstructures—with their attention to agent behavior in a field context—and only aggregate up to systems with recognizable macroeconomic characteristics. One might ask why the traditional Keynes–Kalecki or structuralist (KKS) model would bear any relationship to the multi‐agent modeling approach. This paper shows how KKS models might benefit from agent‐based microfoundations, without sacrificing traditional macroeconomic themes, such as aggregate demand, animal spirits and endogenous money. Above all, the integration of the two approaches gives rise to the possibility that a KKS system—stable over many consecutive time periods—might lurch into an uncontrollable downturn, from which a recovery would require outside intervention. As a by‐product of the integration of these two popular approaches, there emerges a cogent analysis of the network structure necessary to bind real and financial agents into an integrated whole. It is seen, contrary to much of the existing literature, that a highly connected financial system does not necessarily lead to more crashes of the integrated system.

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“…All above works show the advantages of complex network theory in the application of risk contagion. However, there are still some points needed to be improved: (i) Above models basically analyzed the characteristics of network risk contagion from a macro perspective, mainly analyzed the [45] used an epidemiologic SIR model to model the spreading of the contagion in the interbank network and analyzed the importance of individual bank-specific factors on financial stability. Brandi and Clemente [46] developed an Exposed-Distressed-Bankrupted model based on SIR model for the dynamics of liquidity shocked reverberation between banks.…”

Section: Introductionmentioning

confidence: 99%

Credit Risk Contagion Based on Asymmetric Information Association

2018

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The study of the contagion law of credit risk is very important for financial market supervision. The existing credit risk contagion models based on complex network theory assume that the information between individuals in the network is symmetrical and analyze the proportion of the individuals infected by the credit risk from a macro perspective. However, how individuals are infected from a microscopic perspective is not clear, besides the level of the infection of the individuals is characterized by only two states: completely infected or not infected, which is not realistic. In this paper, a credit risk contagion model based on asymmetric information association is proposed. The model can effectively describe the correlation among individuals with credit risk. The model can analyze how the risk individuals are infected in the network and can effectively reflect the risk contagion degree of the individual. This paper further analyzes the influence of network structure, information association, individual risk attitude, financial market supervision intensity, and individual risk resisting ability on individual risk contagion. The correctness of the model is verified by theoretical deduction and numerical simulation.

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Contagion in the Interbank Network: An Epidemiological Approach

Cited by 40 publications

References 70 publications

Epidemics of liquidity shortages in interbank markets

Epidemics of liquidity shortages in interbank markets

Real and financial crises in the Keynes–Kalecki structuralist model: An agent‐based approach

Credit Risk Contagion Based on Asymmetric Information Association

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