Bankruptcy Cascades in Interbank Markets

Tedeschi, Gabriele; Mazloumian, Amin; Gallegati, Mauro; Helbing, Dirk

doi:10.1371/journal.pone.0052749

Cited by 74 publications

(48 citation statements)

References 61 publications

(23 reference statements)

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“…Agent-based models, on the other hand, have been used to explic-itly investigate the propagation of bankruptcies in the financial system (see e.g. Battiston et al, 2009;Tedeschi et al, 2011;Lenzu and Tedeschi, 2012;Markose et al, 2012). When allowing for more than one agent, heterogeneity enters a model.…”

Section: Literature Reviewmentioning

confidence: 99%

Prices, debt and market structure in an agent-based model of the financial market

Fischer

Riedler

2014

Journal of Economic Dynamics and Control

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Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW. Non-technical SummaryIn this paper we develop an agent-based model of the financial market. Agent-based modeling is a simulation-based technique that is gaining popularity in economics. In an agent-based model autonomously acting and interacting units (e.g. representing financial market participants) endogenously generate structures and system properties which become subject to analysis. In contrast to conventional equilibrium models, agent-based models prominently take into account mutual dependencies between agents and feedback processes.In our model boundedly rational agents trade a financial asset. Their trading strategy thereby depends on their return forecast which is formed by either considering fundamentals or technical analysis. This setup is well established in the literature and has been exceptionally successful in reproducing several stylized facts of financial asset price time series. With our model we analyze the behavior of a large number of heterogeneous agents. The heterogeneity can predominantly be attributed to differing trading strategies and the ensuing divergence in the structure of agents' balance sheets. The balance sheet aspect of the financial markets has been largely neglected in extant literature.Specifically, we endow each agent with a balance sheet comprising of a risky asset and cash on the asset side and equity capital and debt on the liabilities side. The risky asset is traded among agents at an endogenously set price. We assume that agents actively manage their respective balance sheet in two regards. Firstly, they choose a portfolio which optimizes the ratio between risky assets and cash conditional on their current return forecast, and secondly they aim at a fixed ratio between equity and debt (leverage ratio). Agents are constrained in their ability to acquire and dispose of debt by the credit supply of a risk managing financier and credit frictions, which hinder agents to make immediate changes to their debt levels.We simulate our model and show that it can reproduce several empirically observable facts and relationships. Although we initially endow all agents with identical balance sheets, the size distribution of agents quickly converges to a lognormal distribution, which is typically observed for investment banks. We furthermore observe a natural tendency for inequality to increase over time. When we impose low credit frictions on the model financial market, leverage becomes procyclical, which is also typical for investme...

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Section: Literature Reviewmentioning

confidence: 99%

Prices, debt and market structure in an agent-based model of the financial market

Fischer

Riedler

2014

Journal of Economic Dynamics and Control

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“…Thus, the probability that a link exists between a pair of banks is equal to the fitted probability from the logit regression (Vandenbossche et al 2013;Tedeschi et al 2012 andTedeschi et al 2014). The parameter β ∈ [0, ∞] in Eq.…”

Section: The Interbank Credit Relationships: a Dynamic Network Approachmentioning

confidence: 99%

“…Indeed, when the agents' balance sheets are heterogeneous, banks are not uniformly exposed to their counter-party. Therefore, if contagion is triggered by the failure of a big bank, which represents the highest source of exposure for its creditors, the situation is certainly worse than when agents are homogeneous (see Iori et al 2006;Caccioli et al 2012; Lenzu and Tedeschi 2012;Tedeschi et al 2012). On the other hand, the probability of default in credit markets is strictly linked to the presence of highly leveraged agents (see Gonzalez 2013;Gonzalez and Gonzalez 2014).…”

Section: Introductionmentioning

confidence: 99%

From banks' strategies to financial (in)stability

Berardi

Tedeschi

2017

International Review of Economics & Finance

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This paper aims to shed light on the emergence of systemic risk in credit systems. By developing an interbank market with heterogeneous financial institutions granting loans on different network structures, we investigate which market architecture is more resilient to liquidity shocks and how the risk spreads over the modeled system. In our model, credit linkages evolve endogenously via a fitness measure based on different banks' strategies. Each financial institution, in fact, applies a strategy based on a low interest rate, a high supply of liquidity or a combination of them. Interestingly, the choice of the strategy influences both the banks' performance and the network topology. In this way, we are able to identify the most effective tactics adapt to contain contagion and the corresponding network topology. Our analysis shows that, when financial institutions combine the two strategies, the interbank network does not condense and this generates the most efficient scenario in case of shocks.

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“…The conceptual framework employed draws heavily from Takahashi and Okada (2003) and Tedeschi et al (2012). For tractability, we adopt a parsimonious approach that drifts away from fully specified models such as the Eurace project (Raberto et al, 2012;.…”

Section: Introductionmentioning

confidence: 99%

Prudential Regulation in an Artificial Banking System

Quinaz

Curto

2016

Economics

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This study is an exploratory analysis of the economic role of banks under different prudential frameworks. It considers an agent-based computational model populated by consumers, firms, banks, and a central bank whose out-of-equilibrium interactions replicate the conjunct dynamics of a banking system, a financial market and the real economy. A calibrated version of the model is shown to provide an intelligible account of several recurring economic phenomena, thus constituting a favorable ground for policy analysis. The investigation provides a valuable methodological contribution to the field of banking research and sheds new light on the role of banks and their prudential regulation. Specifically, the results suggest that banks are key economic agents. Through their financial intermediation activity, credit institutions facilitate investment and promote growth. JEL C63 G28

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Bankruptcy Cascades in Interbank Markets

Cited by 74 publications

References 61 publications

Prices, debt and market structure in an agent-based model of the financial market

Prices, debt and market structure in an agent-based model of the financial market

From banks' strategies to financial (in)stability

Prudential Regulation in an Artificial Banking System

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