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Interbank Contagion: An Agent-based Model Approach to Endogenously Formed Networks

Anqi Liu (), Mark Paddrik, Steve Yang () and Xingjia Zhang ()
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Anqi Liu: Stevens Institute of Technology
Steve Yang: Stevens Institute of Technology
Xingjia Zhang: Stevens Institute of Technology

No 16-14, Working Papers from Office of Financial Research, US Department of the Treasury

Abstract: The potential impact of interconnected financial institutions on interbank financial systems is a financial stability concern for central banks and regulators. A number of algorithms/methods have been developed to extrapolate latent interbank risk exposures. However, most use highly stylized network models and reconstruction methods with global optimality lending allocation approaches such as maximizing entropy or minimizing costs. This paper argues that U.S. bank lending and borrowing decisions are largely suboptimal and performance-driven. We present an agent-based model to endogenously reconstruct interbank networks based on 6,600 banks' decision rules and behaviors reflected in quarterly balance sheets. The model formulation reproduces dynamics similar to those of the 2007-09 financial crisis and shows how bank losses and failures arise from network contagion and lending market illiquidity. When calibrated to post-crisis data from 2011-14, the model shows the banking system has reduced its likelihood of bank failures through network contagion and illiquidity, given a similar stress scenario.

Keywords: Interbank lending market; agent-based simulation; contagion risk; network topology; financial crisis (search for similar items in EconPapers)
Pages: 39 pages
Date: 2016-12-20
New Economics Papers: this item is included in nep-cmp, nep-hme and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link) ... ion-ABM-Approach.pdf First version, 2016 (application/pdf)

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Journal Article: Interbank contagion: An agent-based model approach to endogenously formed networks (2020) Downloads
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