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Open AccessFeature PaperArticle

An Agent-Based Approach to Interbank Market Lending Decisions and Risk Implications

1
School of Mathematics, Cardiff University, Cardiff CF10 3AT, UK
2
School of Business, Stevens Institute of Technology, Hoboken, NJ 07030, USA
3
Office of Financial Research, US Department of Treasury, 717 14th Street, NW Washington, DC 20220, USA
*
Author to whom correspondence should be addressed.
Information 2018, 9(6), 132; https://doi.org/10.3390/info9060132
Received: 1 April 2018 / Revised: 16 May 2018 / Accepted: 26 May 2018 / Published: 29 May 2018
(This article belongs to the Special Issue Agent-Based Artificial Markets)
In this study, we examine the relationship of bank level lending and borrowing decisions and the risk preferences on the dynamics of the interbank lending market. We develop an agent-based model that incorporates individual bank decisions using the temporal difference reinforcement learning algorithm with empirical data of 6600 U.S. banks. The model can successfully replicate the key characteristics of interbank lending and borrowing relationships documented in the recent literature. A key finding of this study is that risk preferences at the individual bank level can lead to unique interbank market structures that are suggestive of the capacity with which the market responds to surprising shocks. View Full-Text
Keywords: interbank market; contagion risk; multi-agent system; reinforcement learning agents interbank market; contagion risk; multi-agent system; reinforcement learning agents
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Liu, A.; Mo, C.Y.J.; Paddrik, M.E.; Yang, S.Y. An Agent-Based Approach to Interbank Market Lending Decisions and Risk Implications. Information 2018, 9, 132.

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