Interbank Market Formation through Reinforcement Learning and Risk Aversion

30 Pages Posted: 29 Jun 2017 Last revised: 26 Jul 2017

See all articles by Anqi Liu

Anqi Liu

Cardiff University - School of Mathematics

Cheuk Yin Mo

Stevens Institute of Technology - School of Business

Mark E. Paddrik

Government of the United States of America - Office of Financial Research

Steve Y. Yang

Stevens Institute of Technology

Date Written: June 29, 2017

Abstract

In this study, we propose a multi-agent model to examine bank lending and borrowing risk behaviors and their implications to interbank market dynamics. Using data from 2001 to 2014 that covers around U.S. 6600 banks, we model individual bank decisions using the temporal difference reinforcement learning algorithm based on banks’ lending preferences and environment, and we then generate the interbank market dynamics from the empirical data. This dynamic model allows us to construct interbank networks as they change with bank risk preferences, and thus facilitates the analysis of the banking systems stability. The model successfully replicates the key characteristics of interbank lending and borrowing relationships that have been documented in the recent literature. A key finding of this study is that the risk aversion choice of individual bank leads to unique interbank market structures that suggest the macro risk preference of the market. Combined with the use of balance sheet data, this modeling framework helps central banks and regulators building more functional models for examining the interbank market stability problems.

Keywords: Interbank Lending Market, Contagion Risk, Multi-Agent System, Reinforcement Learning Agent

JEL Classification: D85, G17, G21, L14

Suggested Citation

Liu, Anqi and Mo, Cheuk Yin and Paddrik, Mark Endel and Yang, Steve Y., Interbank Market Formation through Reinforcement Learning and Risk Aversion (June 29, 2017). Stevens Institute of Technology School of Business Research Paper. Available at SSRN: https://ssrn.com/abstract=2994585 or http://dx.doi.org/10.2139/ssrn.2994585

Anqi Liu

Cardiff University - School of Mathematics ( email )

Senghennydd Road
Cardiff, CF24 4AG
United Kingdom

Cheuk Yin Mo

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States

Mark Endel Paddrik

Government of the United States of America - Office of Financial Research ( email )

717 14th Street, NW
Washington DC, DC 20005
United States

Steve Y. Yang (Contact Author)

Stevens Institute of Technology ( email )

Hoboken, NJ 07030
United States

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