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

Anqi Liu,Steve Yang,Cheuk Mo,Mark Paddrik

doi:10.3390/info9060132

Abstract

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.

Highlights

Prior to the financial crisis in 2008, central banks and market regulators were primarily concerned with banks’ performance through a microprudential lens, examining individual banks’ assets and liability portfolios to control risk [1,2]
The primary contribution of this study is to develop a heterogeneous multi-agent computational model to reconstruct the banking system based on banks’ behavioral patterns and to understand how banks’ risk preference can influence the interbank market structures
We study the effectiveness of applying the temporal difference (TD) (0) method in a complex interbank network environment

Summary

Introduction

Prior to the financial crisis in 2008, central banks and market regulators were primarily concerned with banks’ performance through a microprudential lens, examining individual banks’ assets and liability portfolios to control risk [1,2] While this perspective has been commonly used to identify problematic banks, it does not consider the contagion effects of troubled banks. Liquidity hoarding occurs when banks are reluctant to lend out excess liquidity due to adverse selection of borrowers and the increasing uncertainty on assessing the counterparty credit risks. It leads to a domino effect of banks collapsing due to insolvency

Methods

Findings

Discussion

Conclusion