ABBA: An Agent-Based Model of the Banking System

June 9, 2017

Preview Citation

Format: Chicago

Jorge A Chan-Lau. ABBA: An Agent-Based Model of the Banking System, (USA: International Monetary Fund, 2017) accessed September 19, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

A thorough analysis of risks in the banking system requires incorporating banks’ inherent heterogeneity and adaptive behavior in response to shocks and changes in business conditions and the regulatory environment. ABBA is an agent-based model for analyzing risks in the banking system in which banks’ business decisions drive the endogenous formation of interbank networks. ABBA allows for a rich menu of banks’ decisions, contingent on banks’ balance sheet and capital position, including dividend payment rules, credit expansion, and dynamic balance sheet adjustment via risk-weight optimization. The platform serves to illustrate the effect of changes on regulatory requirements on solvency, liquidity, and interconnectedness risk. It could also constitute a basic building block for further development of large, bottom-up agent-based macro-financial models.

Subject: Asset and liability management, Banking, Capital adequacy requirements, Commercial banks, Financial institutions, Financial regulation and supervision, Liquidity, Loans, Monetary policy, Reserve requirements

Keywords: Agent-based model, Banks, Capital adequacy requirements, Commercial banks, Creditor bank share, Excess reserves, Experiences default, Financial stability, Insolvent creditor bank, Interbank loan, Interconnectedness, Interest bank, Lending bank, Liquidation loss, Liquidity, Loan portfolio, Loans, NetLogo, Regulation, Reserve requirements, Return on equity, Solvency, WP

Publication Details

Pages:

33
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2017/136
Stock No:

WPIEA2017136
ISBN:

9781484300688
ISSN:

1018-5941

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