Agent Simulation of Chain Bankruptcy

TL;DR

This paper presents an agent-based simulation model for chain bankruptcy propagation in financial networks, using real data from Japanese firms to identify high-risk links and improve bankruptcy risk management.

Contribution

It introduces a novel agent-based model that estimates parameters from real financial data to simulate and analyze chain bankruptcy propagation.

Findings

Successfully modeled chain bankruptcy propagation on real transaction networks.

Identified high-risk links in financial networks for better risk management.

Demonstrated the model's potential for predicting and preventing large-scale bankruptcies.

Abstract

We have conducted an agent-based simulation of chain bankruptcy. The propagation of credit risk on a network, i.e., chain bankruptcy, is the key to nderstanding largesized bankruptcies. In our model, decrease of revenue by the loss of accounts payable is modeled by an interaction term, and bankruptcy is defined as a capital deficit. Model parameters were estimated using financial data for 1,077 listed Japanese firms. Simulations of chain bankruptcy on the real transaction network consisting of those 1,077 firms were made with the estimated model parameters. Given an initial bankrupt firm, a list of chain bankrupt firms was obtained. This model can be used to detect high-risk links in a transaction network, for the management of chain bankruptcy.