Modeling Bank Systemic Risk of Emerging Markets under Geopolitical Shocks: Empirical Evidence from BRICS Countries
Haibo Wang

TL;DR
This paper introduces BRIDGES, a comprehensive framework combining network analysis, trend detection, neural networks, and agent-based simulations to assess systemic risk in BRICS banks under geopolitical shocks.
Contribution
It develops a novel multi-method framework, including dynamic graph modeling and agent-based simulations, to evaluate systemic risk and resilience of BRICS banking systems.
Findings
Failure of large BRICS banks causes significant systemic damage.
Geopolitical shocks can lead to near-total systemic collapse.
Traditional risk models may not detect threats from large bank failures or geopolitical shocks.
Abstract
In this study, we introduce an analytics framework, the Bank Risk Interlinkage with Dynamic Graph and Event Simulations (BRIDGES), to capture the systemic risks associated with the growing economic influence of the BRICS nations. This framework includes a Dynamic Time Warping (DTW) method to construct a dynamic network of 551 BRICS banks with their annual balance sheet data from 2008 to 2024; a trend analysis in risk ratios to detect shifts in banks' behavior; a Temporal Graph Neural Network (TGNN) to detect anomalous changes in the bank network's structural relationships; and Agent-Based Model (ABM) simulations to measure the impact of anomalous changes on network stability and assess the banking system's resilience to internal financial failure and external geopolitical shocks at the individual country level and across BRICS nations. Our simulation results highlight several important…
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