Modeling Bank Systemic Risk of Emerging Markets under Geopolitical Shocks: Empirical Evidence from BRICS Countries
Fuente:
arXiv
Saved in:
| Main Author: | |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908965549375488 |
|---|---|
| author | Wang, Haibo |
| author_facet | Wang, Haibo |
| contents | 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 insights. The failure of the largest BRICS banks can cause more systemic damage than that of financially vulnerable or anomalous banks due to the panic effects. Moreover, compared to the failure of the largest BRICS banks, a geopolitical shock with correlated country-wide propagation can cause more systemic damage, resulting in a near-total systemic collapse. Our findings suggest that the panic over the failure of the largest BRICS banks and large-scale geopolitical shocks are the primary threats to the financial stability of the BRICS nations, which traditional bank risk analysis models might not detect. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_20515 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Modeling Bank Systemic Risk of Emerging Markets under Geopolitical Shocks: Empirical Evidence from BRICS Countries Wang, Haibo Computational Finance Econometrics Risk Management 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 insights. The failure of the largest BRICS banks can cause more systemic damage than that of financially vulnerable or anomalous banks due to the panic effects. Moreover, compared to the failure of the largest BRICS banks, a geopolitical shock with correlated country-wide propagation can cause more systemic damage, resulting in a near-total systemic collapse. Our findings suggest that the panic over the failure of the largest BRICS banks and large-scale geopolitical shocks are the primary threats to the financial stability of the BRICS nations, which traditional bank risk analysis models might not detect. |
| title | Modeling Bank Systemic Risk of Emerging Markets under Geopolitical Shocks: Empirical Evidence from BRICS Countries |
| topic | Computational Finance Econometrics Risk Management |
| url | https://arxiv.org/abs/2512.20515 |