Publicação
Systemic risk in the U.S. banking sector during the Silicon Valley bank collapse: a neural network analysis
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.advisor | Eisert, Tim | |
| dc.contributor.author | Hasenkamp, Moritz Viktor Friedrich Wilhelm | |
| dc.date.accessioned | 2025-04-02T08:33:19Z | |
| dc.date.available | 2025-04-02T08:33:19Z | |
| dc.date.issued | 2025-01-22 | |
| dc.date.submitted | 2025-01-22 | |
| dc.description.abstract | The collapse of Silicon Valley Bank in 2023 exposed significant systemic risks, particularly for commercial and regional bank. This study analyzes 125 banks, categorized by size, to evaluate their contributions to systemic risks using a neural network quantile regression with Value-at-Risk and Conditional Value-at-Risk metrics. Results show that large banks remained stable, reflecting effective regulation, while commercial and regional banks experienced sharp increases in systemic risks. The findings highlight the need for enhanced supervision of smaller banks to mitigate their vulnerability to external shocks and prevent broad financial instability. The Banks with a dual risk of high vulnerability and risk exposure for the system are identified as key drivers of systemic risk. | pt_PT |
| dc.identifier.tid | 203926722 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/181813 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Systemic risk | pt_PT |
| dc.subject | Neural networks | pt_PT |
| dc.subject | Quantile regression | pt_PT |
| dc.subject | CoVar | pt_PT |
| dc.title | Systemic risk in the U.S. banking sector during the Silicon Valley bank collapse: a neural network analysis | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a master’s degree in finance from the Nova School of Business and Economics | pt_PT |