Abstract
The paper investigates the importance of banks’ business classification in shaping the risk profile of financial institutions on a global scale. We employ a rare-event logit model based on a state-of-the-art list of major global distress events from the global financial crisis. When clustering banks by their business strategies using a community detection approach, we show that (i) capital enhanced resilience only for traditional banks that were on average less capitalized than other banks; (ii) boosting ROE, usually associated with riskier exposures, improved resilience for stable funded and asset diversified banks; (iii) conversely, higher levels of ROA exacerbated banks’ vulnerability when associated with concentrated (not-diversified) investment structures; (iv) size in terms of total assets contributed to instability only for wholesale-funded institutions due to their high levels of unstable funding. Liquidity, on the contrary, reduced the institution likelihood of being in distress, regardless of its business classification. Although our findings refer to the recent financial crisis, they provide evidence that a tailored risk monitoring based on a proper peer group identification can facilitate banks’ distresses prediction.
Original language | English |
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Pages (from-to) | 1-50 |
Number of pages | 50 |
Journal | Annals of Operations Research |
Early online date | 24 Sep 2019 |
DOIs | |
Publication status | E-pub ahead of print - 24 Sep 2019 |
Keywords
- Bank business strategies
- Bank distress
- Clustering
- Financial crisis
ASJC Scopus subject areas
- Decision Sciences(all)
- Management Science and Operations Research
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Profiles
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Simone Giansante
- Management - Lecturer (Assistant Professor)
- Accounting, Finance & Law
- Centre for Governance, Regulation and Industrial Strategy
Person: Research & Teaching