This paper employs a computational model of solvency and liquidity contagion assessing the vulnerability of banks to systemic risk. We find that the main risk drivers relate to the financial connections a bank has and the market concentration, apart from the size of the bank triggering the contagion, while balance sheets play only a minor role. We also find that market concentration might facilitate banks to withstand liquidity shocks better while exposing them to larger solvency chocks. Our results are validated through an out-of-sample forecasting that shows that both type I and type II prediction errors are reduced if we include network characteristics in our prediction model.
|Number of pages||11|
|Journal||IEEE Transactions on Emerging Topics in Computational Intelligence|
|Early online date||23 May 2018|
|Publication status||Published - 30 Jun 2018|
- interbank loans
- network topology
- banking crises
- systemic risk
- systemic crisis
- bank failure
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- Management - Lecturer (Assistant Professor)
- Accounting, Finance & Law
- Centre for Governance, Regulation and Industrial Strategy
Person: Research & Teaching