Advances in credit risk management : extensions of the Basel ASRF framework and LGD empirical insights
(2024)
Files
Doctoral_Thesis_Matteo_Barbagli_Printed_Online.pdf
Restricted Access - Adobe PDF
- 4.47 MB
Details
- Authors
- Supervisors
- Vrins, Frédéric
- Abstract
- This doctoral thesis addresses three critical challenges in credit risk modelling and quantitative finance within the scope of the Basel banking regulations. The goal is to propose models and conduct inference studies to enhance the simplicity, comparability and risk-sensitivity of capital requirements. The first two research projects focus on addressing two limitations of the loss model underlying capital requirements for credit risk, specifically the asymptotic single risk-factor model. Extensions to the current setup are proposed to capture unaddressed risks by introducing a PD-LGD dependency and quantitatively measuring credit concentration risk. These methodological contributions have multiple applications, including calculating economic capital, assessing model risk, and pricing and managing mortgage-backed securities, thereby contributing to the broader financial literature. The final project identifies novel determinants of one of the central risk parameters for capital adequacy of large internationally active banks: the loss given default (LGD). By introducing CDS-based indices, the research provides valuable insights into sector-specific uncertainties, contributing to the explanation of corporate bond recovery rates. Collectively, these contributions aim to improve the Basel framework's accuracy and transparency, helping to strengthen regulatory practices supporting global financial stability.
- Affiliations
UCLouvain SSH/LIDAM/LFIN - Louvain Finance
Citations
Barbagli, M. (2024). Advances in credit risk management : extensions of the Basel ASRF framework and LGD empirical insights. https://hdl.handle.net/2078.5/233213