Advancing the Merton model: the impact of deep learning–based volatility on probability of default
Micci Battaglini, Alessandro (A.A. 2023/2024) Advancing the Merton model: the impact of deep learning–based volatility on probability of default. Tesi di Laurea in Advanced corporate finance, Luiss Guido Carli, relatore Pierluigi Murro, pp. 56. [Master's Degree Thesis]
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Abstract/Index
Literature review. Structural approach. Reduced–form approach. Incomplete–information approach. Methodology and data. Application of the Merton model. Data. Variables estimation. Long short–term memory model. Results. Data visualization. Merton models evaluation. LSTM model evaluation.
References
Bibliografia: pp. 49-50.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree program in Corporate Finance, English language (LM-77) |
| Chair: | Advanced corporate finance |
| Thesis Supervisor: | Murro, Pierluigi |
| Thesis Co-Supervisor: | Santella, Rosella |
| Academic Year: | 2023/2024 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 29 Apr 2025 10:43 |
| Last Modified: | 29 Apr 2025 10:43 |
| URI: | https://tesi.luiss.it/id/eprint/41891 |
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