Systemic crises and international finance: an econometric and machine learning approach
Panfilo, Matteo (A.A. 2019/2020) Systemic crises and international finance: an econometric and machine learning approach. Tesi di Laurea in Advanced financial economics, Luiss Guido Carli, relatore Paolo Porchia, pp. 233. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Theoretical framework. Theories of financial crises, the role of money, investments. The open economy case, some basic concepts. Literature review. A brief history of EWS. Machine learning approaches. Credit booms gone bust. Methodology. Notes on method and strategic assessments. Credit booms detection. The multinomial logit model. Specifications. Machine learning algorithms. Data. Credit time series and dependent variable definition. Covariates: sources, computations, availability. Different specifications. Dealing with multicollinearity. Results. Logistic regressions. Machine learning algorithms. Event analysis.
References
Bibliografia: pp. 145-149.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Economics and Finance (LM-56) |
| Chair: | Advanced financial economics |
| Thesis Supervisor: | Porchia, Paolo |
| Thesis Co-Supervisor: | Santucci de Magistris, Paolo |
| Academic Year: | 2019/2020 |
| Session: | Extraordinary |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 05 Jul 2021 11:19 |
| Last Modified: | 05 Jul 2021 11:20 |
| URI: | https://tesi.luiss.it/id/eprint/29976 |
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