Forecasting financial returns using machine learning methods
Khazen, Charbel (A.A. 2022/2023) Forecasting financial returns using machine learning methods. Tesi di Laurea in Asset pricing, Luiss Guido Carli, relatore Nicola Borri, pp. 135. [Master's Degree Thesis]
|
PDF (Full text)
Download (3MB) | Preview |
Abstract/Index
Underlying theory and rationale. Theoretical framework. Necessity for machine learning methods. Methodology. Underlying machine learning theory. Statistical learning theory. L1, L2 and elastic net regularizations. Regularization and overfitting. Regularization and ill-posedness. Dimension reduction methods. Principal component analysis. Independent component analysis. Robust linear estimation. Numerical methods. Generalized additive models. Regression trees. Ensemble methods. Predictive evaluation metrics.
References
Bibliografia: pp. 133-135.
| 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: | Asset pricing |
| Thesis Supervisor: | Borri, Nicola |
| Thesis Co-Supervisor: | Patnaik, Megha |
| Academic Year: | 2022/2023 |
| Session: | Extraordinary |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 28 Aug 2024 14:42 |
| Last Modified: | 28 Aug 2024 14:42 |
| URI: | https://tesi.luiss.it/id/eprint/39466 |
Downloads
Downloads per month over past year
Repository Staff Only
 |
View Item |
