ESG and corporate profitability: forecasting EBITDA with ESG scores, through a random forest algorithm
Mantoan, Filippo (A.A. 2024/2025) ESG and corporate profitability: forecasting EBITDA with ESG scores, through a random forest algorithm. Tesi di Laurea in Quantitative methods in strategic management, Luiss Guido Carli, relatore Francesco Morelli, pp. 63. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Literature review. ESG adoption and investment styles: what the literature shows. ESG performance, firm value and profitability. Corporate social responsibility. ESG. Analysis structure. Data sample. Methodology. Descriptive outputs. Empirical analysis. Random forest implementation. Variables importance. Cross-industry patterns. Robustness checks.
References
Bibliografia: pp. 60-63.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Strategic Management (LM-77) |
| Chair: | Quantitative methods in strategic management |
| Thesis Supervisor: | Morelli, Francesco |
| Thesis Co-Supervisor: | Angelucci, Davide |
| Academic Year: | 2024/2025 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 09 Jun 2026 14:23 |
| Last Modified: | 09 Jun 2026 14:23 |
| URI: | https://tesi.luiss.it/id/eprint/46137 |
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