Nuclear energy as future infrastructure for artificial intelligence: evidence from US electric utilities
Paschos Gricia, Gabriele Kamran (A.A. 2024/2025) Nuclear energy as future infrastructure for artificial intelligence: evidence from US electric utilities. Tesi di Laurea in Sustainable finance, Luiss Guido Carli, relatore Dominik Damast, pp. 45. [Master's Degree Thesis]
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Abstract/Index
The energy constraint of artificial intelligence. The strategic relevance of nuclear energy in the AI era. Research objectives and research questions. Literature review. The compute–energy constraint of artificial intelligence. Energy transitions and the role of firm low-carbon Capa. Nuclear energy as capital-intensive infrastructure. Asset pricing of utilities and infrastructure firms. Investor attention, expectations and google trends. Data and methodology. Firm classification. Equity data and return construction. Portfolio construction. Fama–French three-factor regression framework. Performance metrics. Google trends and attention-based analysis. Empirical results. Descriptive performance of portfolios. Fama–French three-factor results. Attention regimes and google trends evidence.
References
Bibliografia: pp. 33-35.
| 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: | Sustainable finance |
| Thesis Supervisor: | Damast, Dominik |
| Thesis Co-Supervisor: | Boido, Claudio |
| Academic Year: | 2024/2025 |
| Session: | Extraordinary |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 16 Jun 2026 14:23 |
| Last Modified: | 16 Jun 2026 14:23 |
| URI: | https://tesi.luiss.it/id/eprint/46179 |
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