Scianetti, Elettra (A.A. 2024/2025) Challenging the efficient market hypothesis: asset allocation by sophisticated investors during financial bubbles, evidence from the AI boom. Tesi di Laurea in Econometric theory, Luiss Guido Carli, relatore Paolo Santucci de Magistris, pp. 127. [Master's Degree Thesis]

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Abstract/Index

Literature review. Hegde funds. Financial bubbles. Sophisticated investors’ exposure to bubble assets. The AI market bubble. Signs of overvaluation. Kindleberger-Minsky model. Global investment artificial intelligence. US investment in artificial intelligence. Data and variables construction. Data and data sources. Variables construction. Exploratory data analysis. Methodology. Factor-based performance attribution. Implied AI weight for an average hedge fund’s portfolio. Alpha testing. Results. Factor-based performance attribution. Implied AI weight for an average hedge fund’s portfolio.

References

Bibliografia: pp. 89-93.

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:	Econometric theory
Thesis Supervisor:	Santucci de Magistris, Paolo
Thesis Co-Supervisor:	Cybo, Ottone Alberto
Academic Year:	2024/2025
Session:	Extraordinary
Deposited by:	Alessandro Perfetti
Date Deposited:	14 Jul 2026 12:45
Last Modified:	14 Jul 2026 12:45
URI:	https://tesi.luiss.it/id/eprint/46388

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