Prediction of a low risk portfolio with a random forest application

Squillaci, Mario Umberto (A.A. 2019/2020) Prediction of a low risk portfolio with a random forest application. Tesi di Laurea in Asset pricing, Luiss Guido Carli, relatore Paolo Porchia, pp. 145. [Master's Degree Thesis]

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Abstract/Index

The modern portfolio theory. Fundamentals. The history in a nutshell. Portfolio choice. Mean variance optimization. Minimum variance portgolios. Intertemporal function. Implementation of the Markowitz theories. Overview. The CAPM. Black e Litterman. An introduction to artificail intelligence and machine learning. Artificial intelligence. Machine learning. Training and performance valuation. Decision trees. Random forest. Analysis. Portfolio.

References

Bibliografia: pp. 83-85.

Thesis Type: Master's Degree Thesis
Institution: Luiss Guido Carli
Degree Program: Master's Degree Programs > Master's Degree program in Corporate Finance, English language (LM-77)
Chair: Asset pricing
Thesis Supervisor: Porchia, Paolo
Thesis Co-Supervisor: Pirra, Marco
Academic Year: 2019/2020
Session: Autumn
Deposited by: Alessandro Perfetti
Date Deposited: 06 May 2021 13:56
Last Modified: 06 May 2021 13:56
URI: https://tesi.luiss.it/id/eprint/29384

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