Extending the portfolio optimization problem with multi-objective evolutionary algorithms in Python: an application on sustainable finance
Precicchiani, Simone (A.A. 2021/2022) Extending the portfolio optimization problem with multi-objective evolutionary algorithms in Python: an application on sustainable finance. Tesi di Laurea in Asset pricing, Luiss Guido Carli, relatore Pierluigi Murro, pp. 39. [Master's Degree Thesis]
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Abstract/Index
Literature review. Modern portfolio theory. Multi-criteria portfolio optimization. Methods. Traditional portfolio optimization. Generalized portfolio optimization problem. Multi-objective evolutionary algorithms to solve multi-criteria decisionmaking problems. Sustainability criterion. Empirical analysis. Dataset. Optimization problem implementation in Python. Non-dominated surface result (Pareto front). Comparison with traditional optimization and ESG optimization.
References
Bibliografia: pp. 32-34.
| 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: | Murro, Pierluigi |
| Thesis Co-Supervisor: | Borri, Nicola |
| Academic Year: | 2021/2022 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 27 Feb 2023 09:02 |
| Last Modified: | 27 Feb 2023 09:02 |
| URI: | https://tesi.luiss.it/id/eprint/35214 |
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