Reinforcement learning techniques for optimal control in financial markets
Passarello, Pietro (A.A. 2022/2023) Reinforcement learning techniques for optimal control in financial markets. Tesi di Laurea in Empirical finance, Luiss Guido Carli, relatore Antonio Simeone, pp. 130. [Master's Degree Thesis]
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Abstract/Index
Technical background. Markov decision processes. Dynamic programming. Prediction and control with reinforcement learning. Approximate solution methods. Function approximation. Policy gradient methods. Actor-critic methods. Methodology. The model. Data processing. Performance measures. Results.
References
Bibliografia: pp. 111-114.
| 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: | Empirical finance |
| Thesis Supervisor: | Simeone, Antonio |
| Thesis Co-Supervisor: | Marzioni, Stefano |
| Academic Year: | 2022/2023 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 07 Jun 2024 12:32 |
| Last Modified: | 07 Jun 2024 12:32 |
| URI: | https://tesi.luiss.it/id/eprint/38793 |
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