Efficient portfolio allocation: reinforcement learning methods applied to modern finance
Del Nobile, Federico (A.A. 2020/2021) Efficient portfolio allocation: reinforcement learning methods applied to modern finance. Tesi di Laurea in Artificial intelligence and machine learning, Luiss Guido Carli, relatore Marco Querini, pp. 67. [Bachelor's Degree Thesis]
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Abstract/Index
Reinforcement learning and finance. The efficient porfolio allocation problem. Reinforcement learning applications. RL general applications. RL finance applications. RL definitions and models. General RL definitions. Models applied. Efficient portfolio allocation. Problem formulation. An introduction to practice. Implementation. The stock market. The bonds market. The cryptocurrencies market. Results discussion. Web App. Introduction and motivations. User experience and inner functioning. Further developments.
References
Bibliografia: pp. 66-67.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Artificial intelligence and machine learning |
| Thesis Supervisor: | Querini, Marco |
| Academic Year: | 2020/2021 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 22 Oct 2021 08:21 |
| Last Modified: | 22 Oct 2021 08:21 |
| URI: | https://tesi.luiss.it/id/eprint/30509 |
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