Enhancing quantitative trading systems through alternative data
Marcoccia, Andrea (A.A. 2024/2025) Enhancing quantitative trading systems through alternative data. Tesi di Laurea in Data-driven models for investment, Luiss Guido Carli, relatore Antonio Simeone, pp. 26. [Master's Degree Thesis]
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Abstract/Index
Literature review. Systematic trading: history, users, performance metrics. Genetic algorithm optimization: fundamentals and applications. Alternative data in finance: definitions, evolution, empirical impact. The quantitative trading framework. Overall architecture & philosophy. Stock selection. Quantitative trading system. GA-based optimization. The ensemble approach. Training and validation framework. Performance. Transaction data trading system. Bloomberg second measure transaction data. Feature engineering. Ranking-based long-short strategy. Ensemble system. Strategy.
References
Bibliografia: p. 26.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | Data-driven models for investment |
| Thesis Supervisor: | Simeone, Antonio |
| Thesis Co-Supervisor: | Italiano, Giuseppe Francesco |
| Academic Year: | 2024/2025 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 21 Oct 2025 10:21 |
| Last Modified: | 21 Oct 2025 10:21 |
| URI: | https://tesi.luiss.it/id/eprint/43430 |
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