High-performance Algorithmic Trading using Machine Learning : Building automated trading strategies with AutoML and feature engineering (English Edition)
Description: Machine learning is not just an advantage; it is becoming standard practice among top-performing trading firms. As traditional strategies struggle to navigate noise, complexity, and speed, ML-powered systems extract alpha by identifying transient patterns beyond human reach. This shift...
में बचाया:
| मुख्य लेखक: | |
|---|---|
| स्वरूप: | Livre numérique |
| भाषा: | Anglais |
| प्रकाशित: |
New Delhi :
BPB Publications
2025.
Paris : Cyberlibris |
| ऑनलाइन पहुंच: | Accès Université d'Orléans et IFPM |
| टिप्पणी: |
Couverture. https://static2.cyberlibris.com/books_upload/300pix/9789365893892.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • High-performance Algorithmic Trading using Machine Learning, Building automated trading strategies with AutoML and feature engineering (English Edition), Franck Bardol, New Delhi, BPB Publications, 2025, 1 vol. (455 p.), 978-93-6589-389-2 |
विषय - सूची:
- 1. Algorithmic Trading and Machine Learning in a Nutshell
- 2. Data Feed, Backtests, and Forward Testing
- 3. Optimizing Trading Systems, Metrics, and Automated Reporting
- 4. Implement Trading Strategies
- 5. Supervised Learning for Trading Systems
- 6. Improving Model Capability with Features
- 7. Advanced Machine Learning Models for Trading
- 8. AutoML and Low-Code for Trading Strategies
- 9. Unsupervised Learning Methods for Trading
- 10. Unsupervised Learning with Pattern Matching
- 11. Trading Signals from Reports and News
- 12. Advanced Unsupervised Learning, Anomaly Detection, and Association Rules
- Appendix: APIs and Libraries for each chapter