Foundations of Reinforcement Learning with Applications in Finance
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ISBN-13:
9781032124124
Veröffentl:
2022
Erscheinungsdatum:
16.12.2022
Seiten:
500
Autor:
Ashwin Rao
Gewicht:
1082 g
Format:
260x187x35 mm
Sprache:
Englisch
Beschreibung:
This book demystifies Reinforcement Learning, and makes it a practically useful tool for those studying and working in applied areas, especially finance. This book seeks to overcome that barrier, and to introduce the foundations of RL in a way that balances depth of understanding with clear, minimally technical delivery.
Section I. Processes and Planning Algorithms. 1. Markov Processes. 2. Markov Decision Processes. 3. Dynamic Programming Algorithms. 4. Function Approximation and Approximate Dynamic Programming. Section II. Modeling Financial Applications. 5. Utility Theory. 6. Dynamic Asset-Allocation and Consumption. 7. Derivatives Pricing and Hedging. 8. Order-Book Trading Algorithms. Section III. Reinforcement Learning Algorithms. 9. Monte-Carlo and Temporal-Difference for Prediction. 10. Monte-Carlo and Temporal-Difference for Control. 11. Batch RL, Experience-Replay, DQN, LSPI, Gradient TD. 12. Policy Gradient Algorithms. Section IV. Finishing Touches. 13. Multi-Armed Bandits: Exploration versus Exploitation. 14. Blending Learning and Planning. 15. Summary and Real-World Considerations. Appendices.
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