If you are a Risk.net subscriber you are entitled to 20% off your Risk books purchases. Please email enquiries@riskbooks.com for more information.
As part of your Risk.net subscription you are entitled to 20% off all of your Risk Books purchases. If you would like to place an order please email enquiries@riskbooks.com
Artificial Intelligence in Finance, Volume 2: Reinforcement Learning Theory and Practice
Discipline: Operational Risk, Regulation, Investing
First published:
ISBN: 9781782724544
In this second volume of the Artificial Intelligence in Finance series, the authors explore how reinforcement learning (RL) is transforming financial modelling, strategy and decision-making.
What you’ll learn:
- Foundations first: Markov decision processes, optimal policy learning, and general RL frameworks.
- Next-level techniques: Hybrid models that fuse RL with deep learning, stochastic approximation, temporal difference learning, and even large language models.
- Real-world impact:
- Portfolio and wealth management.
- Algorithmic trading.
- Options pricing and hedging.
- Risk management and beyond.
- State-of-the-art tools: Explore how transformers and graph neural networks handle complex financial datasets with unprecedented flexibility.
With a clear focus on practical application, this book blends rigorous theory with hands-on tools to help professionals and academics alike build smarter, more scalable financial systems.
Whether you’re optimising trading strategies, managing risk or researching future-proof AI tools, this book is your road map to applying RL in the real world of finance.
