Foundations of Reinforcement Learning with Applications in Finance

The book Foundations of Reinforcement Learning with Applications in Finance aims to make Reinforcement Learning a practical tool for those studying and working in applied areas, especially finance. It emphasizes the foundational mathematics and provides Python code and coverage of financial trading problems.

Format: Hardback
Length: 500 pages
Publication date: 16 December 2022
Publisher: Taylor & Francis Ltd

Reinforcement Learning (RL) is a rapidly evolving field that has the potential to revolutionize the way we solve complex problems across industries. It involves learning from interactions with the environment to make optimal decisions in sequential situations where uncertainty is present. With its applications in areas such as self-driving cars, robotics, and strategy games, RL is already demonstrating its superiority over human decision-making abilities. However, there is a reluctancy among individuals to enter this field due to its perceived mystery and technical complexity.

This book aims to demystify Reinforcement Learning and make it a practically useful tool for those studying and working in applied areas, particularly finance. It provides a comprehensive and lucid understanding of the topic by emphasizing the foundational mathematics and implementing models and algorithms in well-designed Python code. Additionally, it offers robust coverage of several financial trading problems that can be solved with Reinforcement Learning.

The book has been created after years of iterative experimentation on the pedagogy of these topics, which have been taught to university students as well as industry practitioners. It focuses on the foundational theory underpinning Reinforcement Learning and software design of the corresponding models and algorithms. While suitable as a primary text for courses in Reinforcement Learning, it can also serve as supplementary reading for applied/financial mathematics, programming, and other related courses.

The book is designed for a professional audience of quantitative analysts or data scientists who are interested in leveraging RL to improve their decision-making processes in finance. It blends theory/mathematics, programming/algorithms, and real-world financial examples to provide a comprehensive and practical guide to this exciting field.

In conclusion, Reinforcement Learning is a transformative technology that has the potential to revolutionize the way we solve complex problems. This book aims to make it accessible and practical for individuals interested in applying RL in finance and other applied areas. By emphasizing the foundational theory and providing hands-on implementation, it seeks to empower readers to leverage RL's power and make meaningful contributions to their fields.

Weight: 1092g
Dimension: 185 x 260 x 35 (mm)
ISBN-13: 9781032124124