Reinforcement Learning for Finance: A Python-Based Introduction
eBook Details:
- Paperback: 212 pages
- Publisher: WOW! eBook (November 19, 2024)
- Language: English
- ISBN-10: 109816914X
- ISBN-13: 978-1098169145
eBook Description:
Reinforcement Learning for Finance: A Python-Based Introduction
Reinforcement learning (RL) has led to several breakthroughs in AI. The use of the Q-learning (DQL) algorithm alone has helped people develop agents that play arcade games and board games at a superhuman level. More recently, RL, DQL, and similar methods have gained popularity in publications related to financial research.
This Reinforcement Learning for Finance book is among the first to explore the use of reinforcement learning methods in finance.
Author Yves Hilpisch, founder and CEO of The Python Quants, provides the background you need in concise fashion. ML practitioners, financial traders, portfolio managers, strategists, and analysts will focus on the implementation of these algorithms in the form of self-contained Python code and the application to important financial problems.
This Reinforcement Learning for Finance: A Python-Based Introduction book covers:
- Reinforcement learning
- Deep Q-learning
- Python implementations of these algorithms
- How to apply the algorithms to financial problems such as algorithmic trading, dynamic hedging, and dynamic asset allocation
This Reinforcement Learning for Finance book is the ideal reference on this topic. You’ll read it once, change the examples according to your needs or ideas, and refer to it whenever you work with RL for finance.
