Hands-On Machine Learning for Algorithmic Trading

Explore the power of machine learning for algorithmic trading with this comprehensive guide. "Hands-On Machine Learning for Algorithmic Trading" lays out practical strategies and step-by-step techniques for implementing smart algorithms that drive financial trading decisions. By the end of this journey, you will be equipped with the tools and knowledge to develop and deploy robust trading models.

What this Book will help me do

• Understand how to use machine learning algorithms to solve investment and trading challenges.
• Learn to work with and gain insights from various data sources including market, fundamental, and alternative data.
• Design and optimize trading models using supervised, unsupervised, and reinforcement learning approaches.
• Implement deep learning for time series forecasting and other trading tasks using Python libraries.
• Validate trading strategies with reliable performance evaluation and backtesting techniques.

Author(s)

None Yau and Stefan Jansen are experts in finance and machine learning with extensive experience in developing data-driven trading systems. They combine their knowledge of algorithms and extensive practical experience in finance to create this accessible, hands-on guide. Their lucid style ensures that readers can apply complex concepts with ease.

Who is it for?

This book is suited for data scientists, quantitative analysts, and Python programmers interested in algorithmic trading. If you're an investment professional aiming to integrate machine learning into trading strategies, this book provides the techniques you need. Some prior experience with Python and machine learning concepts will help you make the most of it.