Hands-On Machine Learning for Algorithmic Trading

ML is a toolkit for solving problems with data

ML offers algorithmic solutions and techniques that can be applied to many use cases. Parts 2, 3, and 4 of the book (as mentioned in Chapter 1, Machine Learning for Trading) have presented ML as a diverse set of tools that can add value to various steps of the strategy process, including:

• Idea generation and alpha factor research,
• Signal aggregation and portfolio optimization,
• Strategy testing
• Trade execution, and
• Strategy evaluation

Even more so, ML algorithms are designed to be further developed, adapted and combined to solve new problems in different contexts. For these reasons, it is important to understand key concepts and ideas underlying these algorithms, in addition to being able to ...