Hands-On Machine Learning for Algorithmic Trading

What this book covers

Chapter 1, Machine Learning for Trading, identifies the focus of the book by outlining how ML matters in generating and evaluating signals for the design and execution of a trading strategy. It outlines the strategy process from hypothesis generation and modeling, data selection, and backtesting to evaluation and execution in a portfolio context, including risk management.

Chapter 2, Market and Fundamental Data, covers sources and working with original exchange-provided tick and financial reporting data, as well as how to access numerous open-source data providers that we will rely on throughout this book.

Chapter 3, Alternative Data for Finance, provides categories and criteria to assess the exploding number of sources ...