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 ...
