Book

Machines now place most trades in the world’s largest markets, yet the story behind trading robots and artificial intelligence is far less glamorous than the headlines suggest. Machines That Trade is a clear, honest guide to how AI and algorithmic trading really work. From the mechanics of the order book to market making, machine learning, deep learning, and reinforcement learning, it shows how models are built, why most of them fail, and how rigorous validation keeps researchers from fooling themselves. It then turns to engineering and risk: how trading robots are tested, deployed, and monitored, and what episodes like the 2010 Flash Crash teach about algorithms interacting. Ideal for students, aspiring quants, developers, and curious investors, this book offers no secret formulas and no get-rich-quick promises. It offers something more valuable: the judgment to evaluate bold claims and to respect the markets you hope to navigate.