Artificial Intelligence in Finance: A Python-Based Guide

Many industries have been revolutionized by the widespread adoption of AI and machine learning. The programmatic availability of historical and real-time financial data in combination with techniques from AI and machine learning will also change the financial industry in a fundamental way. This practical book explains how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science how machine and deep learning algorithms can be applied to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. Examine how data is reshaping finance from a theory-driven to a data-driven discipline Understand the major possibilities, consequences, and resulting requirements of AI-first finance Get up to speed on the tools, skills, and major use cases to apply AI in finance yourself Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Delve into the concepts of the technological singularity and the financial singularity