Artificial Intelligence in Finance

Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book.

In five parts, this guide helps you:

• Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI)
• Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice
• Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets
• Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies
• Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about