The widespread adoption of AI and machine learning is revolutionizing many
industries today. Once these technologies are combined with the programmatic
availability of historical and real-time financial data, the financial
industry will also change fundamentally. With this practical book, you'll
learn 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 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 te 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
Також купити книгу Artificial Intelligence in Finance: A Python-Based Guide,
Yves Hilpisch Ви можете по посиланню