1st Edition
by Yves Hilpisch (Author)
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 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
