Artificial Intelligence in Finance

This book provides practical insights on using AI and machine learning in finance, focusing on algorithmic trading and market inefficiencies.

In Artificial Intelligence in Finance, readers will find a comprehensive guide tailored for practitioners, students, and academics interested in the intersection of finance and data science. The author, Yves Hilpisch, provides insights into how AI and machine learning can be leveraged to identify and exploit statistical inefficiencies within financial markets. As these technologies gain traction, they are set to revolutionize the financial industry, fundamentally altering the landscape of trading and investment strategies.

The book is structured into five informative parts, each designed to build a solid understanding of key concepts and algorithms in AI. Readers will explore the latest advancements on the path to artificial general intelligence (AGI) and superintelligence (SI), while also grasping the significance of data-driven finance. Hilpisch emphasizes the lasting impact that AI and machine learning will have on both financial theory and practical applications, making it a vital resource for anyone looking to stay ahead in this rapidly evolving field.

With numerous self-contained Python examples, Artificial Intelligence in Finance ensures that readers can replicate the results and figures discussed throughout the text. The guide covers essential topics such as neural networks, reinforcement learning, and backtesting, offering practical strategies for discovering and capitalizing on economic inefficiencies through algorithmic trading. Additionally, Hilpisch delves into the potential future of finance, including the implications of AI on competitive dynamics and the concept of a financial singularity.