Advances in Financial Machine Learning

Marcos Lopez de Prado

John Wiley & Sons, Feb 21, 2018 - Business & Economics - 400 pages

Learn to understand and implement the latest machine learning innovations to improve your investment performance

Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest.

In the book, readers will learn how to:

• Structure big data in a way that is amenable to ML algorithms
• Conduct research with ML algorithms on big data
• Use supercomputing methods and back test their discoveries while avoiding false positives

Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting.

Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Contents

• Financial Data Structures: 23
• Labeling: 43
• Sample Weights: 59
• CONTENTS: 65
• Fractionally Differentiated Features: 75
• 43: 91
• MODELLING: 93
• xii: 100
• Feature Importance: 113
• HyperParameter Tuning with CrossValidation: 129
• CONTENTS: 135
• 103: 139
• BACKTESTING: 141
• The Dangers of Backtesting: 151
• 75: 157
• Backtesting through CrossValidation: 161
• xiv: 166
• Backtest Statistics: 195
• CONTENTS: 208
• Machine Learning Asset Allocation: 221
• 91: 245
• 139: 247
• USEFUL FINANCIAL FEATURES: 249
• Entropy Features: 263
• Microstructural Features: 281
• CONTENTS: 283
• HIGHPERFORMANCE COMPUTING RECIPES: 303
• xviii: 317
• HighPerformance Computational Intelligence and Forecasting: 329
• CONTENTS xix: 347
• 329: 352
• Index: 353
• 211: 354

About the author

DR. MARCOS LÓPEZ DE PRADO is a principal at AQR Capital Management, and its head of machine learning. Marcos is also a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). SSRN ranks him as one of the most-read authors in economics, and he has published dozens of scientific articles on machine learning and supercomputing in the leading academic journals. Marcos earned a PhD in financial economics (2003), a second PhD in mathematical finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a graduate course in financial machine learning at the School of Engineering. Marcos has an Erdös #2 and an Einstein #4 according to the American Mathematical Society.

Bibliographic information

• Title: Advances in Financial Machine Learning
• Author: Marcos Lopez de Prado
• Publisher: John Wiley & Sons, 2018
• ISBN: 1119482089, 9781119482086
• Length: 400 pages
• Subjects: Business & Economics / Accounting / General; Business & Economics / General; Business & Economics / Investments & Securities / General; Computers / Artificial Intelligence / Computer Vision & Pattern Recognition; Computers / Machine Theory