finelybook
Advances in Financial Machine Learning
by 作者: Marcos Lopez de Prado
ISBN-10 书号: 1119482089
ISBN-13 书号: 9781119482086
Edition 版本: 1
Publisher Finelybook 出版日期: 2018-02-21
Pages: 400
Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance,this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis,and explains scientifically sound solutions using math,supported by code and examples. Readers become active users who can test the proposed solutions in their particular 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.
About the Author
PREAMBLE
PART 1 DATA ANALYSIS
Chapter 2 Financial Data Structures
Chapter 3 Labeling
Chapter 4 Sample Weights
Chapter 5 Fractionally Differentiated Features
PART 2 MODELLING
Chapter 6 Ensemble Methods
Chapter 7 Cross-Validation in Finance
Chapter 8 Feature Importance
Chapter 9 Hyper-Parameter Tuning with Cross-Validation
PART 3 BACKTESTING
Chapter 10 Bet Sizing
Chapter 11 The Dangers of Backtesting
Chapter 12 Backtesting through Cross-Validation
Chapter 13 Backtesting on Synthetic Data
Chapter 14Backtest Statistics
Chapter 15 Understanding Strategy Risk
Chapter 16 Machine Learning Asset Allocation
PART 4 USEFUL FINANCIAL FEATURES
Chapter 17 Structural Breaks
Chapter 18 Entropy Features
Chapter 19 Microstructural Features
PART 5 HIGH-PERFORMANCE COMPUTING RECIPES
Chapter 20 Multiprocessing and Vectorization
Chapter 21 Brute Force and Quantum Computers
Chapter 22 High-Performance Computational Intelligence and Forecasting Technologies
Index
EULA
