Advances in Financial Machine Learning

Advances in Financial Machine Learning
PDF, ePUB
  • eBook:
    Advances in Financial Machine Learning
  • Author:
    Marcos Lopez de Prado
  • Edition:
    1 edition
  • Categories:
  • Data:
    February 21, 2018
  • ISBN:
    1119482089
  • ISBN-13:
    9781119482086
  • Language:
    English
  • Pages:
    400 pages
  • Format:
    PDF, ePUB

Book Description
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.

Content

1. Financial Machine Learning as a Distinct Subject

PART 1 - DATA ANALYSIS
2. Financial Data Structures
3. Labeling
4. Sample Weights
5. Fractionally Differentiated Features

PART 2 - MODELLING
6. Ensemble Methods
7. Cross-Validation in Finance
8. Feature Importance
9. Hyper-Parameter Tuning with Cross-Validation

PART 3 - BACKTESTING
10. Bet Sizing
11. The Dangers of Backtesting
12. Backtesting through Cross-Validation
13. Backtesting on Synthetic Data
14. Backtest Statistics
15. Understanding Strategy Risk
16. Machine Learning Asset Allocation

PART 4 - USEFUL FINANCIAL FEATURES
17. Structural Breaks
18. Entropy Features
19. Microstructural Features

PART 5 - HIGH-PERFORMANCE COMPUTING RECIPES
20. Multiprocessing and Vectorization
21. Brute Force and Quantum Computers
22. High-Performance Computational Intelligence and Forecasting Technologies

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