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.
Table of contents
- About the Author
- PREAMBLE
- PART 1 DATA ANALYSIS
- PART 2 MODELLING
-
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 14 Backtest Statistics
- Chapter 15 Understanding Strategy Risk
-
Chapter 16 Machine Learning Asset Allocation
- 16.1 Motivation
- 16.2 The Problem with Convex Portfolio Optimization
- 16.3 Markowitz's Curse
- 16.4 From Geometric to Hierarchical Relationships
- 16.5 A Numerical Example
- 16.6 Out-of-Sample Monte Carlo Simulations
- 16.7 Further Research
- 16.8 Conclusion
- APPENDICES
- 16.A.1 Correlation-based Metric
- 16.A.2 Inverse Variance Allocation
- 16.A.3 Reproducing the Numerical Example
- 16.A.4 Reproducing the Monte Carlo Experiment
- Exercises
- References
- Notes
- PART 4 USEFUL FINANCIAL FEATURES
- PART 5 HIGH-PERFORMANCE COMPUTING RECIPES
- Index
- EULA
Product information
- Title: Advances in Financial Machine Learning
- Author(s):
- Release date: February 2018
- Publisher(s): Wiley
- ISBN: 9781119482086
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