Advances in Financial Machine Learning
- 12h 58m 36s
- Marcos Lopez de Prado
- Gildan Media
- 2018
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.
Listeners 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. Listeners 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.
In this Audiobook
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CHAPTER 1: FINANCIAL MACHINE LEARNING AS A DISTINCT SUBJECT
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CHAPTER 2: FINANCIAL DATA STRUCTURES
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CHAPTER 3: LABELING
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CHAPTER 4: SAMPLE WEIGHTS
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CHAPTER 5: FRACTIONALLY DIFFERENTIATED FEATURES
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CHAPTER 6: ENSEMBLE METHODS
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CHAPTER 7: CROSS-VALIDATION IN FINANCE
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CHAPTER 8: FEATURE IMPORTANCE
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CHAPTER 9: HYPER-PARAMETER TUNING WITH CROSS-VALIDATION
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CHAPTER 10: BET SIZING
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CHAPTER 11: THE DANGERS OF BACKTESTING
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CHAPTER 12: BACKTESTING THROUGH CROSS-VALIDATION
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CHAPTER 13: BACKTESTING ON SYNTHETIC DATA
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CHAPTER 14: BACKTEST STATISTICS
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CHAPTER 15: UNDERSTANDING STRATEGY RISK
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CHAPTER 16: MACHINE LEARNING ASSET ALLOCATION
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CHAPTER 17: STRUCTURAL BREAKS
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CHAPTER 18: ENTROPY FEATURES
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CHAPTER 19: MICROSTRUCTURAL FEATURES
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CHAPTER 20: MULTIPROCESSING AND VECTORIZATION
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CHAPTER 21: BRUTE FORCE AND QUANTUM COMPUTERS
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CHAPTER 22: HIGH-PERFORMANCE COMPUTATIONAL INTELLIGENCE AND FORECASTING TECHNOLOGIES
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