000			01291nam a22001577a 4500
020			_a9781119482086
082	0	0	_a006.31 _bPRA/A
100	1		_aPrado Marcos Lopez de
245	1	0	_aAdvances in Financial Machine Learning
260			_aNew Jersey _bJohn Wiley& Sons _c2018
500			_aIncludes index.
505	8		_a 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
650		0	_aFinance
650		0	_aMachine learning.
942			_cBK
999			_c2202 _d2202