Advances in Financial Machine Learning

By:

Prado Marcos Lopez de

Material type: Text

TextPublication details: New Jersey John Wiley& Sons 2018ISBN:

9781119482086

Subject(s):

DDC classification:

006.31 PRA/A

Contents:

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

List(s) this item appears in: New Arrivals IIIT Kottayam Library - January 2024 | Dr T Jaisankar | New Arrivals

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Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Reference	IIIT Kottayam Central Library Reference	006.31 PRA/A (Browse shelf(Opens below))		Not for loan		2140
Books	IIIT Kottayam Central Library General Stacks	006.31 PRA/A (Browse shelf(Opens below))	1	Available		2778
Books	IIIT Kottayam Central Library General Stacks	006.31 PRA/A (Browse shelf(Opens below))	2	Available		2779
Books	IIIT Kottayam Central Library General Stacks	006.31 PRA/A (Browse shelf(Opens below))	3	Checked out to SHEBA ELIZABETH THOMAS (2022PHD13002)	02/02/2026	2780
Books	IIIT Kottayam Central Library General Stacks	006.31 PRA/A (Browse shelf(Opens below))	4	Available		2781

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Includes index.

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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