ISBN 13 : 978-1-119-48208-6

Sommaire :
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

References
Index ;
PREAMBLE
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

References
Index

Langue : Anglais

Lieu d'édition : TORONTO

Localisation : Bibliothèque Campus de Nice

Support : Papier

Etat : Présent

Propriétaire : Bibliothèque