Machine learning for algorithmic trading : predictive models to extract signals from market and alternative data for systematic trading strategies with Python
Stefan Jansen (Author)
This thoroughly revised and expanded second edition demonstrates on over 800 pages how machine learning can add value to algorithmic trading in a practical yet comprehensive way. It has four parts that cover how to work with a diverse set of market, fundamental, and alternative data sources, design ML solutions for real-world trading ..
eBook, English, 2020
Second edition View all formats and editions
Packt Publishing, Birmingham, UK, 2020
1 online resource (1 volume) : illustrations
9781839216787, 1839216786
1203113533
Table of ContentsMachine Learning for Trading
From Idea to ExecutionMarket and Fundamental Data
Sources and TechniquesAlternative Data for Finance
Categories and Use CasesFinancial Feature Engineering
How to Research Alpha FactorsPortfolio Optimization and Performance EvaluationThe Machine Learning ProcessLinear Models
From Risk Factors to Return ForecastsThe ML4T Workflow
From Model to Strategy BacktestingTime-Series Models for Volatility Forecasts and Statistical ArbitrageBayesian ML
Dynamic Sharpe Ratios and Pairs Trading(N.B. Please use the Look Inside option to see further chapters)
Previous edition published: 2018