Screen LibraryMachine learning for algorithmic trading : predictive models to extract signals from market and alternative data for systematic trading strategies with Python /
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...
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| Main Authors: | |
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| Published: |
Packt Publishing,
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| Publisher Address: | Birmingham, UK : |
| Publication Dates: | 2020. |
| Literature type: | Book |
| Language: | English |
| Edition: | Second edition. |
| Series: |
Expert insight
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| Subjects: | |
| Summary: |
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 ... |
| Item Description: | Previous edition published: 2018. |
| Carrier Form: | xxii, 790 pages : illustrations ; 24 cm. |
| Bibliography: | Includes bibliographical references (pages 753-767) and index. |
| ISBN: | 9781839217715 |
| Index Number: | HG104 |
| CLC: | F830.49 |
| Call Number: | F830.49/J351/2nd ed. |
| Contents: | 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). |