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Big Data and Machine Learning in Quantitative Investment
Get to know the 'why' and 'how' of machine learning and big data in quantitative investment Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it's a book by practitioners for practitioners, covering the...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Newark :
John Wiley & Sons, Incorporated,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo |
| Sumario: | Get to know the 'why' and 'how' of machine learning and big data in quantitative investment Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it's a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance. The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning. - Gain a solid reason to use machine learning - Frame your question using financial markets laws - Know your data- Understand how machine learning is becoming ever more sophisticated Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment - and this book shows you how. |
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| Notas: | Chapter 5 Using Alternative and Big Data to Trade Macro Assets |
| Descripción Física: | 1 online resource (299 pages) |
| Bibliografía: | ReferencesChapter 4 Implementing Alternative Data in an Investment Process; 4.1 Introduction; 4.2 The Quake: Motivating the Search for Alternative Data; 4.2.1 What happened?; 4.2.2 The next quake?; 4.3 Taking Advantage of the Alternative Data Explosion; 4.4 Selecting A Data Source for evaluation; 4.5 Techniques for Evaluation; 4.6 Alternative Data for Fundamental Managers; 4.7 Some Examples; 4.7.1 Example 1: Blogger sentiment; 4.7.2 Example 2: Online consumer demand; 4.7.3 Example 3: Transactional data; 4.7.4 Example 4: ESG; 4.8 Conclusions; References |
| ISBN: | 9781119522089 1119522080 9781119522218 1119522218 |