Big Data and Machine Learning in Quantitative Investment

Tony Guida
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Tony Guida: EDHEC-Risk Institute - EDHEC - EDHEC Business School - UCL - Université catholique de Lille

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Abstract: 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.

Date: 2019-01-01
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Published in John Wiley & Sons, VI-285 p., 2019, 978-1-119-52219-5. ⟨10.1002/9781119522225⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02298299

DOI: 10.1002/9781119522225

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