Big Data and Machine Learning in Quantitative Investment
Language: English
Published by John Wiley & Sons Apr 2019, 2019
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 66.09
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Add to basketItem description from seller
Neuware - Get to know the 'why' and 'how' of machine learning and big data in quantitative investmentBig 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 sophisticatedMachine 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.…
Seller Inventory # 9781119522195
- Title
- Big Data and Machine Learning in Quantitative Investment
- Author
- Tony Guida
- Publisher
- John Wiley & Sons Apr 2019
- Publication year
- 2019
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1119522196
- ISBN 13
- 9781119522195
- Item weight
- 712 grams
- Dimensions
- 250x175x21 mm
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.
"Synopsis" may belong to another edition of this title.
About the Author
TONY GUIDA is a senior investment manager in quantitative equity at the investment manager of a major UK pension fund in London, where he manages multifactor systematic equity portfolios. During his career, he held such positions as senior consultant for smart beta and risk allocation at EDHEC RISK Scientific Beta and senior research analyst at UNIGESTION. He is a former member of the research and investment committee for Minimum Variance Strategies, where he led the factor investing research group for institutional clients, and a regular speaker at quant conferences. Tony is chair of machineByte ThinkTank EMEA.
"About the title" may belong to another edition of this title.
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