Big Data and Machine Learning in Quantitative Investment (Hardcover)

Tony Guida

ISBN 10: 1119522196 / ISBN 13: 9781119522195

Published by John Wiley & Sons Inc, New York, 2019

About this Item

Hardcover. 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, its 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9781119522195

Bibliographic Details

• Title: Big Data and Machine Learning in Quantitative Investment (Hardcover)
• Publisher: John Wiley & Sons Inc, New York
• Publication Date: 2019
• Language: English
• ISBN 10: 1119522196
• ISBN 13: 9781119522195
• Binding: Hardcover
• Condition: new

About this title

Synopsis

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.

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.