Big Data and Machine Learning in Quantitative Investment

Tony Guida

ISBN 10: 1119522196 / ISBN 13: 9781119522195

Published by Wiley Mär 2019, 2019

About this Item

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

Bibliographic Details

• Title: Big Data and Machine Learning in Quantitative Investment
• Publisher: Wiley Mär 2019
• Publication Date: 2019
• Language: English
• ISBN 10: 1119522196
• ISBN 13: 9781119522195
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 21D millimeters 250 millimeters width by 175 millimeters height by 21 millimeters depth
• Weight: 712 grams

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.