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Machine Learning for Asset Management
New Developments and Financial Applications
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Machine Learning for Asset Management
$33999
Unit price
/
Unavailable
Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?
Book Hero Magic formatted this description to make it easier to read. While it's new and
still learning, it may not be perfect - your
feedback is welcome!
Description
This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management.
The chapters introduce the reader to some of the latest research developments in the area of equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution, and transaction costs modeling.
Machine Learning for Asset Management will be of great help to portfolio managers, asset owners, and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.
Book Details
INFORMATION
ISBN: 9781786305442
Publisher: ISTE Ltd and John Wiley & Sons Inc
Format: Hardback
Date Published: 31 July 2020
Country: United Kingdom
Imprint: ISTE Ltd and John Wiley & Sons Inc
Contributors:
- Edited by Emmanuel Jurczenko
Audience: Professional and scholarly
DIMENSIONS
Spine width: 28.0mm
Width: 160.0mm
Height: 236.0mm
Weight: 885g
Pages: 460
About the Author
Emmanuel JURCZENKO is Director of Graduate Studies and Professor of Finance at Glion Institute of Higher Education, Switzerland. Prior to this, he spent 13 years as Associate Professor of Finance at ESCP-Europe and worked for ABN-AMRO as Head of Quantitative Analysts where he was in charge of quantitative fund selection. His research focuses on portfolio construction in particular on risk budgeting, factor investing and machine learning estimation techniques.
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