Machine Learning for Asset Management: New Developments and Financial Applications by Jurczenko, Emmanuel

Machine Learning for Asset Management: New Developments and Financial Applications (Hardcover) (ISBN-13: 9781786305442)

Vendor: Emmanuel Jurczenko
Product type: Books
Format: Hardcover
$177.95
$177.95
$177.95
Subtotal: $177.95
Machine Learning for Asset Management: New Developments and Financial Applications by Jurczenko, Emmanuel

Machine Learning for Asset Management: New Developments and Financial Applications

$177.95
Machine Learning for Asset Management: New Developments and Financial Applications by Jurczenko, Emmanuel

Machine Learning for Asset Management: New Developments and Financial Applications

$177.95
Format: Hardcover
Description
Description
x
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. This volume 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.

Author: Emmanuel Jurczenko
ISBN-10: 1786305445
ISBN-13: 9781786305442
Publisher: Wiley-Iste
Language: English
Published: 10/06/2020
Pages: 460
Format: Hardcover
Weight: 2.25lbs
Size: 9.30h x 6.10w x 1.10d
By Emmanuel Jurczenko
By Emmanuel Jurczenko
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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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