Machine Learning for Asset Management: New Developments and Financial Applications

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Emmanuel Jurczenko (Glion Institute of Higher Education, Switzerland)

Machine Learning for Asset Management

New Developments and Financial Applications

Emmanuel Jurczenko (Glion Institute of Higher Education, Switzerland)

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English

ISTE Ltd and John Wiley & Sons Inc
18 September 2020

Finance; Management & management techniques; Machine learning

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.

Edited by: Emmanuel Jurczenko (Glion Institute of Higher Education Switzerland)
Imprint: ISTE Ltd and John Wiley & Sons Inc
Country of Publication: United Kingdom
Dimensions: Height: 236mm, Width: 160mm, Spine: 28mm
Weight: 885g
ISBN: 9781786305442
ISBN 10: 1786305445
Pages: 460
Publication Date: 18 September 2020
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

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.