Machine Learning for Asset Management: New Developments and Financial Applications

ISBN 10: 1786305445 / ISBN 13: 9781786305442

Edité par Wiley-ISTE, 2020

In. N° de réf. du vendeur ria9781786305442_new

Synopsis :

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.

À propos de l'auteur:

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.

Détails bibliographiques

Titre : Machine Learning for Asset Management: New ...
Éditeur : Wiley-ISTE
Date d'édition : 2020
Reliure : Couverture rigide
Etat : New