Overview

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.

Content Highlights

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.

Intended Audience

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.