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. 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.

Machine Learning for Asset Management: New Developments and Financial Applications

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£138.95

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Hardback by Emmanuel Jurczenko

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This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in... Read more

    Publisher: ISTE Ltd and John Wiley & Sons Inc
    Publication Date: 31/07/2020
    ISBN13: 9781786305442, 978-1786305442
    ISBN10: 1786305445

    Number of Pages: 460

    Non Fiction , Business, Finance & Law

    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. 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.

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