How Can Machine Learning Advance Quantitative Asset Management?

The Journal of Portfolio Management, volume 49, issue 9, 2023[10.3905/jpm.2023.1.460]

21 Pages Posted: 10 Jan 2023 Last revised: 28 Jan 2025

See all articles by David Blitz

David Blitz

Robeco Quantitative Investments

Tobias Hoogteijling

Robeco Quantitative Investments

Harald Lohre

Robeco Quantitative Investments; Lancaster University Management School

Philip Messow

Robeco Institutional Asset Management

Date Written: January 9, 2023

Abstract

The emerging literature suggests that machine learning (ML) is beneficial in many asset pricing applications because of its ability to detect and exploit nonlinearities and interaction effects that tend to go unnoticed with simpler modelling approaches. In this paper, we discuss the promises and pitfalls of applying machine learning to asset management, by reviewing the existing ML literature from the perspective of a prudent practitioner. The focus is on the methodological design choices that can critically affect predictive outcomes and on an evaluation of the frequent claim that ML gives spectacular performance improvements. In light of the practical considerations, the apparent advantage of ML is reduced, but still likely to make a difference for investors who adhere to a sound research protocol to navigate the intrinsic pitfalls of ML.

Keywords: machine learning, asset management, portfolio management, factor investing

JEL Classification: G10, G12, G17

Suggested Citation

Blitz, David and Hoogteijling, Tobias and Lohre, Harald and Messow, Philip, How Can Machine Learning Advance Quantitative Asset Management? (January 9, 2023). The Journal of Portfolio Management, volume 49, issue 9, 2023[10.3905/jpm.2023.1.460], Available at SSRN: https://ssrn.com/abstract=4321398 or http://dx.doi.org/10.3905/jpm.2023.1.460

David Blitz (Contact Author)

Robeco Quantitative Investments ( email )

Weena 850
Rotterdam, 3014 DA
Netherlands

Tobias Hoogteijling

Robeco Quantitative Investments ( email )

Rotterdam, 3011 AG
Netherlands
0655685700 (Phone)

Harald Lohre

Robeco Quantitative Investments ( email )

Weena 850
Rotterdam, 3011 AG
Netherlands

Lancaster University Management School

Bailrigg
Lancaster LA1 4YX
United Kingdom

HOME PAGE: http://www.lancaster.ac.uk/lums/people/harald-lohre

Philip Messow

Robeco Institutional Asset Management ( email )

Rotterdam, 3011 AG
Netherlands

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