Man vs. Machine: Quantitative and Discretionary Equity Management

80 Pages Posted: 21 Dec 2020

See all articles by Simona Abis

Simona Abis

Columbia University - Columbia Business School

Date Written: October 23, 2020

Abstract

In modern asset markets, man and machine compete for profits. How does each fare? I build a learning model in which quantitative investors (reliant on computer models) have more learning capacity but less flexibility to adapt to market conditions than discretionary investors (reliant on human judgment). I use machine learning to categorize US active equity mutual funds as quantitative or discretionary. Consistent with the model's predictions, I find that quantitative funds hold more stocks, specialize in stock picking, and engage in more overcrowded trades. Discretionary funds hold lesser known stocks, switch between picking and timing and outperform in recessions.

Keywords: Investment Management, Quantitative Mutual Funds, Machine Learning, Rational Inattention

JEL Classification: G11, G23, G14

Suggested Citation

Abis, Simona, Man vs. Machine: Quantitative and Discretionary Equity Management (October 23, 2020). Available at SSRN: https://ssrn.com/abstract=3717371 or http://dx.doi.org/10.2139/ssrn.3717371

Simona Abis (Contact Author)

Columbia University - Columbia Business School ( email )

3022 Broadway
New York, NY 10027
United States

HOME PAGE: http://https://www8.gsb.columbia.edu/cbs-directory/detail/sa3518

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