Who Benefits from Robo-advising? Evidence from Machine Learning

73 Pages Posted: 3 Apr 2020 Last revised: 1 Feb 2021

See all articles by Alberto G. Rossi

Alberto G. Rossi

Georgetown University

Stephen P. Utkus

University of Pennsylvania; Center for Financial Markets and Policy, Georgetown University

Date Written: March 10, 2020

Abstract

We study the effects of a large U.S. hybrid robo-adviser on the portfolios of previously self- directed investors. Across all investors, robo-advising reduces investors’ holdings in money market mutual funds and increases bond holdings. It also reduces idiosyncratic risk by lowering the holdings of individual stocks and US and international active mutual funds and raising exposure to low-cost indexed mutual funds. It further eliminates home bias by significantly increasing international equity and fixed income diversification. Finally — over our sample period — it increases investors’ overall risk-adjusted performance, mainly by lowering investors’ portfolio risk. We use a machine learning algorithm, known as Boosted Regression Trees (BRT), to explain the cross-sectional variation in the effects of advice on portfolio allocations and performance. Investors who benefit from advice are those with little self-directed investment experience on the platform, those with prior high cash holdings, and those with high trading volume before adopting advice. Individuals invested in high-fee active mutual funds also display significant performance gains. Finally, we study the determinants of investors’ sign-up and attrition. Investors who benefit more from robo-advising are also more likely to sign-up and less likely to quit the service.

Keywords: FinTech, Portfolio Choice, Behavioral Finance, Individual Investors, Financial Literacy, Technology Adoption, Machine Learning

JEL Classification: D14, G11, O33

Suggested Citation

Rossi, Alberto G. and Utkus, Stephen P., Who Benefits from Robo-advising? Evidence from Machine Learning (March 10, 2020). Available at SSRN: https://ssrn.com/abstract=3552671 or http://dx.doi.org/10.2139/ssrn.3552671

Alberto G. Rossi (Contact Author)

Georgetown University ( email )

McDonough School of Business
Georgetown University
Washington, DC 20057
United States

Stephen P. Utkus

University of Pennsylvania ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

Center for Financial Markets and Policy, Georgetown University ( email )

Washington, DC 20057
United States

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