The diversification and welfare effects of robo-advising

Alberto G. Rossi and Stephen Utkus

Journal of Financial Economics, 2024, vol. 157, issue C

Abstract: We study the diversification and welfare effects of a large US robo-advisor on the portfolios of previously self-directed investors and document five facts. First, robo-advice reshapes portfolios by increasing indexing and reducing home bias, number of assets held, and fees. Second, these portfolio changes contribute to higher Sharpe ratios. Third, those who benefit most from robo-advice are investors who did not have high exposure to equities or indexing and had poorer diversification levels. Fourth, robo-advice decreases the time investors dedicate to managing their investments. Fifth, those investors who benefit most are more likely to join the service and not quit it.

Keywords: FinTech; Portfolio choice; Machine learning; Individual investors; Financial literacy; Technology adoption (search for similar items in EconPapers)
JEL-codes: D14 G11 O33 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jfinec:v:157:y:2024:i:c:s0304405x24000928

DOI: 10.1016/j.jfineco.2024.103869

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