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Artificial Intelligence Alter Egos: Who might benefit from robo-investing?

D’Hondt, Catherine, Rudy De Winne, Eric Ghysels and Steve Raymond

Journal of Empirical Finance, 2020, vol. 59, issue C, 278-299

Abstract: We use a unique data set covering brokerage accounts for a large cross-section of investors over a sample from January 2003 to March 2012, which includes the 2008 financial crisis, to assess the potential benefits of robo-investing. We explore robo-investing strategies commonly used in the industry, including some involving advanced machine learning methods. We shadow each of our investors with a robo-advisor to shed light on possible benefits the emerging robo-advising industry may provide to certain segments of the population, such as low income and/or low education investors.

Date: 2020
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Citations: View citations in EconPapers (18)

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Working Paper: Artificial Intelligence Alter Egos: Who might benefit from robo-investing? (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:59:y:2020:i:c:p:278-299

DOI: 10.1016/j.jempfin.2020.10.002

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Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff

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