Human-Robot Interactions in Investment Decisions

Milo Bianchi and Marie Brière

No 21-1251, TSE Working Papers from Toulouse School of Economics (TSE)

Abstract: We study the introduction of robo-advising on a large set of Employee Saving Plans. Differently from many services that fully automate portfolio decisions, our robo-advisor proposes investment and rebalancing strategies, leaving investors free to follow or ignore them. The resulting human-robot interactions occur both at the time of the subscription and over time, as the robot sends alerts when the investor’s portfolio gets too far from the target allocation. We show that the robo-service is associated with an increase in investors’ attention and trading activities. Following the robot’s alerts, investors change their rebalancing behaviors so as to stay closer to their target allocation, which results in larger portfolio returns. Counterfactual returns induced by automatic rebalancing by the robot would be only slightly higher, suggesting that on average the financial cost of letting investors retain control is not large.

Keywords: Robo-Advising, Human-robot Interaction, Financial; Inclusion, Portfolio Dynamics, Long-Term Investment. (search for similar items in EconPapers)
JEL-codes: D14 G11 G23 G41 G51 (search for similar items in EconPapers)
Date: 2021-09, Revised 2024-03
New Economics Papers: this item is included in nep-cwa and nep-isf
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:tse:wpaper:125979

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