Human-Robot Interactions in Investment Decisions

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.

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Replaced by

Milo Bianchi, and Marie Brière, “Human-Robot Interactions in Investment Decisions”, Management Science, March 2024, forthcoming.

Reference

Milo Bianchi, and Marie Brière, “Human-Robot Interactions in Investment Decisions”, TSE Working Paper, n. 21-1251, September 2021, revised March 2024.