Robo-Advisor vs. Human-Advisor : An Experimental Study on Portfolio Valuation

This study experimentally elicits subjects' valuation for a portfolio constructed by a Robo-advisor vs. Human-advisor. We conduct an online experiment using the second price sealed-bid auction to elicit subjects' valuation to the portfolio constructed by the Robo-advisor vs. Human-advisor. The main results are as follows. First, investors are likely to invest more when the portfolio is constructed by a Robo-advisor than a Human-advisor. The result is consistent with the theory of source preference (Fox and Tversky, 1995; Chew and Sagi, 2008) that investors prefer to take risk from the source of uncertainty by Robo-advisor than by Human-advisor. Second, subejcts with higher degree of Fintech knowledge tend to have higher valuation with the Robo-advisor portfolio. Third, subjects are very optimistic on the portfolio constructed by the Robo-advisor. Overall, our results suggest that individuals exhibit strong preference for Robo-advisor over Human-advisor