What drives robo-advice?
通过分析美国一家主要机器人理财顾问的151,200个投资者档案，发现投资目标和时间显著影响股票配置，但复杂的对冲需求被忽略，表明商业机器人理财更注重简单性和客户感知。
The promise of robo-advisory firms is to provide low-cost access to diversified portfolios built according to academic literature on normative portfolio choice. We investigate the extent to which robo-advice aligns with normative advice. Using web-scraped portfolio recommendations for 151,200 investor types from a major US robo-advisor, we find that investment goals and time horizons significantly influence recommended equity allocations, while Merton-type hedging demands are largely ignored. Our results suggest that commercial robo-advisors prioritize simplicity and client perceptions over complex, normative models. By integrating data from the NFCS survey, we further explore how demographic factors influence the likelihood of using robo-advisory services. This study provides empirical evidence on how closely robo-advisory services align with normative portfolio theory, highlighting the practical compromises made in the pursuit of broad market appeal and user-friendly solutions. • Analysis of 151,200 investor profiles from a major US robo-advisor. • Investment goals and time horizons significantly shape equity allocations. • Commercial robo-advisors largely ignore Merton-type hedging demands. • The focus is on client accessibility and reducing financial complexity. • NFCS data shows demographics and trust as key drivers of robo-advisory adoption.