What drives robo-advice?

Abstract

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.