What drives robo-advice?

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.

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Publication Details

Journal
Journal of Empirical Finance
Published
2024-12-10
DOI
https://doi.org/10.1016/j.jempfin.2024.101574
Citations
11
Primary Topic
Decision-Making and Behavioral Economics
Type
article
Field-Weighted Citation Impact
5.89
Controls
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article

What drives robo-advice?

Sebastian Lehner, Bernd Scherer
11 citations
Journal of Empirical Finance
Decision-Making and Behavioral Economics
5.89
article

What drives robo-advice?

Sebastian Lehner, Bernd Scherer
article en
11 citations

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. • 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.

Journal of Empirical FinanceVol. 80
University of Wuppertal (DE), European College of Business and Management (GB), Abu Dhabi Health Services (AE), Spring Techno (Germany) (DE)
Openalex Percentile: Top 3%
Decision-Making and Behavioral Economics
5.89
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