Robo-Advising

30 Pages Posted: 20 Apr 2020

Multiple version iconThere are 2 versions of this paper

Date Written: 2020

Abstract

In this chapter, we first discuss the limitations of traditional financial advice, which led to the emergence of robo-advising. We then describe the main features of robo-advising and propose a taxonomy of robo-advisors based on four defining dimensions---personalization, discretion, involvement, and human interaction. Building on these premises, we delve into the theoretical and empirical evidence on the design and effects of robo-advisors on two major sets of financial decisions, that is, investment choices (for both short- or long-term horizons) and the allocation of financial resources between spending and saving. We conclude by elaborating on five broadly open issues in robo-advising, which beget theoretical and empirical research by scholars in economics, finance, psychology, law, philosophy, as well as regulators and industry practitioners.

Keywords: FinTech, behavioral economics, algorithmic advice, A1, financial regulation, financial literacy

JEL Classification: D140, G210

Suggested Citation

D'Acunto, Francesco and Rossi, Alberto G., Robo-Advising (2020). CESifo Working Paper No. 8225, Available at SSRN: https://ssrn.com/abstract=3578259 or http://dx.doi.org/10.2139/ssrn.3578259

Francesco D'Acunto (Contact Author)

Georgetown University ( email )

Washington, DC 20057
United States

Alberto G. Rossi

Georgetown University ( email )

McDonough School of Business
Georgetown University
Washington, DC 20057
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
563
Abstract Views
2,060
Rank
22,619
PlumX Metrics