In a joint work with Michael Tertilt, an HSBA alumnus of MBA Corporate Management, we analyze the current quality of robo-advice.
Robo-advisors promise efficient, rational, and transparent investment advisory. We analyze how robo-advisors ascertain their user’s risk tolerance and which equity exposure is derived from the individual risk profile. Our findings indicate significant differences in the quality of offered investment advice. On average, robo-advisors ask relatively few questions in their user’s risk profile assessment, and it is particularly surprising that some of the questions seem not to have any impact on the risk categorization. Moreover, the recommended equity exposure is relatively conservative.
Michael Tertilt & Peter Scholz (2017): To Advise, or Not to Advise — How Robo-Advisors Evaluate the Risk Preferences of Private Investors. SSRN Working Paper.