Robo-Advising: A Dynamic Mean-Variance Approach
21 Pages Posted: 4 Jan 2021 Last revised: 7 Feb 2021
Date Written: October 29, 2020
In contrast to traditional financial advising, robo-advising needs to elicit investors’ risk profile via several simple online questions and provide advice consistent with conventional investment wisdom, e.g., rich and young people should invest more in risky assets. To meet the two challenges, we propose to do the asset allocation part of robo- advising using a dynamic mean-variance criterion over the the portfolio’s log-returns. The model yields analytical and time-consistent optimal portfolio policies under jump-diffusion models and regime-switching models.
Keywords: robo-advising, mean-variance, asset allocation
JEL Classification: G11, D81, C61
Suggested Citation: Suggested Citation