Robo-advising: a dynamic mean-variance approach

Min Dai (), Hanqing Jin (), Steven Kou () and Yuhong Xu ()
Additional contact information
Min Dai: National University of Singapore
Hanqing Jin: The University of Oxford
Steven Kou: Boston University
Yuhong Xu: Soochow University

Digital Finance, 2021, vol. 3, issue 2, No 1, 97 pages

Abstract: Abstract 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 portfolio’s log returns. We obtain analytical and time-consistent optimal portfolio policies under jump-diffusion models and regime-switching models.

Keywords: FinTech; Dynamic mean-variance; Time-consistence; Time-varying mean returns (search for similar items in EconPapers)
JEL-codes: C61 D81 G11 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s42521-021-00028-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:digfin:v:3:y:2021:i:2:d:10.1007_s42521-021-00028-4

Ordering information: This journal article can be ordered from
https://www.springer.com/finance/journal/42521

DOI: 10.1007/s42521-021-00028-4

Access Statistics for this article

Digital Finance is currently edited by Wolfgang Karl Härdle, Steven Kou and Min Dai

More articles in Digital Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().