Robo-advisor using closed-form solutions for investors’ risk preferences

ABSTRACT

In this article, we design a robo-advisor which has a bi-level framework. The framework enables it to handle a large amount of assets using fast algorithms in the lower level. The proposed robo-advisor can utilize the closed-form solutions for investors’ risk preferences based on corresponding portfolio choices. A dynamic weight is applied to update investors’ risk preferences. Numerical results based on real data in Chinese stock market show that our proposed robo-advisor can accurately estimate the risk preferences of investors and outperform the benchmark formed by market indexes.

KEYWORDS:

• Fintech
• robo-advisor
• risk preferences
• dynamic weight

JEL CLASSIFICATION:

• C61
• D14
• G11

Acknowledgments

We would like to thank the anonymous reviewers and the editor for the constructive and valuable comments, which improve the quality of this article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Nos. 11801433,11571271,11971372] and the National Social Science Foundation of China [No. 16BJY012].