Risk and Potential: An Asset Allocation Framework with Applications to Robo-Advising

32 Pages Posted: 6 Nov 2019 Last revised: 22 Feb 2021

See all articles by Xiangyu Cui

Xiangyu Cui

Shanghai University of Finance and Economics - School of Statistics and Management

Duan Li

Chinese University of Hong Kong; City University of Hong Kong

Xiao Qiao

School of Data Science, City University of Hong Kong; Paraconic Technologies US Inc.

Moris Simon Strub

Southern University of Science and Technology - Department of Information Systems and Management Engineering

Date Written: May 11, 2019

Abstract

We propose a novel dynamic asset allocation framework based on a family of mean-variance induced utility functions that overcome the non-monotonicity and time-inconsistency problems of mean-variance optimization. The utility functions are motivated by the equivalence between the mean-variance objective and a quadratic utility function. Crucially, our framework differs from mean-variance analysis in that we allow different treatment of upside and downside deviations from a target wealth level, which naturally leads to a different characterization of investment outcomes. Risk can be viewed as the possible outcomes below the target wealth, whereas potential can be used to describe the possible outcomes exceeding the target wealth. Our proposed asset allocation framework retains two attractive features of mean-variance optimization: an intuitive explanation of the investment objective and an easily-computed optimal strategy. We establish a semi-analytical solution for the optimal trading strategy in our framework and provide numerical examples to
illustrate its behavior. Finally, we discuss applications of this framework to robo-advisors.

Keywords: mean-risk optimization; mean-variance; expected utility maximization; portfolio choice; risk; potential; asset allocation; robo-advising; FinTech

JEL Classification: C61, G11

Suggested Citation

Cui, Xiangyu and Li, Duan and Qiao, Xiao and Strub, Moris Simon, Risk and Potential: An Asset Allocation Framework with Applications to Robo-Advising (May 11, 2019). Available at SSRN: https://ssrn.com/abstract=3302111 or http://dx.doi.org/10.2139/ssrn.3302111

Xiangyu Cui

Shanghai University of Finance and Economics - School of Statistics and Management ( email )

777 Guoding Road
Shanghai, Shanghai 200433
China

Duan Li

Chinese University of Hong Kong ( email )

Shatin, New Territories
Hong Kong

City University of Hong Kong

Tat Chee Avenue
Kowloon Tong
Kowloon
Hong Kong
852 3442 8591 (Phone)

Xiao Qiao

School of Data Science, City University of Hong Kong ( email )

Hong Kong

Paraconic Technologies US Inc. ( email )

New York, NY
United States

HOME PAGE: http://sites.google.com/site/xiaoqiao10/

Moris Simon Strub (Contact Author)

Southern University of Science and Technology - Department of Information Systems and Management Engineering ( email )

1088 Xueyuan Ave
Shenzhen, Guangdong
China

HOME PAGE: http://sites.google.com/view/morisstrub/home

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