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

doi:10.1007/s40305-022-00400-0

Abstract

Abstract: We propose a novel dynamic asset allocation framework based on a family of mean-variance-induced utility functions that alleviate the non-monotonicity and timeinconsistency 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.This naturally leads to a different characterization of possible investment outcomes below and above a target wealth as risk and potential.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.

Key words: Mean-risk optimization, Mean-variance, Expected utility maximization, Portfolio choice, Risk, Potential, Robo-advising, FinTech

CLC Number:

Xiang-Yu Cui, Duan Li, Xiao Qiao, Moris S. Strub. Risk and Potential:An Asset Allocation Framework with Applications to Robo-Advising[J]. Journal of the Operations Research Society of China, 2022, 10(3): 529-558.

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URL: https://www.jorsc.shu.edu.cn/EN/10.1007/s40305-022-00400-0

https://www.jorsc.shu.edu.cn/EN/Y2022/V10/I3/529

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

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