Multiportfolio Optimization: A Fairness-Aware Target-Oriented Model

• DOI: 10.1287/msom.2021.0363
• Publication Date: 2024-03-05T14:42:33Z
• Authors: Xiaoqiang Cai; Daniel Zhuoyu Long; Gen Yu; Lianmin Zhang
• Keywords: 0502 economics and business; 05 social sciences

Problem definition: We consider a multiportfolio optimization problem in which nonlinear market impact costs result strong dependency of one account’s performance on the trading activities other accounts. Methodology/results: develop novel target-oriented model that jointly optimizes rebalancing trades and split costs. The key advantages our proposed include consideration clients’ targets investment returns incorporation distributional uncertainty. former helps fund managers to circumvent difficulty identifying utility functions or risk parameters, whereas latter addresses practical challenge probability distribution risky asset cannot be fully observed. Specifically, evaluate quality multiple portfolios’ payoffs achieving targets, we propose new class measures, called fairness-aware multiparticipant satisficing (FMS) criteria. These criteria can extended encompass uncertainty have salient feature addressing fairness issue with collective level as determined by least satisfied participant. find that, structurally, FMS dual connection set measures. For optimization, criterion conditional value-at-risk being underlying measure further account for magnitude shortfalls against targets. resulting problem, although nonconvex, solved efficiently solving an equivalent converging sequence tractable subproblems. Managerial implications: numerical study shows approach outperforms utility-based models out-of-sample performance. More generally, provide decision framework operational problems makers are rather than maximizers issues ambiguity should considered. Funding: This work was supported Hong Kong Research Grants Council [Grants 14210821, 16204521], Leading Talent Program Guangdong Province [Grant 2016LJ06D703], National Natural Science Foundation China 71971187, 72171156, 72231002, 72331009]. Supplemental Material: online appendix is available at https://doi.org/10.1287/msom.2021.0363 .