Multiportfolio Optimization: A Fairness-Aware Target-Oriented Model

Xiaoqiang Cai (), Daniel Zhuoyu Long (), Gen Yu () and Lianmin Zhang ()
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Xiaoqiang Cai: The Chinese University of Hong Kong, Shenzhen, Guangdong 518172, Peoples Republic of China; Shenzhen Research Institute of Big Data, Guangdong 518172, Peoples Republic of China
Daniel Zhuoyu Long: Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong, China
Gen Yu: Department of Business Administration, University of Zurich, 8032 Zurich, Switzerland
Lianmin Zhang: Shenzhen Research Institute of Big Data, Guangdong 518172, Peoples Republic of China; School of Management and Economics, The Chinese University of Hong Kong, Shenzhen, Guangdong 518172, Peoples Republic of China

Manufacturing & Service Operations Management, 2024, vol. 26, issue 3, 952-971

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

Keywords: multiportfolio; market impact costs; satisficing; distributionally robust; financial service (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:26:y:2024:i:3:p:952-971

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