基于前景理论的多模糊参考区间投资组合选择

IF 8.7 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-07-14 DOI:10.1109/TSMC.2025.3578997

Xianhe Wang;Bo Wang;Long Teng;Yaoxin Wu

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引用次数: 0

摘要

投资组合选择是决策和管理工程领域中最重要的关注点。然而，由于资本市场固有的复杂性和非理性投资者行为的存在，投资者实现预定的投资目标仍然是一个巨大的挑战。为了全面描述投资者的行为模式，并在高度不确定和波动的市场中提供投资指导，本研究引入了一种新的模糊模型来表示前景理论，并在此基础上开发了一种新的投资组合优化框架。在此基础上，提出了一种结合自适应和协同策略的粒子群优化方法来求解该模型的最优解。通过使用实际市场数据的两个案例研究验证了该模型的有效性，同时通过基于测试适应度函数的案例研究证实了该求解算法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Prospect Theory-Based Portfolio Selection Using Multiple Fuzzy Reference Intervals

Portfolio selection stands as a paramount concern within the realm of decision-making and management engineering. However, owing to the inherent intricacies of capital markets and the presence of irrational investor behaviors, the attainment of predefined investment objectives by investors remains a formidable challenge. In order to comprehensively depict investor behavior patterns and to provide investment guidance in highly uncertain and volatile markets, this study introduces a novel fuzzy model for representing prospect theory and based on this, develops a novel portfolio selection optimization framework. In addition, a new particle swarm optimization consists of adaptive and cooperative strategy is proposed to find the optimal solution of this model. The effectiveness of this model is validated through two case study utilizing real-market data, while the efficiency of the solution algorithm is confirmed through a test fitness functions-based case study.

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来源期刊

IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS

CiteScore

18.50

自引率

11.50%

发文量

812

审稿时长

6 months

期刊介绍： The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.