Modeling of linear uncertain portfolio selection with uncertain constraint and risk index

IF 4.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Weiwei Guo, Wei-Guo Zhang, Zaiwu Gong
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引用次数: 0

Abstract

Since securities market is subject to a great deal of uncertainty and complexity, the return of securities cannot be accurately estimated by historical data. In this case, it must use experts’ knowledge and judgment. Therefore, we investigate portfolio selection problems in such uncertain environments. First, this paper regards the rate of return on security as an uncertain variable which obeys linear uncertainty distribution, and then provides the analytical expressions of the corresponding risk, return and risk index in the uncertain portfolio selection environment. Afterwards, we construct three types uncertain portfolio selection models with uncertain constraint, namely, the minimizing risk, the maximizing return and the maximizing belief degree. Meanwhile, in order to more intuitively reflect the investor’s sense of loss, three types uncertain portfolio selection models considering both uncertain constraint and risk index are also constructed. These models are transformed into corresponding deterministic models. Finally, through an example analysis, this paper obtains the portfolio selection strategies under different objectives, compares the results under different models, and analyzes the sensitivity of the parameters.

Abstract Image

具有不确定约束和风险指数的线性不确定投资组合选择建模
由于证券市场具有很大的不确定性和复杂性,证券收益无法通过历史数据进行准确估算。在这种情况下,必须利用专家的知识和判断。因此,我们研究了这种不确定环境下的投资组合选择问题。首先,本文将证券收益率视为服从线性不确定性分布的不确定变量,然后给出了不确定投资组合选择环境下相应的风险、收益和风险指数的解析表达式。随后,我们构建了三种具有不确定性约束的不确定投资组合选择模型,即风险最小化、收益最大化和信念度最大化模型。同时,为了更直观地反映投资者的损失感,我们还构建了同时考虑不确定约束和风险指数的三类不确定投资组合选择模型。并将这些模型转化为相应的确定性模型。最后,本文通过实例分析,得到了不同目标下的投资组合选择策略,比较了不同模型下的结果,并分析了参数的敏感性。
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来源期刊
Fuzzy Optimization and Decision Making
Fuzzy Optimization and Decision Making 工程技术-计算机:人工智能
CiteScore
11.50
自引率
10.60%
发文量
27
审稿时长
6 months
期刊介绍: The key objective of Fuzzy Optimization and Decision Making is to promote research and the development of fuzzy technology and soft-computing methodologies to enhance our ability to address complicated optimization and decision making problems involving non-probabilitic uncertainty. The journal will cover all aspects of employing fuzzy technologies to see optimal solutions and assist in making the best possible decisions. It will provide a global forum for advancing the state-of-the-art theory and practice of fuzzy optimization and decision making in the presence of uncertainty. Any theoretical, empirical, and experimental work related to fuzzy modeling and associated mathematics, solution methods, and systems is welcome. The goal is to help foster the understanding, development, and practice of fuzzy technologies for solving economic, engineering, management, and societal problems. The journal will provide a forum for authors and readers in the fields of business, economics, engineering, mathematics, management science, operations research, and systems.
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