An analytic solution for multi-period uncertain portfolio selection problem

IF 4.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Bo Li, Yufei Sun, Kok Lay Teo
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引用次数: 2

Abstract

The return rates of risky assets in financial markets are usually assumed as random variables or fuzzy variables. For the ever-changing real asset market, this assumption may not always be satisfactory. Thus, it is sometimes more realistic to take the return rates as uncertain variables. However, for the existing works on multi-period uncertain portfolio selection problems, they do not find analytic optimal solutions. In this paper, we propose a method for deriving an analytic optimal solution to a multi-period uncertain portfolio selection problem. First, a new uncertain risk measure is defined to model the investment risk. Then, we formulate a bi-criteria optimization model, where the investment return is maximized, while the investment risk is minimized. On this basis, an equivalent transformation is presented to convert the uncertain bi-criteria optimization problem into an equivalent bi-criteria optimization problem. Then, by applying dynamic programming method, an analytic optimal solution is obtained. Finally, a numerical simulation is carried out to show that the proposed model is realistic and the method being developed is applicable and effective.

多周期不确定投资组合问题的解析解
金融市场中风险资产的收益率通常被假设为随机变量或模糊变量。对于瞬息万变的实物资产市场,这种假设可能并不总是令人满意。因此,将收益率作为不确定变量有时更为现实。然而,对于已有的多周期不确定投资组合问题,它们没有找到解析最优解。本文提出了多周期不确定投资组合问题的解析最优解的推导方法。首先,定义了一种新的不确定风险度量来对投资风险进行建模。在此基础上,建立了投资收益最大化、投资风险最小化的双准则优化模型。在此基础上,提出了一个等价变换,将不确定双准则优化问题转化为等价双准则优化问题。然后,应用动态规划方法,得到了一个解析最优解。最后进行了数值仿真,验证了所建模型的真实性和所开发方法的适用性和有效性。
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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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