基于梯形模糊变量的多种风险比较的多准则可信投资组合选择模型

IF 4.6 2区 数学 Q1 MATHEMATICS, APPLIED
J. Pahade, M. Jha
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引用次数: 0

摘要

模糊集合理论在处理投资组合模型问题时,有效地插值了投资者的态度。信用理论(模糊集理论的一个分支)被广泛用于描述金融市场的不确定性。我们把每只风险股票的收益率看作一个梯形模糊数。股票模糊收益的方差和半方差是投资组合模型中被广泛接受的风险度量。本文给出了梯形模糊变量的可信半方差,并将其应用于股票模糊投资组合风险的量化。以金融资产主要市场的历史数据集为例,提出了一种多准则可信均值-半方差-偏度模型,并给出了数值说明。考虑投资组合预期收益、投资组合预期收益风险和投资组合偏度三个目标,并结合基数约束、完全资金利用、下限和上限约束、无卖空约束,构建多目标规划问题。针对所提出的多目标优化问题,提出了最优目标规划方法。最后,通过印度主要金融股市场孟买证券交易所(BSE)的实际数据,进行了一个案例研究,以突出所提出模型的有效性。并将半方差作为风险度量与其他现有风险度量的结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-criteria Credibilistic Portfolio Selection Model with Various Risk Comparisons Using Trapezoidal Fuzzy Variable
Dealing with problems on portfolio selection models fuzzy set theory is effectively interpolating investor’s attitude. The credibility theory (Branch of fuzzy set theory) is broadly utilized to describe uncertainty of the financial markets. We regard the return rate of each risky stock as a trapezoidal fuzzy number. Variance and semi-variance of fuzzy return on stocks are widely accepted as risk measures in portfolio selection models. This paper obtains credibilistic semi-variance of trapezoidal fuzzy variable and applied this concept to quantify the risk in stock fuzzy portfolio selection. A multi-criteria credibilistic mean-semivariance-skewness model is proposed with numerical illustration taking historical data set from the premier market for financial assets. Three objectives are taken into account namely, expected portfolio return, risk on expected portfolio return and portfolio skewness to construct multi-objective programming problem, along with cardinality constraint, complete capital utilization, floor and ceiling constraint, no short selling constraints. To solve the proposed multi-objective optimization problem, optimal goal programming approach is suggested. Finally, a case study is conducted to highlight the effectiveness of the proposed models through the real-world data from the Bombay Stock Exchange (BSE), an Indian premier market for financial stocks. Furthermore, results comparison of semi-variance as risk measure with other existing risk measures is performed.
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来源期刊
CiteScore
8.80
自引率
5.00%
发文量
18
审稿时长
6 months
期刊介绍: Applied and Computational Mathematics (ISSN Online: 2328-5613, ISSN Print: 2328-5605) is a prestigious journal that focuses on the field of applied and computational mathematics. It is driven by the computational revolution and places a strong emphasis on innovative applied mathematics with potential for real-world applicability and practicality. The journal caters to a broad audience of applied mathematicians and scientists who are interested in the advancement of mathematical principles and practical aspects of computational mathematics. Researchers from various disciplines can benefit from the diverse range of topics covered in ACM. To ensure the publication of high-quality content, all research articles undergo a rigorous peer review process. This process includes an initial screening by the editors and anonymous evaluation by expert reviewers. This guarantees that only the most valuable and accurate research is published in ACM.
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