Fuzzy Portfolio Selection in COVID-19 Spreading Period Using Fuzzy Goal Programming Model

Tsaur, Ruey-Chyn; Chiu, Chien‐Liang; Huang, Yin-Yin

doi:10.3390/math9080835

Cited by 6 publications

(3 citation statements)

References 33 publications

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“…Various papers have focused on portfolio optimization for particular industries, such as the automotive [16,17], high-tech [18], shipping [19], oil and gas [20,21], and pharmaceutical [22] industries, as well as emerging markets [23] and even cryptocurrencies [24]. Some other papers have taken into account some particularities of the investors (such as the low financial sustainability of the investors [25]) or new economic and social situations (such as the occurrence of the COVID-19 pandemic [26,27]).…”

Section: Introductionmentioning

confidence: 99%

Modeling the Covariance of Financial Assets Using Neutrosophic Fuzzy Numbers

2023

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This paper aims to model the covariance of financial assets using neutrosophic fuzzy numbers. Two main concepts are discussed and used, namely the neutrosophic covariance of the financial assets and the independent neutrosophic portfolios. In terms of methodology, a three-step approach is proposed with the purpose of identifying the independent neutrosophic portfolio return, the independent neutrosophic portfolio risk and the structure of the independent neutrosophic portfolio. For this purpose, neutrosophic fuzzy theory is chosen for this type of approach as it allows a proper modeling of the financial performance indicators by taking into account the probabilities of their achievement. This action is possible even in the situation in which linguistic variables are used for better characterizing the values of the recorded data. Numerical examples are provided in each stage of the methodology description for a better understanding of the proposed approach. The results of the study can be used to substantiate the decisions made by the capital market investors.

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Section: Introductionmentioning

confidence: 99%

Modeling the Covariance of Financial Assets Using Neutrosophic Fuzzy Numbers

2023

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“…It's done to adapt the existing model to the finance market condition and demand from the capital market player. One of the focuses of the research in portfolio selection is the amount of return, risk, and budget proportion that is allocated in choosing the optimal portfolio [9], [10], and [11]. This can be understood because the more significant the involved security value in portfolio selection, the bigger chance of an optimal portfolio being formed.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Portfolio Using Fuzzy Selection

Wardani

Surono

Wen

2022

BAREKENG: J. Math. & App.

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The problem of portfolio optimization concerns the allocation of the investor’s wealth between several security alternatives so that the maximum profit can be obtained. One of the methods used is Fuzzy Portfolio Selection to understand it better. This method separates the objective function of return and the objective function of risk to determine the limit of the membership function that will be used. The goal of this study is to understand the application of the Fuzzy Portfolio Selection method over shares that have been chosen on a portfolio optimization problem, understand return and risk, and understand the budget proportion of each claim. The subject of this study is the shares of 20 companies included in Bursa Efek Indonesia from 1 January 2021 until 1 January 2022. The result of this study shows that from 20 shares, there are 10 shares that is suitable in the forming of optimal portfolio, those are ADRO (0%), ANTM (43.3%), ASII (0%), BBCA (0%), BBRI (0%), BBTN (0%), BRPT (0%), BSDE (0%), ERAA (16%), and INCO (40.7%). The expected return from the portfolio is 0.0878895207 or 8.8% for the return and 0.0226022117 or 2.3% for the risk.

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“…Li et al [21] discussed a dynamic project portfolio selection problem with project divisibility constraints. Tsaur et al [22] proposed a fuzzy return function and considered excess investment using guaranteed return rates for the selecting securities, and then efficient portfolios could be obtained under different levels of investment risk. Tsaur et al [23] revised the Chen and Tsaur fuzzy portfolio model [20] for the COVID-19 pandemic, which has greatly influenced the global economy, by using fuzzy goal programming model with different linguistic descriptions for the imprecise goal of expected return, the future stock market, and the optimal portfolio selection that can be solved under different investment risks.…”

Section: Introductionmentioning

confidence: 99%

Adjustable Security Proportions in the Fuzzy Portfolio Selection under Guaranteed Return Rates

Huang¹,

Chen

Chiu

et al. 2021

Mathematics

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Based on the concept of high returns as the preference to low returns, this study discusses the adjustable security proportion for excess investment and shortage investment based on the selected guaranteed return rates in a fuzzy environment, in which the return rates for selected securities are characterized by fuzzy variables. We suppose some securities are for excess investment because their return rates are higher than the guaranteed return rates, and the other securities whose return rates are lower than the guaranteed return rates are considered for shortage investment. Then, we solve the proposed expected fuzzy returns by the concept of possibility theory, where fuzzy returns are quantified by possibilistic mean and risks are measured by possibilistic variance, and then we use linear programming model to maximize the expected value of a portfolio’s return under investment risk constraints. Finally, we illustrate two numerical examples to show that the expected return rate under a lower guaranteed return rate is better than a higher guaranteed return rates in different levels of investment risks. In shortage investments, the investment proportion for the selected securities are almost zero under higher investment risks, whereas the portfolio is constructed from those securities in excess investments.

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Fuzzy Portfolio Selection in COVID-19 Spreading Period Using Fuzzy Goal Programming Model

Cited by 6 publications

References 33 publications

Modeling the Covariance of Financial Assets Using Neutrosophic Fuzzy Numbers

Modeling the Covariance of Financial Assets Using Neutrosophic Fuzzy Numbers

Optimization of Portfolio Using Fuzzy Selection

Adjustable Security Proportions in the Fuzzy Portfolio Selection under Guaranteed Return Rates

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