Random fuzzy mean-absolute deviation models for portfolio optimization problem with hybrid uncertainty

Qin, Zhongfeng

doi:10.1016/j.asoc.2016.06.017

Cited by 42 publications

(9 citation statements)

References 43 publications

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“…Walczak and Rutkowska [10] built a model that involves the mixture of randomness and fuzziness, such as stochastic returns with fuzzy information, for portfolio optimization. Qin [11] proposed a model which innovated the multicriteria decision making (MCDM) problems, by solving the cognitive limitations and the factors that can deviate rational decisions.…”

Section: State Of the Artmentioning

confidence: 99%

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

2019

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As companies operate in a competitive environment, where the struggle for survival on the market is rather tough, the top management face new challenges to identify methods, and even techniques, which allows it to select from the market those assets that provide an optimal ratio between the acquisition cost and the economic performance. In this context, a fuzzy logic managerial decision tool for the assets acquisition is proposed with the paper. The algorithm has three main components: the matrix of the membership degree of the existing bids to asset selection criteria, using fuzzy triangular numbers; the vector of the global membership degree of the bids to the selection criteria and the maximum of the global membership degree as an inference operator for establishing the validated bids by the algorithm. Two scenarios of asset acquisition were tested. After simulations, it was determined that the proposed fuzzy logic managerial decision tool combines, with very good results, the acquisition cost of the assets with their economic performance.

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Section: State Of the Artmentioning

confidence: 99%

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

2019

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“…Numerous models have been proposed by using different approaches. Qin (2017) [35] proposed a random fuzzy mean absolute deviation portfolio selection model. Some researchers extend the single period fuzzy portfolio selection into multiperiod setting.…”

Section: Peng Zhangmentioning

confidence: 99%

RETRACTION: Peng Zhang, Chance-constrained multiperiod mean absolute deviation uncertain portfolio selection

Zhang¹

2019

JIMO

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In this paper, we propose a new multiperiod mean absolute deviation uncertain chance-constrained portfolio selection model with transaction costs, borrowing constraints, threshold constraints and cardinality constraints. In proposed model, the return rate of asset is quantified by uncertain expected value and the risk is characterized by uncertain absolute deviation. The chance constraints are that the uncertain expected return of the portfolio selection is bigger than the preset return of investors under the given confidence level. Cardinality constraints limit the number of assets in the optimal portfolio and threshold constraints limit the amount of capital to be invested in each asset and prevent very small investments in any asset. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs and cardinality constraints, the multiperiod portfolio selection is a mix integer dynamic optimization problem with path dependence, which is NP hard problem. The proposed model is approximated to a mix integer dynamic programming model. A novel discrete iteration method is designed to obtain the optimal portfolio strategy, and is proved linearly convergent. Finally, an example is given to illustrate the behavior of the proposed model and the designed algorithm using real data from the Shanghai Stock Exchange.

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“…Therefore, every investment has a risk, investors should not only consider high returns [7] [8]. In investing, every investor has a risk tolerance under their respective preferences [9] [10]. The formation of a portfolio generally will provide optimum results, i.e.…”

Section: Introductionmentioning

confidence: 99%

“…As well as in Li's research [14], optimizing the portfolio of stock data of Chinese small cap using the asymmetry robust mean absolute deviation model. Also in Qin's study [9], modeling portfolio selection under conditions of hybrid uncertainty, using fuzzy random variables to describe stochastic returns using the mean-absolute deviation model.…”

Section: Introductionmentioning

confidence: 99%

Portfolio Optimization of the Mean-Absolute Deviation Model of Some Stocks using the Singular Covariance Matrix

Kalfin¹,

Carnia²

2019

IJRTE

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Abstract: Investing in the stock sector, investors often face risk problems. Usually, forming an investment portfolio is done to minimize risk. In this research, investment portfolio optimization is discussed. The data analyzed are 8 shares traded on the capital market in Indonesia through the Indonesia Stock Exchange (IDX). Optimization is performed using the Mean-Absolute Deviation model with the singular covariance matrix to determine the optimal weights. The results of portfolio optimization Mean-Absolute Deviation model with singular covariance matrix method, was obtained optimal portfolio weights that is of 17.22% for BBCA shares; 26.64% for TKIM shares; 9.96% for BBRI shares; 9.96% for BBNI shares; 8.70% for BMRI shares; 3.75% for ADRO shares; 6.52% for GGRM shares; and 17.25% for UNTR shares. Where the optimal portfolio composition is obtained the expected rate of return (expected return) of 0.18% with a portfolio risk level (standard deviation) of 0.07%.

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Random fuzzy mean-absolute deviation models for portfolio optimization problem with hybrid uncertainty

Cited by 42 publications

References 43 publications

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

RETRACTION: Peng Zhang, Chance-constrained multiperiod mean absolute deviation uncertain portfolio selection

Portfolio Optimization of the Mean-Absolute Deviation Model of Some Stocks using the Singular Covariance Matrix

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