Optimization of Risk and Return Using Fuzzy Multiobjective Linear Programming

Stock selection poses a challenge for both the investor and the finance researcher. In this paper, a hybrid approach is proposed for asset allocation, offering a combination of several methodologies for portfolio selection, such as investor topology, cluster analysis, and the analytical hierarchy pr...

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Veröffentlicht in:Advances in Fuzzy Systems Jg. 2018; H. 2018; S. 1 - 9
Hauptverfasser: Panwar, Darsha, Srivastava, Namita, Jha, Manoj
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cairo, Egypt Hindawi Publishing Corporation 01.01.2018
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John Wiley & Sons, Inc
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ISSN:1687-7101, 1687-711X
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Abstract Stock selection poses a challenge for both the investor and the finance researcher. In this paper, a hybrid approach is proposed for asset allocation, offering a combination of several methodologies for portfolio selection, such as investor topology, cluster analysis, and the analytical hierarchy process (AHP) to facilitate ranking the assets and fuzzy multiobjective linear programming (FMOLP). This paper considers some important factors of stock, like relative strength index (RSI), coefficient of variation (CV), earnings yield (EY), and price to earnings growth ratio (PEG ratio), apart from the risk and return and stocks which are included within these same factors. Employing fuzzy multiobjective linear programming, optimization is performed using seven objective functions viz., return, risk, relative strength index (RSI), coefficient of variation (CV), earnings yield (EY), price to earnings growth ratio (PEG ratio), and AHP weighted score. The FMOLP transforms the multiobjective problem to a single objective problem using the “weighted adaptive approach” in which the weights are calculated by AHP or choices by the investors. The FMOLP model permits choices in solution.
AbstractList Stock selection poses a challenge for both the investor and the finance researcher. In this paper, a hybrid approach is proposed for asset allocation, offering a combination of several methodologies for portfolio selection, such as investor topology, cluster analysis, and the analytical hierarchy process (AHP) to facilitate ranking the assets and fuzzy multiobjective linear programming (FMOLP). This paper considers some important factors of stock, like relative strength index (RSI), coefficient of variation (CV), earnings yield (EY), and price to earnings growth ratio (PEG ratio), apart from the risk and return and stocks which are included within these same factors. Employing fuzzy multiobjective linear programming, optimization is performed using seven objective functions viz., return, risk, relative strength index (RSI), coefficient of variation (CV), earnings yield (EY), price to earnings growth ratio (PEG ratio), and AHP weighted score. The FMOLP transforms the multiobjective problem to a single objective problem using the “weighted adaptive approach” in which the weights are calculated by AHP or choices by the investors. The FMOLP model permits choices in solution.
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Author Panwar, Darsha
Srivastava, Namita
Jha, Manoj
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Copyright Copyright © 2018 Darsha Panwar et al.
COPYRIGHT 2018 John Wiley & Sons, Inc.
Copyright © 2018 Darsha Panwar et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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Snippet Stock selection poses a challenge for both the investor and the finance researcher. In this paper, a hybrid approach is proposed for asset allocation, offering...
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SubjectTerms Algorithms
Analytic hierarchy process
Behavior
Cluster analysis
Clustering
Coefficient of variation
Earnings per share
Expected values
Investment analysis
Investments
Linear programming
Mathematical analysis
Mathematical problems
Methods
Multiple objective analysis
Optimization
Optimization techniques
Portfolio management
Profits
Random variables
Rankings
Risk
Social sciences
Stock exchanges
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Title Optimization of Risk and Return Using Fuzzy Multiobjective Linear Programming
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