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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Vydané v:Advances in Fuzzy Systems Ročník 2018; číslo 2018; s. 1 - 9
Hlavní autori: Panwar, Darsha, Srivastava, Namita, Jha, Manoj
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Cairo, Egypt Hindawi Publishing Corporation 01.01.2018
Hindawi
John Wiley & Sons, Inc
Wiley
Predmet:
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
ISSN:1687-7101, 1687-711X
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1687-7101
1687-711X
DOI:10.1155/2018/4279236