A Novel Hybrid ICA-FA Algorithm for Multiperiod Uncertain Portfolio Optimization Model Based on Multiple Criteria

This paper deals with a multiperiod portfolio selection problem in an uncertain investment environment, in which the returns of securities are assumed to be uncertain variables and determined by experts' subjective evaluation. Based on uncertain theory, we present a novel multiperiod multiobjec...

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Published inIEEE transactions on fuzzy systems Vol. 27; no. 5; pp. 1023 - 1036
Main Authors Chen, Wei, Li, Dandan, Liu, Yong-Jun
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Constraint modelling
Evolutionary algorithms
Goal programming
Heuristic methods
Imperialist competitive algorithm-firefly algorithm (ICA-FA) algorithm
Investment
Mathematical programming
multiperiod portfolio multiple criteria decision-making
Multiple criterion
Multiple objective analysis
Numerical models
Optimization
Optimization models
Portfolios
Programming
Security
uncertain variables
Uncertainty
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Abstract This paper deals with a multiperiod portfolio selection problem in an uncertain investment environment, in which the returns of securities are assumed to be uncertain variables and determined by experts' subjective evaluation. Based on uncertain theory, we present a novel multiperiod multiobjective mean-variance-skewness model by considering multiple realistic investment constraints such as transaction cost, bounds on holdings, cardinality, etc. For the proposed solution, we first apply a weighted max-min fuzzy goal programming approach to convert the proposed multiobjective programming model into a single-objective one. After that, we design a novel hybrid of an imperialist competitive algorithm (ICA) and a firefly algorithm (FA), termed ICA-FA, to solve it. Finally, we provide a numerical example to demonstrate the effectiveness of the proposed model and corresponding algorithm.
AbstractList This paper deals with a multiperiod portfolio selection problem in an uncertain investment environment, in which the returns of securities are assumed to be uncertain variables and determined by experts' subjective evaluation. Based on uncertain theory, we present a novel multiperiod multiobjective mean-variance-skewness model by considering multiple realistic investment constraints such as transaction cost, bounds on holdings, cardinality, etc. For the proposed solution, we first apply a weighted max-min fuzzy goal programming approach to convert the proposed multiobjective programming model into a single-objective one. After that, we design a novel hybrid of an imperialist competitive algorithm (ICA) and a firefly algorithm (FA), termed ICA-FA, to solve it. Finally, we provide a numerical example to demonstrate the effectiveness of the proposed model and corresponding algorithm.
Author Chen, Wei
Liu, Yong-Jun
Li, Dandan
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  givenname: Yong-Jun
  surname: Liu
  fullname: Liu, Yong-Jun
  email: bmyjliu@scut.edu.cn
  organization: School of Business Administration, South China University of Technology, Guangzhou, China
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Snippet This paper deals with a multiperiod portfolio selection problem in an uncertain investment environment, in which the returns of securities are assumed to be...
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SubjectTerms Algorithms
Constraint modelling
Evolutionary algorithms
Goal programming
Heuristic methods
Imperialist competitive algorithm-firefly algorithm (ICA-FA) algorithm
Investment
Mathematical programming
multiperiod portfolio multiple criteria decision-making
Multiple criterion
Multiple objective analysis
Numerical models
Optimization
Optimization models
Portfolios
Programming
Security
uncertain variables
Uncertainty
Title A Novel Hybrid ICA-FA Algorithm for Multiperiod Uncertain Portfolio Optimization Model Based on Multiple Criteria
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