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faezy razi, F., Shadloo, N. (2017). A Hybrid Grey based Two Steps Clustering and Firefly Algorithm for Portfolio Selection. Journal of Optimization in Industrial Engineering, 10(22), 49-59. doi: 10.22094/joie.2017.276
farshad faezy razi; Naeimeh Shadloo. "A Hybrid Grey based Two Steps Clustering and Firefly Algorithm for Portfolio Selection". Journal of Optimization in Industrial Engineering, 10, 22, 2017, 49-59. doi: 10.22094/joie.2017.276
faezy razi, F., Shadloo, N. (2017). 'A Hybrid Grey based Two Steps Clustering and Firefly Algorithm for Portfolio Selection', Journal of Optimization in Industrial Engineering, 10(22), pp. 49-59. doi: 10.22094/joie.2017.276
faezy razi, F., Shadloo, N. A Hybrid Grey based Two Steps Clustering and Firefly Algorithm for Portfolio Selection. Journal of Optimization in Industrial Engineering, 2017; 10(22): 49-59. doi: 10.22094/joie.2017.276

A Hybrid Grey based Two Steps Clustering and Firefly Algorithm for Portfolio Selection

Article 19, Volume 10, Issue 22, Summer and Autumn 2017, Page 49-59  XML PDF (3 MB)
Document Type: Original Manuscript
DOI: 10.22094/joie.2017.276
Authors
farshad faezy razi email 1; Naeimeh Shadloo2
1Assistant professor, Department of Industrial Management, Semnan Branch, Islamic Azad University, Semnan, Iran
2MSc, Department of Industrial Management, Semnan Branch, Islamic Azad University, Semnan, Iran
Abstract
Considering the concept of clustering, the main idea of the present study is based on the fact that all stocks for choosing and ranking will not be necessarily in one cluster. Taking the mentioned point into account, this study aims at offering a new methodology for making decisions concerning the formation of a portfolio of stocks in the stock market. To meet this end, Multiple-Criteria Decision-Making, Data Mining, and Multi-objective Optimization were employed. First, candidate stocks were clustered using two-step clustering method. Available stocks in each cluster were independently ranked using grey relational analysis. Firefly algorithm was employed for Pareto analysis of risk and ranking. The results of clustering in the stocks revealed that all candidate stocks were not placed in one cluster. The results of robustness analysis employed in ranking method verified the accuracy of calculations in the grey relational analysis through stock repetition of candidates in each cluster.

Highlights
  • This study aims at offering a new methodology for making decisions concerning the formation of a portfolio of stocks in the stock market
  • Candidate stocks were clustered using two-step clustering method. Available stocks in each cluster were independently ranked using grey relational analysis
  • Firefly algorithm was employed for Pareto analysis of risk and ranking. The results of clustering in the stocks revealed that all candidate stocks were not placed in one cluster
  • The results of robustness analysis employed in ranking method verified the accuracy of calculations in the grey relational analysis through stock repetition of candidates in each cluster  
Keywords
Firefly algorithm; Grey Relational Analysis; Multiple-Criteria Decision-Making; Portfolio optimization; Two-Step Clustering
Main Subjects
Design of Experiment
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