Genetic algorithms for portfolio selection problems with minimum transaction lots

2008 ◽  
Vol 185 (1) ◽  
pp. 393-404 ◽  
Author(s):  
Chang-Chun Lin ◽  
Yi-Ting Liu
Keyword(s):  
Genetic Algorithms ◽  
Portfolio Selection ◽  
Selection Problems

scholarly journals Linguistic Z-Number Bonferroni Mean and Linguistic Z-Number Geometric Bonferroni Mean Operators: Their Applications in Portfolio Selection Problems

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 98742-98760
Author(s):  
Amir Hosein Mahmoodi ◽  
Seyed Jafar Sadjadi ◽  
Soheil Sadi-Nezhad ◽  
Roya Soltani ◽  
Farzad Movahedi Sobhani
Keyword(s):  
Portfolio Selection ◽  
Selection Problems ◽  
Bonferroni Mean ◽  
Geometric Bonferroni Mean

scholarly journals A New Decision-Making Method for Stock Portfolio Selection Based on Computing with Linguistic Assessment

2009 ◽  
Vol 2009 ◽  
pp. 1-20 ◽  
Author(s):  
Chen-Tung Chen ◽  
Wei-Zhan Hung
Keyword(s):  
Decision Making ◽  
Portfolio Selection ◽  
Quantitative Data ◽  
Decision Makers ◽  
Stock Selection ◽  
Qualitative And Quantitative ◽  
Selection Problems ◽  
Different Types ◽  
Linguistic Assessment ◽  
Stock Portfolio

The purpose of stock portfolio selection is how to allocate the capital to a large number of stocks in order to bring a most profitable return for investors. In most of past literatures, experts considered the portfolio of selection problem only based on past crisp or quantitative data. However, many qualitative and quantitative factors will influence the stock portfolio selection in real investment situation. It is very important for experts or decision-makers to use their experience or knowledge to predict the performance of each stock and make a stock portfolio. Because of the knowledge, experience, and background of each expert are different and vague, different types of 2-tuple linguistic variable are suitable used to express experts' opinions for the performance evaluation of each stock with respect to criteria. According to the linguistic evaluations of experts, the linguistic TOPSIS and linguistic ELECTRE methods are combined to present a new decision-making method for dealing with stock selection problems in this paper. Once the investment set has been determined, the risk preferences of investor are considered to calculate the investment ratio of each stock in the investment set. Finally, an example is implemented to demonstrate the practicability of the proposed method.

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