A Divide-and-Conquer-based Approach for Diverse Group Stock Portfolio Optimization Using Island-based Genetic Algorithms

2019 ◽  
Author(s):  
Chun-Hao Chen ◽  
Wan-Yi Shen ◽  
Mu-En Wu ◽  
Tzung-Pei Hong
Keyword(s):  
Genetic Algorithms ◽  
Portfolio Optimization ◽  
Divide And Conquer ◽  
Diverse Group ◽  
Stock Portfolio

scholarly journals An Effective Approach for the Diverse Group Stock Portfolio Optimization Using Grouping Genetic Algorithm

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 155871-155884
Author(s):  
Chun-Hao Chen ◽  
Cheng-Yu Lu ◽  
Tzung-Pei Hong ◽  
Jerry Chun-Wei Lin ◽  
Matteo Gaeta
Keyword(s):  
Genetic Algorithm ◽  
Portfolio Optimization ◽  
Diverse Group ◽  
Grouping Genetic Algorithm ◽  
Stock Portfolio

Portfolio Optimization based on Synthetic Fish Congestion Algorithm and Artificial Intelligence: In the Condition of Uncertainty and Half-Variance Risk

2020 ◽  
Vol 12 (10) ◽  
pp. 01-12
Author(s):  
Reza Abedi Ghahderijani ◽  
Sayed Mojtaba Mirlohi ◽  
Fariborzj olai ◽  
Abdolmajid Abdolbaghi Ataabadi
Keyword(s):  
Artificial Intelligence ◽  
Portfolio Optimization ◽  
Hybrid Algorithm ◽  
Combination Method ◽  
Optimal Selection ◽  
Computational Results ◽  
Artificial Immunity ◽  
Variance Risk ◽  
Stock Portfolio ◽  
Selection Of

The issue of stock portfolio optimization is the most well-known issue in the area of optimization. The purpose of this issue is to create a portfolio among different stocks in such a way that it has the highest returns and the least risk. The problem of optimal selection of stock portfolio is one of the Non-deterministic polynomial hardproblems (NP-hard). For this reason, this article introduces a new hybrid algorithm based on artificial immunity algorithm and swarm of fish algorithm. The computational results show that the proposed combination method has the ability to find the best investment boundary in comparison to other proposed methods.

Sign in / Sign up

Export Citation Format

Share Document