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

Reza Abedi Ghahderijani, Sayed Mojtaba Mirlohi, Fariborzjolai and Abdolmajid Abdolbaghi Ataabadi

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.

Volume 12 | Issue 10

Pages: 01-12

DOI: 10.5373/JARDCS/V12I10/20202651