Research Area:  Metaheuristic Computing

Abstract:

Investment decision making is one of the key issues in financial management. Selecting the appropriate tools and techniques that can make optimal portfolio is one of the main objectives of the investment world. This study tries to optimize the decision making in stock selection or the optimization of the portfolio by means of the artificial colony of honey bee algorithm. To determine the effectiveness of the algorithm, its sharp criteria was calculated and compared with the portfolio made up of genes and ant colony algorithms. The sample consisted of active firms listed on the Tehran Stock Exchange from 2005 to 2015. The sample selected by the systematic removal method. The findings show that artificial bee colony algorithm functions better than the genetic and ant colony algorithms in terms of portfolio formation

Keywords:  
Artificial Bee Colony
Portfolio optimization
Genetic Algorithm
Ant Colony Algorithm
Effectiveness
Sharp Criteria

Author(s) Name:  Mahmoud Rahmani, Maryam Khalili Eraqi, Hashem Nikoomaram

Publisher name:  IA University of Arak, Iran

DOI:  10.22034/amfa.2019.579510.1144

Volume Information:  Volume : 4

Paper Link:   https://amfa.arak.iau.ir/article_666216.html