Portfolio Optimization by Means of Meta Heuristic Algorithms

• Main Authors: Mahmoud Rahmani, Maryam Khalili Eraqi, Hashem Nikoomaram
• Format: Article
• Language: English
• Published: Islamic Azad University of Arak 2019-10-01
• Series: Advances in Mathematical Finance and Applications
• Subjects: artificial bee colony; portfolio optimization; genetic algorithm; ant colony algorithm
• Online Access: http://amfa.iau-arak.ac.ir/article_666216_8cdb279385068252b70b1e6751b28e87.pdf

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