Portfolio Selection by Means of Artificial Bee Colony Algorithm and its Comparison with Genetic Algorithm and Ant Colony Algorithm

Investment decision making is one of the key issues in financial management. Investor might know about different asset types when facing with various options and the ways in which investors can incorporate them in devising a strategy is significant. Selecting the appropriate tools and techniques that can make optimum portfolio is one of the main objectives of the investment world. In this study it is tried to optimize the decision making in stock selection or optimization of portfolio by means of artificial colony of honeybee algorithm. And to determine the effectiveness of the algorithm, Sharp criteria algorithm, the trainer criteria and its downside risk were calculated and compared with the portfolio made up of genetic and ant colony algorithms .The sample consisted of active firms listed in the Tehran Stock Exchange from 2005 to 2015. The sample was selected by the systematic removal method. The findings show that Sharp criteria algorithm formed by the artificial bee colony algorithm functions better than the genetic and ant colony algorithms in terms of portfolio formation .However, the trainer's criteria and downside risk of the stock portfolio formed through the artificial bee colony algorithm shows the optimum function, this difference is not statistically significant.