Index Tracking Optimization under down Side Beta and Evolutionary Based Algorithms

Portfolio optimization is the one of most important problems in financial theory. Different strategies can be selected to manage the portfolio that include two kinds is called passive and active. Index tracking is one of most important passive approach. So, there are different models and algorithms to make index tracking portfolio. The aim of this research is analyze of down side beta in the index tracking portfolio. So, three models are presented. Then, to solve these models, evolutionary algorithms include genetic and deferential evolutionary algorithm is used. To show sufficiency of the models, Tehran stock exchange data are selected. Results show the model based down side beta with deferential evolutionary algorithm has higher efficiency Compared with two another models.