Univrsity Of Tehran Press Financial Research Journal 1024-8153 19 2 2017 07 23 Index Tracking Optimization under down Side Beta and Evolutionary Based Algorithms Index Tracking Optimization under down Side Beta and Evolutionary Based Algorithms 319 340 64814 10.22059/jfr.2017.226501.1006374 FA Ahmad Nabizade Assistant Prof, Faculty of Financial Science, Kharazmi University, Tehran, Iran Hadi Gharehbaghi MSc in Financial Management, Faculty of Financial Science, Kharazmi University, Tehran, Iran 0009-0007-4636-8117 Adel Behzadi Ph.D. Candidate in Financial Engineering, University of Tehran, Tehran, Iran Journal Article 2017 01 30 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.   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.   https://jfr.ut.ac.ir/article_64814_70a6d0ab10eecafa8b4f616717172fef.pdf