Proposing and solving a multi-objective index tracking portfolio model considering beta, risk and tracking error of the portfolio

There are two strategies in investment management; active and passive. One of the passive strategies is to construct an index tracking portfolio. In the classical models of index tracking portfolio, the goal is to minimize tracking error. However, it may cause to miss portfolio’s beta and unsystematic risk. Considering BETA in index tracking for same behavior with index and control systematic risk which relates to index and non-systematic risk of tracking portfolio will help to minimizing total risk and to close expectation to facts .In this study we propose a multi-objective model to consider portfolio’s beta and unsystematic risk as well as tracking error and studied the simultaneous effect of effective elements (BETA and risk) on index tracking portfolio and comparing suggested function with traditional function and classic portfolio. Goal programming is applied to deal with the multi-objective model and Genetic algorithm is used to solve the model. The proposed model is tested on real-data of Tehran Stock Exchange. The obtained results show the efficiency of the model.