Application of an optimization model for constructing an index tracker portfolio and considering the uncertainty of model parameters by using of robust optimization approach

index tracking is the process of developing a portfolio that reproduces the performance of an index. The tracker portfolio has relatively good diversity and low turnover and low transaction costs. In this paper we applied a binary programming model for index tracking problem. In this model the number of assets for portfolio construction is defined by portfolio manager. The robust optimization framework is applied for considering data uncertainty of correlation coefficient. The out of sample test demonstrated that considering the data uncertainty by robust optimization framework decrease the tracking error and increase the information ratio of portfolio.