چکیده (انگلیسی):

Index tracking is an investment approach where the primary objective is to keep portfolio return as close as
possible to a target index without purchasing all index components. The main purpose is to minimize the
tracking error between the returns of the selected portfolio and a benchmark. In this study, quadratic as well
as linear models are presented for minimizing the tracking error. The uncertainty is considered in the input
data using a tractable robust framework that controls the level of conservatism while maintaining linearity.
The linearity of the proposed robust optimization models allows a simple implementation of an ordinary
optimization software package to find the optimal robust solution. The proposed model of this study
employs Morgan Stanley Capital International Index as the target index and the results are reported for six
national indices including Japan, the USA, the UK, Germany, Switzerland and France. The performance of
the proposed models is evaluated using several financial criteria e.g., information ratio, market ratio, Sharpe
ratio and Treynor ratio. The preliminary results demonstrate that the proposed model lowers the amount of
tracking error while raising values of portfolio performance measures.