One of the significant problems facing capital market investors is choosing the right securities to invest in and create an optimal portfolio. Since the portfolio selection parameters cannot be considered fixed due to market and price fluctuations, a method that takes i More
One of the significant problems facing capital market investors is choosing the right securities to invest in and create an optimal portfolio. Since the portfolio selection parameters cannot be considered fixed due to market and price fluctuations, a method that takes into account data uncertainty should be used. Robust optimization is a scientific solution to the problems in which data uncertainty is present. The present study has been conducted for Robust portfolio optimization based on the omega approach. The present paper introduces the linear omega model as a criterion for calculating risk and provides an optimal Robust omega model. Robust approach used in this research is the Bertsimas and Sim approach. In this approach, Robust counterpart presented for a linear programming model remains linear, maintaining the advantages of the linear programming model in the optimal model. The model developed in this research is randomly selected by real data of 20 stocks of the S&P 500 index for three years, the results show the high efficiency of the model that developmenting models under uncertainty conditions. The results also show that if conservatism increases, the value of the objective function will increase.
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