After introducing Markowitz mean-variance model, decision makers (DMs) and financial planners paid much attention to the matter of portfolio selection, so that DMs explain purposes and investment requirements in the frame of multi-objective mathematic models which are more consistent with decision making realities in optimal portfolio selection. At now there are various methods introduced to optimize such problems. One of the optimization methods is the Compromise Programming (CP) method. In this paper, considering increasing importance of investment in financial portfolios, we propose a new method, called Nadir Compromising Programming (NCP) by expanding a CP-based method for optimization of multi-objective portfolio selection problem. In order to examine NCP performance and operational capability, we implemented a case study by selecting a portfolio with 35 stock indices of Iran stock market. Results of comparing the CP method and proposed method under the same conditions indicate that NCP method results are more consistent with DM purposes.