Examining the Efficiency of Portfolio Optimization using Model of Minimum-Variance and N/1 in Portfolio Selection

The issue of portfolio selection has always been considered as one of the key issues in the field of investment. To select optimal portfolios, various models and methods have been represented since the initial presentation of the Markowitz approach. However, finding the most efficient model in portfolio selection has always been the subject of concern. Introducing a new model, called “the composition model of minimum-variance and N/1”, this paper aims to examine the efficiency of three different models of portfolio optimization. For this purpose, the performance of the composition model is compared with the sole minimum-variance model and the sole N/1 model. To evaluate the performance of the portfolios, some criteria such as Sharpe ratio, Trainer ratio, Modigliani and Modigliani ratio, Sortino ratio, and Information ratio have been applied. Finally, the TOPSIS multi-criteria decision-making method for ranking the research models has been used. The results indicate the superiority of the composition model over the two models applied solely.