Forecasting portfolio’s rate of return: a comparison of Artificial Neural Networks with Grey Model and Discrete Grey Model

In this study, Artificial Neural Networks (ANN) is used as a forecasting method and examined if it is the most reliable forecasting method in comparison of Grey Model and Discrete Grey Model(DGM). Thesetwo methods are suggested as accurate forecasting methods to predict portfolio?s rate of return in many different studies. The data is gathered from 29 accepted companies in Tehran stock market, which were announced as the best companies last year. Mean Square of Errors (MSE) is computed for each method and the results are compared. The comparison indicates that ANN with the least MSE has the best result and is the most suitable method for forecasting data used in this study. In continue, the capability of GM(1,1) and DGM is compared and indicated despite of results of previous researches, the performance of GM(1,1) is better than DGM.