An Improved OIF Elman Neural Network Model with Direction Profit Factor and Its Applications

Abstract

Output-input feedback (OIF) Elman neural network is a dynamic feedback network. An improved model is proposed based on the OIF Elman neural network by introducing direction profit factor in this paper. Moreover, the proposed model is applied to forecast the composite index of stock. In addition, some comparisons are also made when the stock exchange is performed using prediction results from OIF Elman neural network. Simulation results show that the proposed model is feasible and effective in the finance field. It shows that the proposed model can not only improve the forecasting precision evidently and possess the characteristic of quick convergence but also provide a good reference tool for investors to obtain more profits.