Stock Price Forecasting using Higher Order Neural Networks

A.M. Kimiagari, M. Keyvanloo, M. Fallahnezhad, M.H. Moradi, and A.B. Farimani (Iran)


Stock Price, Forecasting, Higher Order Neural Network (Honn)


An advancement on artificial neural networks (ann) and higher order neural networks (honn) are conducted on the theoretical results of the stock price forecasting. We used honn as a strongopen box intelligent unit in comparison with traditional black box neural networks for forecasting the stock price results. It is shown that by having the honn model of nonlinear stock pattern applied in this study, there are many advantageous compared against ann model and ,additionally; this model provides less cpu time, less rms error and better fitting properties. The experimental results are compared with ones in chang and liu, 2008[1].

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