%0 Journal Article %A Hazem M. El-Bakry and Nikos Mastorakis %D 2010 %J International Journal of Computer and Information Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 37, 2010 %T Fast Forecasting of Stock Market Prices by using New High Speed Time Delay Neural Networks %U https://publications.waset.org/pdf/3683 %V 37 %X Fast forecasting of stock market prices is very important for strategic planning. In this paper, a new approach for fast forecasting of stock market prices is presented. Such algorithm uses new high speed time delay neural networks (HSTDNNs). The operation of these networks relies on performing cross correlation in the frequency domain between the input data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented HSTDNNs is less than that needed by traditional time delay neural networks (TTDNNs). Simulation results using MATLAB confirm the theoretical computations. %P 129 - 135