Financial Data Mining Using Time delay Neural Networks

  • Kim, Hyun-Jung (Ewha Womans University, College of Business Administration) ;
  • Shin, Kyung-Shik (Ewha Womans University, College of Business Administration)
  • Published : 2001.01.01

Abstract

This study investigates the effectiveness of time delay neural networks(TDNN) for the time dependent prediction domain. Although it is well-known fact that the back-propagation neural network(BPN) performs well in pattern recognition tasks, the method has some limitations in that it can only learn an input mapping of static (or spatial) patterns that are independent of time of sequences. The preliminary results show that the accuracy of TDNN is higher than the standard BPN with time lag. Our proposed approaches are demonstrated by the stork market prediction domain.

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