File(s) not publicly available
Application of Genetic Algorithms to the Optimisation of Neural Network Configuration for Stock Market Forecasting
© Springer-Verlag Berlin Heidelberg 2001. Neural networks are recognised as an effective tool for predicting stock prices (Shin & Han, 2000), but little is known about which configurations are best and for which indices. The present study uses genetic algorithms to find a near optimal learning rate, momentum, tolerance and network architecture for 47 indices listed on the Australian Stock Exchange (ASX). Some relationships were determined between stock index and neural network attributes, and important observations were made for the further development of a methodology for determining optimal neural network configurations.
History
Publication title
AI 2001: Advances in Artificial IntelligenceVolume
LNAI 2256Editors
M Stumptner, D CorbettPagination
285-296ISBN
3-540-42960-3Department/School
School of Information and Communication TechnologyPublisher
Springer-VerlagPlace of publication
BerlinEvent title
14th Australian Joint Conference on Artificial IntelligenceEvent Venue
AdelaideDate of Event (Start Date)
2001-12-10Date of Event (End Date)
2001-12-14Repository Status
- Restricted