By Topic

Stock market indices in Santiago de Chile: forecasting using neural networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)

Artificial neural networks (ANN) were used to predict the general index of share prices at the Santiago de Chile stock market. Time series with daily values of the index and of total amount of transactions were used to train the ANN. Input data was standardized and normalized shifting mean value to zero, variance to one and maximum values to one. A combined ANN produced better results than simple architectured ANN. The network managed TIS and I-delay memories in parallel. A time delay of ten labor days were sufficient to forecast. Results shows adequate performance of ANN in comparison with other methods used at INDECSA

Published in:

Neural Networks, 1996., IEEE International Conference on  (Volume:4 )

Date of Conference:

3-6 Jun 1996