Title
An analysis of a hybrid neural network and pattern recognition technique for predicting short-term increases in the NYSE composite index
Abbreviated Journal Title
Omega-Int. J. Manage. Sci.
Keywords
stock market forecasting; neural networks; pattern recognition; heuristics; financial decision support; efficient markets hypothesis; technical analysis; Management; Operations Research & Management Science
Abstract
We introduce a method for combining template matching, from pattern recognition, and the feed-forward neural network, from artificial intelligence, to forecast stock market activity. We evaluate the effectiveness of the method for forecasting increases in the New York Stock Exchange Composite Index at a 5 trading day horizon. Results indicate that the technique is capable of returning results that are superior to those attained by random choice. (C) 2002 Elsevier Science Ltd. All rights reserved.
Journal Title
Omega-International Journal of Management Science
Volume
30
Issue/Number
2
Publication Date
1-1-2002
Document Type
Article
Language
English
First Page
69
Last Page
76
WOS Identifier
ISSN
0305-0483
Recommended Citation
"An analysis of a hybrid neural network and pattern recognition technique for predicting short-term increases in the NYSE composite index" (2002). Faculty Bibliography 2000s. 3310.
https://stars.library.ucf.edu/facultybib2000/3310
Comments
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