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Author:Leigh, W.
Paz, M.
Purvis, R.
Title:An analysis of a hybrid neural network and pattern recognition technique for predicting short-term increases in the NYSE composite index
Journal:Omega
2002 : APR, VOL. 30:2, p. 69-76
Index terms:Stock markets
Forecasting
Finance
Decision making
Networks
USA
Freeterms:Technical analysis
Language:eng
Abstract:In the paper, a method for combining template matching, from pattern recognition, and the feed-forward neural network, from artificial intelligence, to forecast stock market activity is introduced. The effectiveness of the method is evaluated for forecasting increases in the New York Stock Exchange (NYSE) Composite Index at a 5 trading day horizon. Results indicate that the technique is capable of returning results that are superiour to those attained by random choice.
SCIMA record nr: 232384
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