An analysis of a hybrid neural network and pattern recognition technique for predicting short-term increases in the NYSE composite index

    Authors

    W. Leigh; M. Paz;R. Purvis

    Comments

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    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

    WOS:000174457100001

    ISSN

    0305-0483

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