Forecasting the New York stock exchange composite index with past price and interest rate on condition of volume spike

    Authors

    W. Leigh; R. Hightower;N. Modani

    Comments

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    Abbreviated Journal Title

    Expert Syst. Appl.

    Keywords

    market efficiency; security market forecasting; financial expert system; neural networks; data mining; NEURAL-NETWORK; RETURNS; MODELS; MARKET; Computer Science, Artificial Intelligence; Engineering, Electrical &; Electronic; Operations Research & Management Science

    Abstract

    We identify trading volume spikes through use of the template matching technique from statistical pattern recognition. For those trading days meeting the condition signifying volume spike recognition, application of linear regression models the future change in price using historical price and prime interest rate values. Also, we train a nonlinear neural network model and use it as a basis for simulated trading, which includes consideration of transaction costs and cash dividends. We illustrate and test with New York Stock Exchange Composite Index data for the period from 1981 to 1999. Results are positive, robust, systematic, economically significant, and informative as to the role of trading volume in the stock market mechanism. (C) 2004 Elsevier Ltd. All fights reserved.

    Journal Title

    Expert Systems with Applications

    Volume

    28

    Issue/Number

    1

    Publication Date

    1-1-2005

    Document Type

    Article

    Language

    English

    First Page

    1

    Last Page

    8

    WOS Identifier

    WOS:000225261500001

    ISSN

    0957-4174

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