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Forecasting the direction of change in sector stock indexes: An application of neural networks

Author

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  • Stanley R Stansell

    (Robert Dillard Teer Distinguished Professor of Business, East Carolina University)

  • Stanley G Eakins

Abstract

In this study, neural network modelling procedures are used to forecast the direction of change in 19 sector stock indexes. Publicly available historical data on 19 economic indexes are used to perform the forecasts. Two separate sets of forecasts for each of the sector stock indexes are performed for the months January–May 2001 and for the months January–March 2003. The results are evaluated both on the basis of ability to forecast the direction of change in the stock index and on the basis of total gains in terms of index points. The results indicate that the models have some ability to forecast stock index changes.

Suggested Citation

  • Stanley R Stansell & Stanley G Eakins, 2004. "Forecasting the direction of change in sector stock indexes: An application of neural networks," Journal of Asset Management, Palgrave Macmillan, vol. 5(1), pages 37-48, June.
    • Handle: RePEc:pal:assmgt:v:5:y:2004:i:1:d:10.1057_palgrave.jam.2240126
    DOI: 10.1057/palgrave.jam.2240126
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    Cited by:

    1. Adam Fadlalla & Farzaneh Amani, 2014. "Predicting Next Trading Day Closing Price Of Qatar Exchange Index Using Technical Indicators And Artificial Neural Networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 209-223, October.
    2. Timotej Jagric & Sebastjan Strasek, 2011. "Behavioural patterns as determinants of market movements: evidence from an emerging market," Applied Financial Economics, Taylor & Francis Journals, vol. 21(7), pages 481-491.

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