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Index forecasting and model selection

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  • Christian Haefke
  • Christian Helmenstein

Abstract

In this paper we derive a trading strategy that exploits the informational difference implied by different stock market index construction principles. In order to gain a competitive advantage over other market participants we forecast the indexes one day ahead and subsequently generate buy and sell signals through the trading rule. To illustrate how the system works we apply it to select from those stocks that are included in the Austrian Traded Index (ATX). The forecasting of the indexes is performed on the basis of standard financial econometric techniques and feedforward neural networks. We discuss the importance of parsimonious modeling and the applicability of information criteria for architecture selection in artificial neural networks. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • Christian Haefke & Christian Helmenstein, 2002. "Index forecasting and model selection," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 11(2), pages 119-135, April.
    • Handle: RePEc:wly:isacfm:v:11:y:2002:i:2:p:119-135
    DOI: 10.1002/isaf.214
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    References listed on IDEAS

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    9. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May.
    10. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-275, July.
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