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Prediction Risk and the Forecasting of Stock Market Indexes

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  • Haefke, Christian

    (Department of Economics, Institute for Advanced Studies, Vienna)

  • Helmenstein, Christian

    (Department of Economics, Institute for Advanced Studies, Vienna)

Abstract

In most of the empirical research on capital markets, stock market indexes are used as proxies for the aggregate market development. In previous work we found that a particular market segment might be less efficient than the whole market and hence easier to forecast. In this paper we extend the focus of this investigation by taking a comprehensive look at the Vienna Stock Exchange. We use feedforward networks and linear models to forecast the all share index WBI as well as various subindexes covering the highly liquid, semi-liquid, and initial public offering (IPO) market segment. In order to shed some light on network construction principles, we compare different models as selected by hold-out crossvalidation (HCV), Akaike's information criterion (AIC), and Schwartz' information criterion (SIC). The forecasts are subsequently evaluated on the basis of hypothetical trading in the out-of-sample period.

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File URL: http://www.ihs.ac.at/publications/eco/es-20.pdf
File Function: First version, 1995
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Bibliographic Info

Paper provided by Institute for Advanced Studies in its series Economics Series with number 20.

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Length: 18 pages
Date of creation: Dec 1995
Date of revision:
Handle: RePEc:ihs:ihsesp:20

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Related research

Keywords: Neural Network Architecture Selection; Information Criteria; Stock Market Indexes; Trading Strategy;

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