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Neural Networks in the Capital Markets: An Application to Index Forecasting

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  • Helmenstein, Christian
  • Häfke, Christian

Abstract

In this article we construct an Index of Austrian Initial Public Offerings (IPOX) which is isomorph to the Austrian Traded Index (ATX). Conjecturing that the ATX qualifies as an explaining variable for the IPOX, we investigate the time trend properties of and the comovement between the two indices. We use the relationship to construct a TJ.eural network and a linear error-correction forecasting model for the IPOX and base a tracling scheme on either forecast. The results suggest that trading based on the forecasts significantly increases an investor's return as compared to Buy and Hold or simple Moving Average trading strategies.

Suggested Citation

  • Helmenstein, Christian & Häfke, Christian, 1995. "Neural Networks in the Capital Markets: An Application to Index Forecasting," Department of Economics Working Paper Series 32, WU Vienna University of Economics and Business.
    • Handle: RePEc:wiw:wus005:6308
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    Cited by:

    1. Gerlinde Fellner & Matthias Sutter, 2009. "Causes, Consequences, and Cures of Myopic Loss Aversion – An Experimental Investigation," Economic Journal, Royal Economic Society, vol. 119(537), pages 900-916, April.
    2. Riedl, Aleksandra & Rocha-Akis, Silvia, 2007. "Testing the tax competition theory: How elastic are national tax bases in western Europe?," Department of Economics Working Paper Series 112, WU Vienna University of Economics and Business.
    3. Helmenstein, Christian, 1995. "The Withdrawal of the State from Economic Activity: An Austrian Capital Market Perspective," Economics Series 19, Institute for Advanced Studies.
    4. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    5. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    6. Annemarie Steidl & Engelbert Stockhammer, 2007. "Coming and leaving. Internal mobility in late Imperial Austria," Department of Economics Working Papers wuwp107, Vienna University of Economics and Business, Department of Economics.
    7. Engelbert Stockhammer & Paul Ramskogler, 2008. "Uncertainty and Exploitation in History," Journal of Economic Issues, Taylor & Francis Journals, vol. 42(1), pages 175-194, March.
    8. Harald Badinger & Ingrid Kubin, 2007. "Vom kurzfristigen zum mittelfristigen Gleichgewicht in einer offenen Volkswirtschaft unter fixen und flexiblen Wechselkursen," Department of Economics Working Papers wuwp101, Vienna University of Economics and Business, Department of Economics.
    9. Salzano Massimo, 2005. "Neural Networks as tools for increasing the forecast and control of complex economic systems. Economics & Complexity - 1999\Vol2 N2 Spec. NEU 99-a," Macroeconomics 0501012, University Library of Munich, Germany.
    10. Pasquale Commendatore & Ingrid Kubin & Carmelo Petraglia, 2009. "Footloose Capital and Productive Public Services," Chapters, in: Neri Salvadori & Pasquale Commendatore & Massimo Tamberi (ed.), Geography, Structural Change and Economic Development, chapter 1, Edward Elgar Publishing.
    11. Özlem Onaran, 2007. "International financial markets and fragility in the Eastern Europe: "can it happen" here?," Department of Economics Working Papers wuwp108, Vienna University of Economics and Business, Department of Economics.

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