Neural network model to exploit the econometric properties of Austrian IPOs

Christian Haefke, Christian Helmenstein

    Research output: Contribution to conferencePaper

    Abstract

    In this paper we apply cointegration and Granger-causality analyses to specify linear and neural network error-correction models for an Austrian Initial Public Offerings IndeX (IPOXATX). We use the significant relationship between the IPOXATX and the Austrian Stock Market Index ATX to forecast the IPOXATX. For prediction purposes we apply augmented feedforward neural networks whose architecture is determined by Sequential Network Construction with the Schwartz Information Criterion as an estimator for the prediction risk. The results suggest that trading schemes based on the forecasts significantly increase an investor's return as compared to Buy and Hold or simple Moving Average trading strategies.

    Original languageEnglish (US)
    Pages128-135
    Number of pages8
    StatePublished - Dec 1 1995
    EventProceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering (CIFEr) - New York, NY, USA
    Duration: Apr 9 1995Apr 11 1995

    Other

    OtherProceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering (CIFEr)
    CityNew York, NY, USA
    Period4/9/954/11/95

    Fingerprint

    Neural networks
    Linear networks
    Feedforward neural networks
    Error correction
    Network architecture
    Econometrics
    Network model
    Prediction
    Financial markets
    Investors
    Granger causality
    Moving average
    Information criterion
    Initial public offerings
    Stock market index
    Estimator
    Cointegration
    Error correction model
    Trading strategies

    ASJC Scopus subject areas

    • Computer Science(all)
    • Economics, Econometrics and Finance(all)
    • Engineering(all)

    Cite this

    Haefke, C., & Helmenstein, C. (1995). Neural network model to exploit the econometric properties of Austrian IPOs. 128-135. Paper presented at Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering (CIFEr), New York, NY, USA, .

    Neural network model to exploit the econometric properties of Austrian IPOs. / Haefke, Christian; Helmenstein, Christian.

    1995. 128-135 Paper presented at Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering (CIFEr), New York, NY, USA, .

    Research output: Contribution to conferencePaper

    Haefke, C & Helmenstein, C 1995, 'Neural network model to exploit the econometric properties of Austrian IPOs' Paper presented at Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering (CIFEr), New York, NY, USA, 4/9/95 - 4/11/95, pp. 128-135.
    Haefke C, Helmenstein C. Neural network model to exploit the econometric properties of Austrian IPOs. 1995. Paper presented at Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering (CIFEr), New York, NY, USA, .
    Haefke, Christian ; Helmenstein, Christian. / Neural network model to exploit the econometric properties of Austrian IPOs. Paper presented at Proceedings of the IEEE/IAFE 1995 Computational Intelligence for Financial Engineering (CIFEr), New York, NY, USA, .8 p.
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