Forecasting Austrian IPOs: An Application of Linear and Neural Network Error-Correction Models

Haefke, Christian and Helmenstein, Christian (December 1995) Forecasting Austrian IPOs: An Application of Linear and Neural Network Error-Correction Models. IHS Economics Series 18

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Abstract or Table of Contents

Abstract: In this paper we apply cointegration and Granger-causality analyses to construct 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. Trading based on the forecasts yields results superior to Buy and Hold or Moving Average trading strategies in terms of mean-variance considerations.;

Item Type: IHS Series
Keywords: 'Initial Public Offerings' 'Neural Networks' 'Stock Market Index' 'Cointegration Analysis'
Classification Codes (e.g. JEL): C53, C45, C43, G12
Status: Published
Date Deposited: 26 Sep 2014 10:36
Last Modified: 04 Apr 2016 11:34
URI: http://irihs.ihs.ac.at/id/eprint/876

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