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Neural Networks in the Capital Markets: An Application to Index Forecasting
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....
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Published in: | Computational economics 1996-02, Vol.9 (1), p.37-50 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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 neural network and a linear error-correction forecasting model of the IPOX and base a trading scheme on each 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. Citation Copyright 1996 by Kluwer Academic Publishers. |
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ISSN: | 0927-7099 1572-9974 |
DOI: | 10.1007/bf00115690 |