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

Helmenstein, Christian and Häfke, Christian (1995) Neural Networks in the Capital Markets: An Application to Index Forecasting. Department of Economics Working Paper Series, 32. Inst. für Volkswirtschaftstheorie und -politik, WU Vienna University of Economics and Business, Vienna.

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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.

Item Type: Paper
Divisions: Departments > Volkswirtschaft
Depositing User: Mohammad Al Hessan
Date Deposited: 03 May 2018 06:55
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/6308

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