Thu, 13 Jun 1996 10:38:49 EDT
(M. Deistler, R. Alt, R. Kunst)
Donnerstag, 20. Juni 1996
"Forecasting Stock Market Averages
to Enhance Profitable Trading Strategies"
Christian HAEFKE and Christian HELMENSTEIN
In this paper we formulate a trading strategy
for stocks that exploits the informational
difference implied by different stock market
index construction principles. In order to gain
a competitive advantage over other market participants,
we forecast the indexes one day ahead and subsequently
generate buy and sell signals through the trading rule.
To illustrate how the system works, we apply it to select
stocks from those constituting the ATX index sample.
The forecasting of the indexes is done applying standard
financial econometric techniques and feedforward neural
networks. Drawing upon various model selection criteria,
such as AIC, HQ and SIC, we discuss their potential for
rendering parsimonious neural network architectures.
Artificial Neural Networks, Model Selection,
Stock Market Indexes, Trading Systems.
Ort: HS II
Zeit: 9.00 Uhr c. t.