This paper investigates the use of influence from foreign
stock markets (intermarket influence) to predict
the trading signals, buy, hold and sell, of the of a given
stock market. Australian All Ordinary Index was selected
as the stock market whose trading signals to
be predicted. Influence is taken into account as a set
of input variables for prediction. Two types of input
variables were considered: quantified (weighted)
input variables and their un-quantified counterparts.
Two criteria was applied to determine the trading signals:
one is based on the relative returns while the
other uses the conditional probability that a given
relative return is greater than or equals zero. The
prediction of trading signals was done by Feedforward
neural networks, Probabilistic neural networks
and so called probabilistic approach which was proposed
in past studies. Results suggested that using
quantified intermarket influence as input variables to
predict trading signals, is more effective than using
their un-quantified counterparts.
Cite as: Tilakaratne, C., Mammadov, M. and Morris, S. (2007). Effectiveness of Using Quantified Intermarket Influence for Predicting Trading Signals of Stock Markets. In Proc. Sixth Australasian Data Mining Conference (AusDM 2007), Gold Coast, Australia. CRPIT, 70. Christen, P., Kennedy, P. J., Li, J., Kolyshkina, I. and Williams, G. J., Eds. ACS. 171-179.
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