Abstract
This paper presents an approach to single-position, intraday automated
trading based on a neurogenetic algorithm. An artificial neural
network is evolved to provide trading signals to a simple automated trading
agent. The neural network uses open, high, low, and close quotes of
the selected financial instrument from the previous day, as well as a selection
of the most popular technical indicators, to decide whether to take a
single long or short position at market open. The position is then closed
as soon as a given profit target is met or at market close. Experimental
results indicate that, despite its simplicity, both in terms of input data
and in terms of trading strategy, such an approach to automated trading
may yield significant returns.