Investigations into Market Index Trading Models Using Evolutionary Automatic Programming

Authors:
Ian Dempsey;Michael O'Neill;Anthony Brabazon
Affiliations:
-;-;-
Venue:
AICS '02 Proceedings of the 13th Irish International Conference on Artificial Intelligence and Cognitive Science
Year:
2002

Citing 4
Cited 4

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Abstract

This study examines the potential of an evolutionary automatic programming methodology to uncover a series of useful technical trading rules for the US S&P stock index. Index values for the period 01/01/1991 to 01/10/1997 are used to train and test the evolved rules. A number of replacement strategies, and a novel approach to constant evolution are investigated. The findings indicate that the automatic programming methodology has much potential with the evolved rules making gains of approximately 13% over a 6 year test period.