Investigations into market index trading models using evolutionary automatic programming

Abstract

This study examines the potential of an evolutionary automatic programming methodology to uncover a series of useful technical tradingrules 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 makingg ains of approximately 13% over a 6 year test period.