Fitness function evaluation for MA trading strategies based on genetic algorithms

Authors:
José Pinto;Rui Ferreira Neves;Nuno Horta
Affiliations:
Instituto de Telecomunicações, IST, Lisboa, Portugal;Instituto de Telecomunicações, IST, Lisbon, Portugal;Instituto de Telecomunicações, IST, Lisboa, Portugal
Venue:
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Year:
2011

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Abstract

This paper presents a new approach to optimize an investment strategy based on moving averages (MA). The proposed approach optimizes the entry and exit points, for both long and short positions, using a genetic algorithm (GA) kernel. This approach outperforms B&H strategy and explores alternative functions to the classical absolute return fitness function. The approach is demonstrated for major market indexes, such as, S&P 500, FTSE100, DAX30, NIKKEI225.