An analysis of the robustness of Genetic Algorithm (GA) methodology in the design of trading systems for the Stock Exchange
Laura Núñez‐Letamendia · RePEc: Research Papers in Economics · 2002
This paper analyzes the robustness of Genetic Algorithms (GAs) technique for its application in the field of trading systems design for the Stock Exchange. The functioning of the GA is driven by the control parameters: crossover and mutation probabilities, number of generations, and size of population. Whether the results generated by the application of GAs to a specific problem are conditioned by the value assess to these parameters, becomes a main research field. The purpose of this paper is to develop a sensibility analyses about the dependency of the GA to the value of these parameters. The sensibility analyses is developed in part by a hierarchic GA (a GA which is used to the optimisation of the control parameters of a second GA which is used to design the trading system). The results find that the GAs are a very robustness technique when logical ranges are considered for these parameters (taken into account that there is a high level of complementation between them), with a wide optimisation capacity.