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Abstract
This thesis describes an attempt to predict the next value in a .nancial time series using various arti .cial techniques.The time series in question consists of daily values for commodities futures.First,an arti .cial neural network is used as a pre- dictor.Then the neural network is augmented with a genetic algorithm.The genetic algorithm .rst is used to select the parameters for the neural network.Then in a seperate experiment the genetic algorithm is used to evolve the weights of the network.The various approaches had similar results.