Commodity Trading Using Neural Networks: Models for the Gold Market

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1997

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Essential to building a good financial forecasting model is having a realistic trading model to evaluate forecasting performance. Using gold trading as a platform for testing we present a profit based model which we use to evaluate a number of different approaches to forecasting. Using novel training techniques we show that neural network forecasting systems are capable of generating returns for above those of classical regression models.

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