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Commodity futures price prediction an artificial intelligence approach /

by (Ernest Allen), 1976- Foster

Abstract (Summary)
This thesis describes an attempt to predict the next value in a financial time series using various artificial techniques. The time series in question consists of daily values for commodities futures. First, an artificial neural network is used as a predictor. Then the neural network is augmented with a genetic algorithm. The genetic algorithm first 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. Index words: artificial neural networks, genetic algorithms, commodity futures, time series analysis Commodity Futures Price Prediction, an Artificial Intelligence Approach by Ernest A. Foster B.S., The University of Alabama, 1993 A Thesis Submitted to the Graduate Faculty of The University of Georgia in Partial Fulfillment of the Requirements for the Degree Master of Science Athens, Georgia 2002 c? 2002 Ernest A. Foster All Rights Reserved Commodity Futures Price Prediction, an Artificial Intelligence Approach by Ernest A. Foster Approved: Major Professor: Walter D. Potter Committee: Donald Nute Khaled Rasheed Electronic Version Approved: Maureen Grasso Dean of the Graduate School The University of Georgia December 2002
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School:The University of Georgia

School Location:USA - Georgia

Source Type:Master's Thesis

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