Stock Trend Prediction With Neural Network Techniques

This thesis presents a study and implementation of stock trend prediction using neural network techniques. The multilayer-perceptron (MLP) and radial basis function network (RBF) are compared with the new neural network technique, Support Vector Machine(SVM). In this study the stock trend is defined...

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Bibliographic Details
Main Author: Mohd Haris Lye Abdullah
Format: Thesis
Published: 2003
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Summary:This thesis presents a study and implementation of stock trend prediction using neural network techniques. The multilayer-perceptron (MLP) and radial basis function network (RBF) are compared with the new neural network technique, Support Vector Machine(SVM). In this study the stock trend is defined as the maximum excess return from the stock index closing level observed within the next 10 days ahead.