Stock Trend Prediction With Neural Network Techniques

Mohd Haris Lye Abdullah, (2003) Stock Trend Prediction With Neural Network Techniques. Masters thesis, Multimedia University.

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Abstract

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.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Mr Shaharom Nizam Mohamed
Date Deposited: 10 Dec 2009 08:27
Last Modified: 15 Dec 2009 06:39
URI: http://shdl.mmu.edu.my/id/eprint/112

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