Citation
Abdullah, Mohd Haris Lye (2003) Stock Trend Prediction With Neural Network Techniques. Masters thesis, Multimedia University. Full text not available from this repository.
Official URL: http://myto.perpun.net.my/metoalogin/logina.php
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 > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software |
Divisions: | Faculty of Computing and Informatics (FCI) |
Depositing User: | Ms Rosnani Abd Wahab |
Date Deposited: | 29 Jun 2010 03:31 |
Last Modified: | 29 Jun 2010 03:31 |
URII: | http://shdl.mmu.edu.my/id/eprint/722 |
Downloads
Downloads per month over past year
Edit (login required) |