Prediction of stock prices at Kuala Lumpur stock exchange KLSE using artificial neural network
It is known that Artificial Neural Network (ANN) technique that can make prediction. Stock market prices are tough to predict because there are many factors involve thus making it hard to make prediction. Three counters from KLSE, AIRASIA, AMBANK, and ASTRO are chosen to compare the prediction betwe...
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2014
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Online Access: | http://umpir.ump.edu.my/id/eprint/13381/ http://umpir.ump.edu.my/id/eprint/13381/ http://umpir.ump.edu.my/id/eprint/13381/1/FSKKP%20-%20MUHAMMAD%20HAFIZ%20SAMSURI.PDF |
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ump-133812016-06-16T04:20:21Z http://umpir.ump.edu.my/id/eprint/13381/ Prediction of stock prices at Kuala Lumpur stock exchange KLSE using artificial neural network Muhammad Hafiz, Samsuri Q Science (General) T Technology (General) It is known that Artificial Neural Network (ANN) technique that can make prediction. Stock market prices are tough to predict because there are many factors involve thus making it hard to make prediction. Three counters from KLSE, AIRASIA, AMBANK, and ASTRO are chosen to compare the prediction between those counters. Six month's of data from each of those counter are used for the predictions and compared for getting the results. Two values of predictions for today and yesterday are obtained by using the prototype. By comparing both values, the increase and decrease of the stock prices can be revealed. The results from the prototype shows that ANN can be used to predict increase or decrease of the stock prices for each of the related counters. 2014 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/13381/1/FSKKP%20-%20MUHAMMAD%20HAFIZ%20SAMSURI.PDF Muhammad Hafiz, Samsuri (2014) Prediction of stock prices at Kuala Lumpur stock exchange KLSE using artificial neural network. Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:92154&theme=UMP2 |
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Universiti Malaysia Pahang |
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Online Access |
language |
English |
topic |
Q Science (General) T Technology (General) |
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Q Science (General) T Technology (General) Muhammad Hafiz, Samsuri Prediction of stock prices at Kuala Lumpur stock exchange KLSE using artificial neural network |
description |
It is known that Artificial Neural Network (ANN) technique that can make prediction. Stock market prices are tough to predict because there are many factors involve thus making it hard to make prediction. Three counters from KLSE, AIRASIA, AMBANK, and ASTRO are chosen to compare the prediction between those counters. Six month's of data from each of those counter are used for the predictions and compared for getting the results. Two values of predictions for today and yesterday are obtained by using the prototype. By comparing both values, the increase and decrease of the stock prices can be revealed. The results from the prototype shows that ANN can be used to predict increase or decrease of the stock prices for each of the related counters. |
format |
Undergraduates Project Papers |
author |
Muhammad Hafiz, Samsuri |
author_facet |
Muhammad Hafiz, Samsuri |
author_sort |
Muhammad Hafiz, Samsuri |
title |
Prediction of stock prices at Kuala Lumpur stock exchange KLSE using artificial neural network |
title_short |
Prediction of stock prices at Kuala Lumpur stock exchange KLSE using artificial neural network |
title_full |
Prediction of stock prices at Kuala Lumpur stock exchange KLSE using artificial neural network |
title_fullStr |
Prediction of stock prices at Kuala Lumpur stock exchange KLSE using artificial neural network |
title_full_unstemmed |
Prediction of stock prices at Kuala Lumpur stock exchange KLSE using artificial neural network |
title_sort |
prediction of stock prices at kuala lumpur stock exchange klse using artificial neural network |
publishDate |
2014 |
url |
http://umpir.ump.edu.my/id/eprint/13381/ http://umpir.ump.edu.my/id/eprint/13381/ http://umpir.ump.edu.my/id/eprint/13381/1/FSKKP%20-%20MUHAMMAD%20HAFIZ%20SAMSURI.PDF |
first_indexed |
2023-09-18T22:15:57Z |
last_indexed |
2023-09-18T22:15:57Z |
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1777415338051239936 |