An Intelligent Model for Stock Market Prediction
This paper presents an intelligent model for stock market signal prediction using Multi-Layer Perceptron (MLP) Artificial Neural Networks (ANN). Blind source separation technique, from signal processing, is integrated with the learning phase of the constructed baseline MLP ANN to overcome the proble...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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Springer
2012-08-01
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Series: | International Journal of Computational Intelligence Systems |
Subjects: | |
Online Access: | https://www.atlantis-press.com/article/25867998.pdf |
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author | IbrahimM. Hamed AshrafS. Hussein MohamedF. Tolba |
author_facet | IbrahimM. Hamed AshrafS. Hussein MohamedF. Tolba |
author_sort | IbrahimM. Hamed |
collection | DOAJ |
description | This paper presents an intelligent model for stock market signal prediction using Multi-Layer Perceptron (MLP) Artificial Neural Networks (ANN). Blind source separation technique, from signal processing, is integrated with the learning phase of the constructed baseline MLP ANN to overcome the problems of prediction accuracy and lack of generalization. Kullback Leibler Divergence (KLD) is used, as a learning algorithm, because it converges fast and provides generalization in the learning mechanism. Both accuracy and efficiency of the proposed model were confirmed through the Microsoft stock, from wall-street market, and various data sets, from different sectors of the Egyptian stock market. In addition, sensitivity analysis was conducted on the various parameters of the model to ensure the coverage of the generalization issue. Finally, statistical significance was examined using ANOVA test. |
first_indexed | 2024-04-12T16:33:56Z |
format | Article |
id | doaj.art-750be443404a4de7b4a9a3abc2987971 |
institution | Directory Open Access Journal |
issn | 1875-6883 |
language | English |
last_indexed | 2024-04-12T16:33:56Z |
publishDate | 2012-08-01 |
publisher | Springer |
record_format | Article |
series | International Journal of Computational Intelligence Systems |
spelling | doaj.art-750be443404a4de7b4a9a3abc29879712022-12-22T03:25:03ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832012-08-015410.1080/18756891.2012.718108An Intelligent Model for Stock Market PredictionIbrahimM. HamedAshrafS. HusseinMohamedF. TolbaThis paper presents an intelligent model for stock market signal prediction using Multi-Layer Perceptron (MLP) Artificial Neural Networks (ANN). Blind source separation technique, from signal processing, is integrated with the learning phase of the constructed baseline MLP ANN to overcome the problems of prediction accuracy and lack of generalization. Kullback Leibler Divergence (KLD) is used, as a learning algorithm, because it converges fast and provides generalization in the learning mechanism. Both accuracy and efficiency of the proposed model were confirmed through the Microsoft stock, from wall-street market, and various data sets, from different sectors of the Egyptian stock market. In addition, sensitivity analysis was conducted on the various parameters of the model to ensure the coverage of the generalization issue. Finally, statistical significance was examined using ANOVA test.https://www.atlantis-press.com/article/25867998.pdfstock market predictiontechnical indicatorartificial neural networksblind source separation |
spellingShingle | IbrahimM. Hamed AshrafS. Hussein MohamedF. Tolba An Intelligent Model for Stock Market Prediction International Journal of Computational Intelligence Systems stock market prediction technical indicator artificial neural networks blind source separation |
title | An Intelligent Model for Stock Market Prediction |
title_full | An Intelligent Model for Stock Market Prediction |
title_fullStr | An Intelligent Model for Stock Market Prediction |
title_full_unstemmed | An Intelligent Model for Stock Market Prediction |
title_short | An Intelligent Model for Stock Market Prediction |
title_sort | intelligent model for stock market prediction |
topic | stock market prediction technical indicator artificial neural networks blind source separation |
url | https://www.atlantis-press.com/article/25867998.pdf |
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