The performance of immune-based neural network with financial time series prediction
This paper presents the use of immune-based neural networks that include multilayer perceptron (MLP) and functional neural network for the prediction of financial time series signals. Extensive simulations for the prediction of one- and five-steps-ahead of stationary and non-stationary time series w...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2015-12-01
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| Series: | Cogent Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/23311916.2014.985005 |
| _version_ | 1827834781535043584 |
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| author | Dhiya Al-Jumeily Abir J. Hussain |
| author_facet | Dhiya Al-Jumeily Abir J. Hussain |
| author_sort | Dhiya Al-Jumeily |
| collection | DOAJ |
| description | This paper presents the use of immune-based neural networks that include multilayer perceptron (MLP) and functional neural network for the prediction of financial time series signals. Extensive simulations for the prediction of one- and five-steps-ahead of stationary and non-stationary time series were performed which indicate that immune-based neural networks in most cases demonstrated advantages in capturing chaotic movement in the financial signals with an improvement in the profit return and rapid convergence over MLPs. |
| first_indexed | 2024-03-12T05:56:49Z |
| format | Article |
| id | doaj.art-bea5b7db4fe3493bbc5a0cccdf849824 |
| institution | Directory Open Access Journal |
| issn | 2331-1916 |
| language | English |
| last_indexed | 2024-03-12T05:56:49Z |
| publishDate | 2015-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj.art-bea5b7db4fe3493bbc5a0cccdf8498242023-09-03T04:32:47ZengTaylor & Francis GroupCogent Engineering2331-19162015-12-012110.1080/23311916.2014.985005985005The performance of immune-based neural network with financial time series predictionDhiya Al-Jumeily0Abir J. Hussain1Liverpool John Moores UniversityLiverpool John Moores UniversityThis paper presents the use of immune-based neural networks that include multilayer perceptron (MLP) and functional neural network for the prediction of financial time series signals. Extensive simulations for the prediction of one- and five-steps-ahead of stationary and non-stationary time series were performed which indicate that immune-based neural networks in most cases demonstrated advantages in capturing chaotic movement in the financial signals with an improvement in the profit return and rapid convergence over MLPs.http://dx.doi.org/10.1080/23311916.2014.985005financial signalsimmune-based neural networktime series prediction |
| spellingShingle | Dhiya Al-Jumeily Abir J. Hussain The performance of immune-based neural network with financial time series prediction Cogent Engineering financial signals immune-based neural network time series prediction |
| title | The performance of immune-based neural network with financial time series prediction |
| title_full | The performance of immune-based neural network with financial time series prediction |
| title_fullStr | The performance of immune-based neural network with financial time series prediction |
| title_full_unstemmed | The performance of immune-based neural network with financial time series prediction |
| title_short | The performance of immune-based neural network with financial time series prediction |
| title_sort | performance of immune based neural network with financial time series prediction |
| topic | financial signals immune-based neural network time series prediction |
| url | http://dx.doi.org/10.1080/23311916.2014.985005 |
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