Multilayer stock forecasting model using fuzzy time series
After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings. In addition, the lack of constructive systematic framework, which can be helpful to indicate direction of growth in entire FTS forecasting sy...
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2014
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Online Access: | http://eprints.utm.my/id/eprint/54189/1/HosseinJavedaniSadaei2014_Multilayerstockforecastingmodel.pdf http://eprints.utm.my/id/eprint/54189/ http://dx.doi.org/10.1155/2014/610594 |
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my.utm.541892018-08-03T08:49:43Z http://eprints.utm.my/id/eprint/54189/ Multilayer stock forecasting model using fuzzy time series Sadaei, Hossein Javedani Lee, Muhammad Hisyam Q Science After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings. In addition, the lack of constructive systematic framework, which can be helpful to indicate direction of growth in entire FTS forecasting systems, is outstanding. In this study, we propose a multilayer model for stock market forecasting including five logical significant layers. Every single layer has its detailed concern to assist forecast development by reconciling certain problems exclusively. To verify the model, a set of huge data containing Taiwan Stock Index (TAIEX), National Association of Securities Dealers Automated Quotations (NASDAQ), Dow Jones Industrial Average (DJI), and S&P 500 have been chosen as experimental datasets. The results indicate that the proposed methodology has the potential to be accepted as a framework for model development in stock market forecasts using FTS Hindawi Publishing Corporation 2014 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/54189/1/HosseinJavedaniSadaei2014_Multilayerstockforecastingmodel.pdf Sadaei, Hossein Javedani and Lee, Muhammad Hisyam (2014) Multilayer stock forecasting model using fuzzy time series. Scientific World Journal . ISSN 1537-744X http://dx.doi.org/10.1155/2014/610594 DOI: 10.1155/2014/610594 |
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Q Science Sadaei, Hossein Javedani Lee, Muhammad Hisyam Multilayer stock forecasting model using fuzzy time series |
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After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings. In addition, the lack of constructive systematic framework, which can be helpful to indicate direction of growth in entire FTS forecasting systems, is outstanding. In this study, we propose a multilayer model for stock market forecasting including five logical significant layers. Every single layer has its detailed concern to assist forecast development by reconciling certain problems exclusively. To verify the model, a set of huge data containing Taiwan Stock Index (TAIEX), National Association of Securities Dealers Automated Quotations (NASDAQ), Dow Jones Industrial Average (DJI), and S&P 500 have been chosen as experimental datasets. The results indicate that the proposed methodology has the potential to be accepted as a framework for model development in stock market forecasts using FTS |
format |
Article |
author |
Sadaei, Hossein Javedani Lee, Muhammad Hisyam |
author_facet |
Sadaei, Hossein Javedani Lee, Muhammad Hisyam |
author_sort |
Sadaei, Hossein Javedani |
title |
Multilayer stock forecasting model using fuzzy time series |
title_short |
Multilayer stock forecasting model using fuzzy time series |
title_full |
Multilayer stock forecasting model using fuzzy time series |
title_fullStr |
Multilayer stock forecasting model using fuzzy time series |
title_full_unstemmed |
Multilayer stock forecasting model using fuzzy time series |
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multilayer stock forecasting model using fuzzy time series |
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Hindawi Publishing Corporation |
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2014 |
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http://eprints.utm.my/id/eprint/54189/1/HosseinJavedaniSadaei2014_Multilayerstockforecastingmodel.pdf http://eprints.utm.my/id/eprint/54189/ http://dx.doi.org/10.1155/2014/610594 |
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