Universiti Teknologi Malaysia Institutional Repository

Multilayer stock forecasting model using fuzzy time series

Sadaei, Hossein Javedani and Lee, Muhammad Hisyam (2014) Multilayer stock forecasting model using fuzzy time series. Scientific World Journal . ISSN 1537-744X

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Official URL: http://dx.doi.org/10.1155/2014/610594

Abstract

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

Item Type:Article
Uncontrolled Keywords:accuracy, article, data base, empiricism, forecasting, fuzzy system, information model
Subjects:Q Science
Divisions:Science
ID Code:54189
Deposited By: Siti Nor Hashidah Zakaria
Deposited On:05 Apr 2016 15:00
Last Modified:03 Aug 2018 16:49

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