• ISSN: 2010-023X
    • Frequency: Bimonthly
    • DOI: 10.18178/IJTEF
    • Editor-in-Chief: Prof.Tung-Zong (Donald) Chang
    • Executive Editor: Ms. Cherry L. Chen
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, DOAJ , EBSCO, and Ulrich's Periodicals Directory
    • E-mail: ijtef@ejournal.net
IJTEF 2011 Vol.2(2): 109-114 ISSN: 2010-023X
DOI: 10.7763/IJTEF.2011.V2.87

A New Approach to Forecasting Stock Price with EKF Data Fusion

H. Haleh, B. Akbari Moghaddam, and S. Ebrahimijam
Abstract—Obtaining to the method with the least prediction error is one of the challenging issues of financial and investment markets analyzers. Investors often use two different views of technical and fundamental analysis of prices for buying and selling their desired shares. But each of these two methods alone may have not enough performance due to differences between the actual value of the share and its market price.
This paper presents a predictive model named extended Kalman filter which simultaneously fuses information and parameters of technical and fundamental analysis. Then as a real test, the model implemented for the shares of one of industrial company in Iran. Finally, the obtained results will be compared with other methods results such as regression and neural networks which shows its desirability in short-term predictions

Index Terms—Stock exchange, data fusion, Extended Kalman filter, technical and fundamental analysis.

H. Haleh is with Faculty of Industrial and Mechanical Engineering; Islamic Azad University-Qazvin Branch, Qazvin, Iran; e-mail: hhaleh@cc.iut.ac.ir.
B. Akbari Moghaddam, is with Faculty of Management and Accounting Science, Islamic Azad University-Qazvin Branch ,Qazvin, Iran; e-mail: finan@qiau.ac.ir.
S. Ebrahimijam is with Faculty of Industrial and Mechanical Engineering; Islamic Azad University-Qazvin Branch , Qazvin, Iran; e-mail: ebrahimijam@mrl.ir

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Cite:H. Haleh, B. Akbari Moghaddam, and S. Ebrahimijam, "A New Approach to Forecasting Stock Price with EKF Data Fusion," International Journal of Trade, Economics and Finance vol.2, no.2, pp. 109-114, 2011.

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