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Fuzzy-neural model with hybrid market indicators for stock forecasting

Adebiyi, A. A. and Ayo, C. K. and Otokiti, S. O. (2011) Fuzzy-neural model with hybrid market indicators for stock forecasting. International Journal of Electronic Finance, 5 (3). pp. 286-297.

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A number of research had been carried out to forecast stock price based on technical indicators, which rely purely on historical stock price data. Nevertheless, their performance is not always satisfactory. In this paper, the effect of using hybrid market indicators of technical, fundamental indicators and experts opinion for stock price prediction is examined. Input variables extracted from these market hybrid indicators are fed into a fuzzy-neural network for improved accuracy of stock price prediction. The empirical results obtained with published stock data shows that the proposed model can be effective to improve accuracy of stock price prediction.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mr Adewole Adewumi
Date Deposited: 20 Mar 2015 16:39
Last Modified: 20 Mar 2015 16:39

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