Fuzzy-neural model with hybrid market indicators for stock forecasting

A.A. Adebiyi, C.K. Ayo and S.O. Otokiti

International Journal of Electronic Finance, 2011, vol. 5, issue 3, 286-297

Abstract: 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.

Keywords: artificial neural networks; ANNs; fuzzy logic; market indicators; stock prediction; electronic finance; stock index; e-finance; modelling; stock forecasting; stock prices. (search for similar items in EconPapers)
Date: 2011
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