Several research efforts had been done to forecast stock price based on technical indicators
which rely purely on historical stock price data. Nevertheless, their performance is not always
satisfactory. However, there are other influential factors which can affect the direction of stock
market which form the basis of market experts’ opinion such as interest rate, inflation rate,
foreign exchange rate, business sector, management caliber, government policy and political
effects among others. In this paper, the effect of using market experts’ opinion in addition to the
use of technical and fundamental indicators for stock price prediction is examined. Input
variables extracted from these 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 improving accuracy of stock price predictio
