Stock price index is the initial significant factor influencing on investors' financialuddecision making. That's why predicting the exact movements of stock price indexudis considerably regarded. This study aims at evaluating the effectiveness of usingudtechnical indicators, such as A/D Oscillator, Moving Average, RSI, CCI, MACD,udetc. in predicting movements of Indonesian Stock Exchange Price Index (IDX).udAn artificial neural network is employed for stock price index forecasting. Theudexisting data are achieved from Yahoo.Finance. To capture the relationshipudbetween the technical indicators and the levels of the index in the market for theudperiod under investigation, a back propagation neural network is used. Theudstatistical and financial performance of this technique is evaluated and empiricaludresults revealed that artificial neural networks are fairly good tools for financialudmarket predicting.
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