Stock price index is the initial significant factor influencing on investors' financial
decision making. That's why predicting the exact movements of stock price index
is considerably regarded. This study aims at evaluating the effectiveness of using
technical indicators, such as A/D Oscillator, Moving Average, RSI, CCI, MACD,
etc. in predicting movements of Indonesian Stock Exchange Price Index (IDX).
An artificial neural network is employed for stock price index forecasting. The
existing data are achieved from Yahoo.Finance. To capture the relationship
between the technical indicators and the levels of the index in the market for the
period under investigation, a back propagation neural network is used. The
statistical and financial performance of this technique is evaluated and empirical
results revealed that artificial neural networks are fairly good tools for financial
market predicting.