Setyo Tri Wahyudi
Prediction of stock price volatility is an important topic either in economics or in finance as it benefits both the investors and economists. In this paper, we conducted the prediction of Indonesia stock price by using Autoregressive Integrated Moving Average (ARIMA). The ARIMA model was chosen as the model to predict the volatility of Indonesia stock price due to its simplicity and wide acceptability. To this end, the daily Indonesia Composite Stock Price Index (CSPI) in the period January, 4th 2010 until December, 5th 2014 was employed. This study reports empirical evidences that ARIMA models are applicable for forecasting Indonesia stock price. Furthermore, the results obtained in the study revealed that ARIMA model has a strong potential for short-term prediction and can compete favourably with the existing techniques for stock price prediction. The best ARIMA model was selected using Akaike Information Criterion (AIC) criteria and it was found that ARIMA (0,0,1) is the best model for forecasting the Indonesia Composite Stock Price Index.
Department of Economics, Faculty of Economics and Business, Brawijaya University, Indonesia
