PERBANDINGAN AKURASI PERAMALAN METODEARIMA DAN GARCH UNTUK MEMPREDIKSI IHSGPERIODE 1991 - 2011 - , Budi Nugroho ([Yogyakarta] : Universitas Gadjah Mada, 2012)
Investing in the stock market requires a lot of information that affects stock prices. Stock values having higher volatility reflect high level of risk as well. Technical analysis is a tool used to predict stock price movements and an influencing indicator based on historical data. If the historical data and stocks predictive value are already known then it can be taken into consideration while investing. This study focuses on forecasting the daily Composite Stock Price Index starting from January 3, 1991 until June 30, 2011 by ARIMA and GARCH methods which will further be tested their accuracy of predictions. The results of this study indicate that daily stock index data over the period 1991 to 2011 are classified as not stationary. Having made difference 1 and log transformation then the data became stationary. The correlogram test results obtained a significant partial autocorrelation of nine lags, namely lag1, lag 10, lag11, lag 13, lag 16, lag 17, lag 25, lag 33, and lag 36. The best suited model of ARIMA(1,1,0) was obtained. On the residual value of ARIMA(1,1,0) thereâs an ARCH effect forecasting is then performed by GARCH method and obtained the best prediction model GARCH(2,2). ARIMA(1,1,0) has better accuracy as compared to GARCH(2,2) because the forecast error value of one period ahead and the MAE and MAPE values were smaller, which means that the forecast of ARIMA (1,1,0) almost reached the factual value.