Abstract:
In this research, the implementation of GARCH Model to forecast conditional variances (volatility) and forecast data NAV from sharia mutual funds is discussed. In this research, the analysis data of Mandiri Investa Dana Syariah (MidSya), MNC Dana Syariah (MNC), and I-Haji Syariah (Insight) are studied by using analysis time series AR(p)-GARCH(p,q) modeling. From the analysis, it was found that the data Mandiri Investa Dana Syariah (MidSya), MNC Dana Syariah (MNC), and I-Haji Syariah (Insight) are nonstationary. To make the data stationary, the differencing process with lag=2 (d=2) is used and the time series data then attain stationary. The results of forecasting the conditional variance (volatility) from model AR(1)-GARCH(1,1) for the data Mandiri Investa Dana Syariah (MidSya), MNC Dana Syariah (MNC), and IHaji Syariah (Insight) depicted the behavior of the volatility. The results from the GARCH (1,1) will be implemented into Sharpe Ratio method by replacing the Standard Deviation (The New Model). Then valuating each mutual funds using The New Model and Sharpe Ratio to do a comparison between these methods. The results is that the new model which using GARCH provide better valuation with less risk than the original Sharpe Ratio method.
