<![CDATA[Abstract Time series model accommodating the above heteroscedastisity is Generalized Autoregressive Conditional heteroscedastisity (GARCH) model and Exponential Weighted Moving Average   (EWMA)  model. The volatility estimated by these model can be used to measure the market risk of a portofolio of assets, called Value at Risk (VaR). VaR depends on the volatility, time horizon and confidence interval for the continuous return under analysis. For empirical assessment of these models, we use a sample on Jakarta Islamic Stock to sepecify  the GARCH and EWMA model. The best GARCH model yielded from this research is model GARCH (1,2) and the best EWMA model, be modeled with weight 0,992. The comparison process of GARCH model and EWMA model was done by measuring the value of Mean Absolute Percentage Error (MAPE) for estimation and forecasting. The result of research of shows that the MAPE to EWMA model is of 21,67 which is smaller than GARCH model which is 71,79 Therefore, it can be concluded that EWMA model has a better level of accuration than GARCH model in representing the actual data and forecasting. The result of variance forecasting for one periods forwards shows that the GARCH model has a larger Value at Risk ( Var) than the EWMA model has.Keywords : EWMA Model, GARCH Model, MAPE, VaR]]>
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