Forecasting Volatility of USD/MUR Exchange Rate using a GARCH (1,1) model with GED and Student’s-t errors

This paper aims at evaluating volatility forecasts for the US Dollar/Mauritian Rupee exchange rate obtained via a GARCH (1,1) model under two distributional assumptions: the Generalized Error Distribution (GED) and the Student’s-t distribution. We make use of daily data to evaluate the parameters of each model and produce volatility estimates. The forecasting ability is subsequently assessed using the symmetric loss functions which are the Mean Absolute Error(MAE) and Root Mean Square Error (RMSE). The latter show that both distributions may forecast quite well with a slight advantage to the GARCH(1,1)- GED for out-of-sample forecasts.