Modeling Exchange Rate Volatility: Application of the GARCH and EGARCH Models

摘要: Policy makers need accurate forecasts about future values of exchange rates. This is due to the fact that rate volatility a useful measure uncertainty economic environment country. paper applies univariate nonlinear time series analysis daily (TZS/USD) data spanning from January 4, 2009 July 27, 2015 examine behavior in Tanzania. To capture symmetry effect data, both ARCH and GARCH models. Also, employs exponential (EGARCH) model asymmetry clustering leverage rate. The reveals exhibits empirical regularities such as volatility, nonstationarity, non-normality serial correlation justify application methodology. results also suggest generally influenced by previous information implies day’s can affect current In addition, estimate for asymmetric suggests positive shocks imply higher next period conditional variance than negative same sign. main policy implication these since (exchange-rate risk) may increase transaction costs reduce gains international trade, knowledge estimation forecasting important asset pricing risk management.