Exchange rate forecasts are important because these forecasts help in hedging decisions, capital budgeting decisions and earnings assessments. While numerous methods are available for forecasting exchange rates, the current study employs time series models to forecast daily data of US Dollar exchange rate against Malaysian Ringgit (USD/MYR). Using hybrid ARIMA-GARCH and hybrid ARIMA-EGARCH models, the modelling and forecasting performances are compared using Akaike Information Criterion (AIC) and Root Mean Square Error (RMSE) respectively. Such findings are important since exchange rate forecasts can help to evaluate the foreign denominated cash flows involved in international transactions.