FORECASTING THE VOLATILITY OF ETHIOPIAN BIRR/ EURO EXCHANGE RATE USING GARCH-TYPE MODELS

Abstract

This thesis provides a robust analysis of volatility forecasting of Euro-ETB exchange rate using weekly data spanning the period January 3, 2000 to December 2, 2015.The forecasting performance of various GARCH-type models is investigated based on forecasting performance criteria such as MSE and MAE based tests, and alternative measures of realized volatility. To our knowledge, this is the first study that focuses on Euro-ETB exchange rate using high frequency data, and a range of econometric models and forecast performance criteria.The empirical results indicate that the Euro-ETB exchange rate series exhibits persistent volatility clustering over the study period. We document evidence that ARCH (8), GARCH (1, 1), EGARCH (1, 1) and GJR-GARCH (2, 2) models with normal distribution, student’s-t distribution and GED are the best in-sample estimation models in terms of the volatility behavior of the series. Amongst these models, GJR-GARCH (2, 2) and GARCH(1,1) with students t- distribution are found to perform best in terms of one step-ahead forecasting based on realized volatility calculated from the underlying daily data and squared weekly first difference of the logarithm of the series,respectively. Furthermore, GJR-GARCH (2, 2) with student’s t-distribution is the best model both interms of fit the stylized facts(like asymmetric) and forecasting performance of the volatility of Ethiopian Birr/ Euro exchange rate among others.