Abstract

This paper models the exchange rate volatility in the Gambian foreign exchange rates data. Financial time series models that combined autoregressive moving average (ARMA) and generalized conditional heteroscedasticity (GARCH) was explored theoritically and applied to the daily Euro and US dollars (USD) exchange rates against the Gambian Dalasi (GMD) from 2003 through 2013. Based on Akaike information criteria, the ARMA(1,1)- GARCH(1,1) and ARMA(2,1)-GARCH(1,1) were judged the best ?tting models to the Euro/GMD and USD/GMD return series respectively. Our empirical results revealed that the distribution of the return series was heavy-tailed and volatility was highly persistent in the Gambian foreign exchange market.

This work is licensed under a Creative Commons Attribution 4.0 License.