Estimation of Risk in Rwanda Exchange Rate

Abstract

Generalized Autoregressive Conditional Heteroskedasticity (GARCH) approach was applied to Rwanda Exchange rate returns to estimating current volatility. We fitted autoregressive (AR) model with GARCH errors to the daily exchange rate returns using Quasi-Maximum Likelihood Estimation (Q-MLE) method to get the current volatility and asymptotic properties of the estimators were given. The appropriate GARCH model for each currency was selected using Akaike Information Criterion (AIC). Jarque Bera test for normality was applied and showed that both returns and residuals have fat tails behaviour. Lagrange Multiplier test showed ARCH effects presence in residuals. Results were used to estimate risk in the Rwanda exchange rate process