This paper considers the application of the generalized autoregressive conditional heteroscedasticity process in the estimation of volatility in the Kenyan exchange rates. A quasi-maximum likelihood estimation procedure was used and asymptotic properties of the estimators were given. Exploratory data analysis performed indicated that the returns are heavy tailed. It was found that the estimated model fits the exchange rates return data well.