A very significant input to monetary policymaking is estimating the current level of exchange rate. This paper examined the application of stochastic volatility of returns on the Ghana Cedis and US dollar ($) exchange rate. Stationarity of the dataset was achieved after differencing. Markov Chain Monte Carlo (MCMC) was used in the parameter estimation. A stochastic volatility (SV) was obtained with the level of log-variance = μ 10:8320, the persistence of log-variance- = 0:9285, and the volatility of log-variance = 0:660. Posterior density estimates, standardized residual plots as well as estimated volatilies were actualized. Keywords: Stochastic Volatility, Markov Chain Monte Carlo (MCMC), GARCH.