This paper employs conditional probabilities generated from a homogenous two-state Markov chain to obtain maximum likelihood estimates of the efficacy of central bank intervention on the foreign exchange market in Uganda. This enables us to explicitly model the fact that intervention actions usually do not target the exchange rate itself but rather its orderly movement. The results suggest that seasonal pressures are largely responsible for moving the short-term exchange rate process between the different state spaces. Intervention reduces the probability of the exchange rate process staying in a regime characterised by sharp and disruptive tendencies. Copyright © 2010 John Wiley & Sons, Ltd.