Many industries face the problem of selling a fixed stock of items over a f
inite horizon. These industries include airlines selling seats before plane
s depart, hotels renting rooms before midnight, theaters selling seats befo
re curtain time, and retailers selling seasonal items with long procurement
lead times. Given a sunk investment in seats, rooms, or winter coats, the
objective for these industries is to maximize revenues in excess of salvage
value. When demand is price sensitive and stochastic, pricing is an effect
ive tool to maximize expected revenues. In this paper we address the proble
m of deciding the optimal timing of price changes within a given menu of al
lowable, possibly time dependent, price paths each of which is associated w
ith a general Poisson process with Markovian, time dependent, predictable i
ntensities. We show that a set of variational inequalities characterize the
value functions and the optimal (possibly random) time changes. In additio
n, we develop an efficient algorithm to compute the optimal value functions
and the optimal pricing policy.