We consider a continuous time dynamic pricing model where a seller needs to sell a single item over a finite time horizon. Customers arrive in accordance with a Poisson process. Upon arrival, a customer either purchases the item if the posted price is lower than his/her reservation price, or leaves empty-handed. After purchasing the item, some customers, however, will return the item to the seller at an exponential rate for a full refund. We assume that a returned item is in mint condition and the seller can resell it to future customers. The objective of the seller is to dynamically adjust the price in order to maximize the expected total revenue when the sale horizon ends. We formulate the dynamic pricing problem as a dynamic programming model and derive the structural properties of the optimal policy and the optimal value function. For cases in which the customer's reservation price is exponentially distributed, we derive the optimal policy in a closed form. For general reservation price distribution, we consider an approximation of the original model by discretizing both time and the allowable price set. We then present an algorithm for numerically computing the optimal policy in this discrete time model. Numerical examples show that if the discrete price set is carefully chosen, the expected total revenue is nearly the same as that when the allowable price set is continuous. / Master of Science