Revenue management has been successfully applied to service-oriented industries for a long time. In the more recent past, besides these classical application areas, it has been introduced to other production and logistics processes as well. For the automobile industry so far, only a few revenue managementmodels have been developed but practically none for its used car sector. Being a sector with suitable prerequisites and a low profit margin, this is a promising application area for price-based revenue management. As used cars are “individual” and “durable” goods – unlike seat or room bookings –, a different approach is necessary with “dynamic pricing” as the main control strategy. A somewhat similar problem can only be found in the real estate sector. Thus, a conceptual framework of an appropriate revenue management model based on dynamic pricing must be developed. Using current and historical m- ket data, the price-responsefunctionhas to be estimated which then can serve as the basis for determining the optimal dynamic pricing strategy. For two central components of this framework, optimization and estimation, - novative approaches are proposed. Based on results from Control Theory, different possible models are suggested and extensively evaluated. Finally, a shastic discrete-time model is identified as themost appropriate.Withthis, it is possible todevelopiterativealgorithmsto det- mine the optimal pricing strategy even for problems without closed-form solution.