We propose a general stochastic framework for modelling repeated auctions in the Real Time Bidding (RTB) ecosystem using point processes. The flexibility of the framework allows a variety of auction scenarios including configuration of information provided to player, determination of auction winner and quantification of utility gained from each auctions. We propose theoretical results on how this formulation of process can be approximated to a Poisson point process, which enables the analyzer to take advantage of well-established properties. Under this framework, we specify the player's optimal strategy under various scenarios. We also emphasize that it is critical to consider the joint distribution of utility and market condition instead of estimating the marginal distributions independently.

翻译：我们提出了一种使用点过程对实时竞价生态系统中重复拍卖进行建模的通用随机框架。该框架的灵活性支持多种拍卖场景，包括向参与者提供信息的配置、拍卖胜出者的确定以及每次拍卖获得效用的量化。我们提出了理论结果，证明该过程如何近似为泊松点过程，从而使分析人员能够利用其成熟的性质。在此框架下，我们明确了不同场景下参与者的最优策略。同时强调，必须考虑效用与市场条件的联合分布，而非独立估计其边际分布。