In today's online advertising markets, it is common for an advertiser to set a long-period budget. Correspondingly, advertising platforms adopt budget control methods to ensure that any advertiser's payment is within her budget. Most budget control methods rely on value distributions of advertisers. However, due to the complex environment advertisers stand in and privacy issues, the platform hardly learns their true priors. Therefore, it is essential to understand how budget control auction mechanisms perform under unassured priors. This paper gives a two-fold answer. First, we propose a bid-discount method barely studied in the literature. We show that such a method exhibits desirable properties in revenue-maximizing and computation when fitting into first-price auction. Second, we compare this mechanism with another four in the prior manipulation model, where an advertiser can arbitrarily report a value distribution to the platform. These four mechanisms include the optimal mechanism satisfying budget-constrained IC, first-price/second-price mechanisms with the widely-studied pacing method, and an application of bid-discount in second-price mechanism. We consider three settings under the model, depending on whether the reported priors are fixed and advertisers are symmetric or not. We show that under all three cases, the bid-discount first-price auction we introduce dominates the other four mechanisms concerning the platform's revenue. For the advertisers' side, we show a surprising strategic-equivalence result between this mechanism and the optimal auction. Extensive revenue dominance and strategic relationships among these mechanisms are also revealed. Based on these findings, we provide a thorough understanding of prior dependency in repeated auctions with budgets. The bid-discount first-price auction itself may also be of further independent research interest.
翻译:在今天的在线广告市场中,广告商通常会设定长期的拍卖预算。 因此,广告商通常会采用预算控制方法,以确保广告商的付款在她的预算范围内。 大多数预算控制方法都依赖于广告商的价值分配。 但是,由于复杂的环境广告商在网上广告市场中所处的地位和隐私问题,平台几乎无法了解其真实的前科。 因此,理解预算控制拍卖机制如何在未经确定的前期下运行至关重要。 本文给出了双重答案。 首先,我们提议了一种在文献中几乎未研究过的减价方法。 我们表明,这种方法在首次进行价格拍卖时,在收入最大化和计算方面显示出适当的属性。 其次,我们把这个机制与先前的操纵模型中的另一个四个机制进行比较,在这个机制中,广告商家可以任意向平台报告其价值分配情况。这四个机制包括最佳机制满足预算限制的IC,第一个价格/第二价格机制,在广泛研究的平台中,在二次价格机制中,我们提出出价折扣的方法很少研究。 我们还认为,在二次价格机制中应用了标价差的方法。 我们认为,在第一次的标价价定价中,我们没有在之前的汇率中显示三个的标值的汇率, 我们的汇率是在之前的排序中显示的,我们之前的,我们所报告的排序的标的,我们是否的标的排序的,我们是在这些是的。