Dynamic Reserve Prices for Repeated Auctions: Learning from Bids

Abstract

A large fraction of online advertisement is sold via repeated second price auctions. In these auctions, the reserve price is the main tool for the auctioneer to boost revenues. In this work, we investigate the following question: Can changing the reserve prices based on the previous bids improve the revenue of the auction, taking into account the long-term incentives and strategic behavior of the bidders?

In order to set the reserve price effectively, the auctioneer requires information about distribution of the valuations of the bidders. A natural idea, which is widely used in practice, is to construct these distributions using the history of the bids. This approach, though intuitive, raises a major concern with regards to long-term (dynamic) incentives of the advertisers. Because the bid of an advertiser may determine the price he or she pays in future auctions, this approach may result in the advertisers shading their bids and ultimately in a loss of revenue for the auctioneer.

A complete version is available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2444495 . We would like to thank Brendan Lucier, Mohammad Mahdian, Mukund Sundararajan and the anonymous referees for their insightful comments and suggestions. This work was supported in part by Microsoft Research New England. The work of the second author was supported in part by a Google Faculty Research Award.