On Best-Response Bidding in GSP Auctions
How should players bid in keyword auctions such as those used by Google, Yahoo! and MSN? We model ad auctions as a dynamic game of incomplete information, so we can study the convergence and robustness properties of various strategies. In particular, we consider best-response bidding strategies for a repeated auction on a single keyword, where in each round, each player chooses some optimal bid for the next round, assuming that the other players merely repeat their previous bids. We focus on a strategy we call Balanced Bidding (bb). If all players use the bb strategy, we show that bids converge to a bid vector that obtains in a complete information static model proposed by Edelman, Ostrovsky and Schwarz (2007). We prove that convergence occurs with probability 1, and we compute the expected time until convergence.
|Date of creation:||Feb 2008|
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- Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007.
"Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords,"
American Economic Review,
American Economic Association, vol. 97(1), pages 242-259, March.
- Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2005. "Internet Advertising and the Generalized Second Price Auction: Selling Billions of Dollars Worth of Keywords," NBER Working Papers 11765, National Bureau of Economic Research, Inc.
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