Incentive-Compatible Learning of Reserve Prices for Repeated Auctions

Y. Kanoria and H. Nazerzadeh, "Incentive-Compatible Learning of Reserve Prices for Repeated Auctions," to appear in Operations Research.

39 Pages Posted: 9 Jun 2014 Last revised: 26 May 2020

See all articles by Yash Kanoria

Yash Kanoria

Columbia Business School - Decision Risk and Operations

Hamid Nazerzadeh

University of Southern California - Marshall School of Business

Date Written: February 24, 2020

Abstract

A large fraction of online advertisements are 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: How can the auctioneer optimize reserve prices by learning from the previous bids, while accounting for the long-term incentives and strategic behavior of the bidders? To this end, we consider a seller who repeatedly sells ex ante identical items via a second-price auction. Buyers' valuations for each item are drawn i.i.d. from a distribution F that is unknown to the seller. We find that if the seller attempts to dynamically update a common reserve price based on the bidding history, this creates an incentive for buyers to shade their bids, which can hurt revenue. When there is more than one buyer, incentive compatibility can be restored by using *personalized* reserve prices, where the personal reserve price for each buyer is set using the historical bids of *other* buyers. Such a mechanism asymptotically achieves the expected revenue obtained under the static Myerson optimal auction for F. Further, if valuation distributions differ across bidders, the loss relative to the Myerson benchmark is only quadratic in the size of such differences. We extend our results to a contextual setting where the valuations of the buyers depend on observed features of the items. When up-front fees are permitted, we show how the seller can determine such payments based on the bids of others to obtain an approximately incentive-compatible mechanism that extracts nearly all the surplus.

Our earlier conference paper in WINE 2014 "Dynamic Reserve Prices for Repeated Auctions: Learning from Bids" featured a different model. The full version of that paper is posted at https://arxiv.org/abs/2002.07331

JEL Classification: D44

Suggested Citation

Kanoria, Yash and Nazerzadeh, Hamid, Incentive-Compatible Learning of Reserve Prices for Repeated Auctions (February 24, 2020). Y. Kanoria and H. Nazerzadeh, "Incentive-Compatible Learning of Reserve Prices for Repeated Auctions," to appear in Operations Research., Available at SSRN: https://ssrn.com/abstract=2444495 or http://dx.doi.org/10.2139/ssrn.2444495

Yash Kanoria

Columbia Business School - Decision Risk and Operations ( email )

New York, NY
United States

Hamid Nazerzadeh (Contact Author)

University of Southern California - Marshall School of Business ( email )

Bridge Memorial Hall
Los Angeles, CA 90089
United States

HOME PAGE: http://www-bcf.usc.edu/~nazerzad/

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