Bidding

About: Bidding is a research topic. Over the lifetime, 15371 publications have been published within this topic receiving 294233 citations. The topic is also known as: competitive bidding.

Cyclical Bid Adjustments in Search-Engine Advertising

Abstract: Keyword advertising, or sponsored search, is one of the most successful advertising models on the Internet. One distinctive feature of keyword auctions is that they enable advertisers to adjust their bids and rankings dynamically, and the payoffs are realized in real time. We capture this unique feature with a dynamic model and identify an equilibrium bidding strategy. We find that under certain conditions, advertisers may engage in cyclical bid adjustments, and equilibrium bidding prices may follow a cyclical pattern: price-escalating phases interrupted by price-collapsing phases, similar to an “Edgeworth cycle” in the context of dynamic price competitions. Such cyclical bidding patterns can take place in both first-and second-price auctions. We obtain two data sets containing detailed bidding records of all advertisers for a sample of keywords in two leading search engines. Our empirical framework, based on a Markov switching regression model, suggests the existence of such cyclical bidding strategies. The cyclical bid-updating behavior we find cannot be easily explained with static models. This paper emphasizes the importance of adopting a dynamic perspective in studying equilibrium outcomes of keyword auctions. This paper was accepted by Pradeep Chintagunta and Preyas Desai, special issue editors. This paper was accepted by Pradeep Chintagunta and Preyas Desai, special issue editors.

Absentee bidders and the declining price anomaly in wine auctions

Abstract: The anomaly is concerned with the observation that in multiple item auctions of identical objects, prices tend to decline over time. I show that in the case of wine auctions, which have been analyzed frequently, the anomaly is likely to be caused by the fact that most bids are entered by absentees, who use nonoptimal bidding strategies. Therefore, wine auctions can hardly be used to illustrate the standard multiple‐object auction model.

Vickrey Auctions with Reserve Pricing

Abstract: We generalize the Vickrey auction to allow for reserve pricing in a multiple item auction with interdependent values. By withholding quantity in some circumstances, the seller can improve revenues or mitigate collusion. In the Vickrey auction with reserve pricing, the seller determines the quantity to be made available as a function of the bidders' private information, and then efficiently allocates this quantity among the bidders. Truthful bidding is a dominant strategy with private values and an ex post equilibrium with interdependent values. If the auction is followed by resale, then truthful bidding remains an equilibrium in the auction-plus-resale game. In settings where resale exhausts all the gains from trade among the bidders, the Vickrey auction with reserve pricing maximizes seller revenues.

Adaptive bidding for display advertising

Abstract: Motivated by the emergence of auction-based marketplaces for display ads such as the Right Media Exchange, we study the design of a bidding agent that implements a display advertising campaign by bidding in such a marketplace. The bidding agent must acquire a given number of impressions with a given target spend, when the highest external bid in the marketplace is drawn from an unknown distribution P. The quantity and spend constraints arise from the fact that display ads are usually sold on a CPM basis. We consider both the full information setting, where the winning price in each auction is announced publicly, and the partially observable setting where only the winner obtains information about the distribution; these differ in the penalty incurred by the agent while attempting to learn the distribution. We provide algorithms for both settings, and prove performance guarantees using bounds on uniform closeness from statistics, and techniques from online learning. We experimentally evaluate these algorithms: both algorithms perform very well with respect to both target quantity and spend; further, our algorithm for the partially observable case performs nearly as well as that for the fully observable setting despite the higher penalty incurred during learning.

System and method for supporting online auctions

Abstract: A system that facilitates bidding by online bidders in “live” auctions and provides enhanced functionality for administering auctions. Online bidders who are registered can select one or more “channels” to participate in auctions that are being held live for different collections of items. Data transferred over the Internet or other network is limited so that the asking bids, and current highest bid amounts can readily be transmitted to online bidders, who can then quickly respond with bids online, without slowing the bidding process for those bidders who are onsite. The system also provides management functions that facilitate the running of elections, including the registration process, compilation of inventories available for auction, and invoicing of successful bidders, both online and onsite.