Topic
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.
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TL;DR: The authors examines a model in which advertisers bid for "sponsored-link" positions on a search engine and the value advertisers derive from each position is endogenized as coming from sales to a population of consumers who make rational inferences about rm qualities and search optimally.
Abstract: This paper examines a model in which advertisers bid for \sponsored-link" positions on a search engine. The value advertisers derive from each position is endogenized as coming from sales to a population of consumers who make rational inferences about rm qualities and search optimally. Consumer search strategies, equilibrium bidding, and the welfare benets of position auctions are analyzed. Implications for reserve prices and a number of other auction design questions are discussed.
218 citations
TL;DR: In this paper, the authors show that jump bids serve as correlating devices which select asymmetric bidding functions to be played subsequently, and that each possibility of jump bidding provides a Pareto improvement for the bidders from the symmetric equilibrium of a sealed bid, second price auction.
Abstract: This paper solves for equilibria of sequential bid (or English) auctions with affiliated values when jump bidding strategies may be employed to intimidate one’s opponents. In these equilibria, jump bids serve as correlating devices which select asymmetric bidding functions to be played subsequently. Each possibility of jump bidding provides a Pareto improvement for the bidders from the symmetric equilibrium of a sealed bid, secondprice auction. The expanded set of equilibria can approximate either first or second-price outcomes and produce exactly the set of expected prices between those two bounds. These results contrast with standard conclusions that equate English and second-price auctions.
218 citations
TL;DR: In this article, the authors focus on two dynamic effects, which they call quasi-endowment and opponent effect, and find that these effects may result in over-bidding.
216 citations
TL;DR: In this paper, the authors investigated the properties of the winning bid in a sealed bid tender auction where each player has private information and found that it is possible for the winning bidder to converge in probability to the true value of the object at auction, even though no bidder knows the real value.
Abstract: IN THIS PAPER we investigate the properties of the winning bid in a sealed bid tender auction where each player has private information. We find that it is possible for the winning bid to converge in probability to the true value of the object at auction, even though no bidder knows the true value. Necessary and sufficient conditions for this phenomenon are derived, extending and generalizing certain of Wilson's results [3]. We study an auction in which a seller offers to sell at the highest bid an item of unknown value V. The kth bidder receives a private signal Sk (for k = 1, 2,.. .) and submits a bid without knowledge of the other signals. A finitely additive probability measure P reflects the bidders' unanimous beliefs about V and the signals. Conditional on V, the signals are independent and identically distributed. The signals take their values in some space &'. With n bidders, a bidding strategy for k is a function Pnk: 9' -> R. k's strategy specifies that upon receiving the signal Sk, he shall bid Pnk(Sk).2 Thus the winning
216 citations
TL;DR: In this paper, the problem is modeled as a two-level optimization problem where, at the first level, a market participant tries to maximize his expected profit under the constraint that an independent system operator dispatches power solving an optimal power flow problem that minimizes total system cost.
Abstract: This paper presents a methodology for the development of bidding strategies for electricity producers in a competitive electricity marketplace. Initially, the problem is modeled as a two level optimization problem where, at the first level, a market participant tries to maximize his expected profit under the constraint that, at the second level, an independent system operator dispatches power solving an optimal power flow problem that minimizes total system cost. It is assumed that each supplier bids a linear supply function and chooses his bidding strategy based on probabilistic estimates of demand and rival behavior. Monte Carlo simulation is used to calculate the expected profit and Genetic Algorithms are employed to find the optimal strategy. Subsequently, the formulation is expanded to account for different market participants' risk profiles. It is shown that risk aversion may influence the optimal bidding strategy of an individual.
215 citations