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: In this article, the authors study a contest with multiple (not necessarily equal) prizes and show that for any number of contestants having linear, convex or concave cost functions, and for any distribution of abilities, it is optimal for the designer to allocate the entire prize sum to a single ''first'' prize.
Abstract: We study a contest with multiple (not necessarily equal) prizes. Contestants have private information about an ability parameter that affects their costs of bidding. The contestant with the highest bid wins the first prize, the contestant with the second-highest bid wins the second prize, and so on until all the prizes are allocated. All contestants incur their respective costs of bidding. The contest's designer maximizes the expected sum of bids. Our main results are: 1) We display bidding equlibria for any number of contestants having linear, convex or concave cost functions, and for any distribution of abilities. 2) If the cost functions are linear or concave, then, no matter what the distribution of abilities is, it is optimal for the designer to allocate the entire prize sum to a single ''first'' prize. 3) We give a necessary and sufficient conditions ensuring that several prizes are optimal if contestants have a convex cost function.
705 citations
Posted Content•
TL;DR: In this article, the authors show that large bidders have an incentive to reduce demand in order to pay less for their winnings, which creates an inefficiency in multi-unit auctions.
Abstract: Auctions typically involve the sale of many related goods. The FCC spectrum auctions and the Treasury debt auctions are examples. With conventional auction designs, large bidders have an incentive to reduce demand in order to pay less for their winnings. This incentive creates an inefficiency in multi-unit auctions. Large bidders reduce demand for additional units and so sometimes lose to smaller bidders with lower values. We demonstrate this inefficiency in several auction settings: flat demand and downward-sloping demand, independent private values and correlated values, and uniform pricing and pay-your-bid pricing. We also establish that the ranking of the uniform-price and pay-your-bid auctions is ambiguous. We show how a Vickrey auction avoids this inefficiency and how the Vickrey auction can be implemented with a simultaneous, ascending-bid design (Ausubel 1997). Bidding behavior in the FCC spectrum auctions illustrates the incentives for demand reduction and the associated inefficiency.
704 citations
TL;DR: In this article, an approach to predict next-day electricity prices based on the Generalized Autoregressive Conditional Heteroskedastic (GARCH) methodology that is already being used to analyze time series data in general.
Abstract: Price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets. Both for spot markets and long-term contracts, price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize profits. This paper provides an approach to predict next-day electricity prices based on the Generalized Autoregressive Conditional Heteroskedastic (GARCH) methodology that is already being used to analyze time series data in general. A detailed explanation of GARCH models is presented and empirical results from the mainland Spain and California deregulated electricity-markets are discussed.
700 citations
Posted Content•
TL;DR: In this paper, the authors study a contest with multiple (not necessarily equal) prizes and show that for any number of contestants having linear, convex or concave cost functions, and for any distribution of abilities, it is optimal for the designer to allocate the entire prize sum to a single ''first'' prize.
Abstract: We study a contest with multiple (not necessarily equal) prizes. Contestants have private information about an ability parameter that affects their costs of bidding. The contestant with the highest bid wins the first prize, the contestant with the second-highest bid wins the second prize, and so on until all the prizes are allocated. All contestants incur their respective costs of bidding. The contest's designer maximizes the expected sum of bids. Our main results are: 1) We display bidding equlibria for any number of contestants having linear, convex or concave cost functions, and for any distribution of abilities. 2) If the cost functions are linear or concave, then, no matter what the distribution of abilities is, it is optimal for the designer to allocate the entire prize sum to a single ''first'' prize. 3) We give a necessary and sufficient conditions ensuring that several prizes are optimal if contestants have a convex cost function.
678 citations
TL;DR: In this article, the authors show that price formation via the procedure of competitive bidding satisfies a version of the law of large numbers, in both the probabilistic sense and the economic sense.
Abstract: I demonstrate in this paper that price formation via the procedure of competitive bidding satisfies a version of the law of large numbers, in both the probabilistic sense and the economic sense. That is, if in a sealed-tender auction a seller offers to sell at the highest bid an item having a definite but unknown monetary value, and each of many bidders submits a bid based only on his private sample information about the value, where the bidders' samples are independent and identically distributed conditional on the value, then the maximum bid is almost surely equal to the true value. Thus, no bidder knows the true value of the item, yet it is essentially certain that the seller will receive that value as the sale price. Certain regularity assumptions are needed to prove this proposition. I present three examples, two for which the result is valid and another for which it is not.
645 citations