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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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Journal ArticleDOI
TL;DR: In this paper, the authors conduct a test of adverse selection in the equity issuance process and show that it is the degree of protection against adverse price changes and not the percent of stock offered in a bank merger that explains bidder merger announcement abnormal returns.
Abstract: We conduct a unique test of adverse selection in the equity issuance process. While common stock is the dominant means of payment in bank mergers, stock acquisition agreements provide target shareholders with varying degrees of protection against adverse price movements in the bidder's stock between the time of the merger agreement and the time of merger completion. We show that it is the degree of protection against adverse price changes and not the percent of stock offered in a bank merger that explains bidder merger announcement abnormal returns. This result is difficult to explain outside of an adverse selection framework. FIRMS ARE OFTEN RELUCTANT to issue equity to fund new investments. A frequently cited rationale for this reluctance is that markets might interpret an equity issue authorized by managers with private information about a firm's value as a signal that the firm's stock is overvalued (Myers and Majluf (1984)). Consistent with this adverse selection scenario, firms generally experience a significant drop in their stock price when they announce that they are selling stock in a secondary offering,1 and merger announcement returns are lower when bidding firms offer stock, rather than cash, as payment.2 There are, however, alternative explanations for why share prices decline when firms issue equity. Firms issuing equity rather than debt may forego the discipline that debt imposes on managers (Jensen (1986)) or lose the potential tax advantages of debt financing. Additionally, firms issuing equity may face a downward sloping demand curve for firm shares (Loderer, Cooney, and Van Drunen (1991)). While these explanations are not mutually exclusive, testing the validity of any one explanation requires controlling for the alternatives. In this article we conduct a unique test that isolates the impact of adverse selection in the equity issuance process. Our tests focus on the means of payment used in a large sample of bank mergers agreements during the period 1985-1992. Acquiring banks issuing stock to target bank shareholders offer varying degrees of protection to target shareholders against adverse private

157 citations

Proceedings ArticleDOI
02 Feb 2017
TL;DR: In this article, the authors formulate the bid decision process as a reinforcement learning problem, where the state space is represented by the auction information and the campaign's real-time parameters, while an action is the bid price to set.
Abstract: The majority of online display ads are served through real-time bidding (RTB) --- each ad display impression is auctioned off in real-time when it is just being generated from a user visit. To place an ad automatically and optimally, it is critical for advertisers to devise a learning algorithm to cleverly bid an ad impression in real-time. Most previous works consider the bid decision as a static optimization problem of either treating the value of each impression independently or setting a bid price to each segment of ad volume. However, the bidding for a given ad campaign would repeatedly happen during its life span before the budget runs out. As such, each bid is strategically correlated by the constrained budget and the overall effectiveness of the campaign (e.g., the rewards from generated clicks), which is only observed after the campaign has completed. Thus, it is of great interest to devise an optimal bidding strategy sequentially so that the campaign budget can be dynamically allocated across all the available impressions on the basis of both the immediate and future rewards. In this paper, we formulate the bid decision process as a reinforcement learning problem, where the state space is represented by the auction information and the campaign's real-time parameters, while an action is the bid price to set. By modeling the state transition via auction competition, we build a Markov Decision Process framework for learning the optimal bidding policy to optimize the advertising performance in the dynamic real-time bidding environment. Furthermore, the scalability problem from the large real-world auction volume and campaign budget is well handled by state value approximation using neural networks. The empirical study on two large-scale real-world datasets and the live A/B testing on a commercial platform have demonstrated the superior performance and high efficiency compared to state-of-the-art methods.

157 citations

Posted Content
TL;DR: In this paper, the authors present an analysis for a stylised model in which bidders receive a private value signal and an independent common value signal, and show that more uncertainty about the common value has a negative effect on efficiency.
Abstract: The objects for sale in most auctions possess both private and common value elements. This salient feature has not yet been incorporated into a strategic analysis of equilibrium bidding behaviour. This paper reports such an analysis for a stylised model in which bidders receive a private value signal and an independent common value signal. We show that more uncertainty about the common value has a negative effect on efficiency. Information provided by the seller decreases uncertainty, which raises efficiency and seller's revenues. Efficiency and revenues are also higher when more bidders enter the auction.

157 citations

Book ChapterDOI
17 Dec 2008
TL;DR: A Markovian user model is studied that retains the core bidding dynamics of the GSP auction that make it useful for advertisers, and shows that the optimal assignment can be found efficiently (even in near-linear time).
Abstract: Sponsored search involves running an auction among advertisers who bid in order to have their ad shown next to search results for specific keywords. The most popular auction for sponsored search is the "Generalized Second Price" (GSP) auction where advertisers are assigned to slots in the decreasing order of their score , which is defined as the product of their bid and click-through rate. One of the main advantages of this simple ranking is that bidding strategy is intuitive: to move up to a more prominent slot on the results page, bid more. This makes it simple for advertisers to strategize. However this ranking only maximizes efficiency under the assumption that the probability of a user clicking on an ad is independent of the other ads shown on the page. We study a Markovian user model that does not make this assumption. Under this model, the most efficient assignment is no longer a simple ranking function as in GSP. We show that the optimal assignment can be found efficiently (even in near-linear time). As a result of the more sophisticated structure of the optimal assignment, bidding dynamics become more complex: indeed it is no longer clear that bidding more moves one higher on the page. Our main technical result is that despite the added complexity of the bidding dynamics, the optimal assignment has the property that ad position is still monotone in bid. Thus even in this richer user model, our mechanism retains the core bidding dynamics of the GSP auction that make it useful for advertisers.

157 citations

Journal ArticleDOI
TL;DR: Equilibrium is characterized and it is shown that steeper securities yield higher revenues, that auction formats can be ranked based on the security design, and that informal auctions lead to the lowest possible revenues.
Abstract: We study security-bid auctions in which bidders compete for an asset by bidding with securities. That is, they offer payments that are contingent on the realized value of the asset being sold. The value depends on investment by the winner, thus creating the possibility of moral hazard. Such auctions are commonly used, both formally and informally. In formal auctions, the seller generally restricts bids to an ordered set, such as an equity share or royalty rate. By restricting the bids, standard auction formats such as first and second-price auctions can be used. In informal settings with competing buyers, the seller does not commit to a mechanism upfront. Rather, bidders offer securities and the seller chooses the most attractive bid, based on his beliefs, ex-post. We characterize equilibrium payoffs and bidding strategies in this setting, and show that an informal mechanism yields the lowest possible revenues across all mechanisms. We also determine the optimal formal mechanism, and show that the security design is more important than the auction format. We show that the revenue equivalence principle (that expected revenues are independent of the auction format) holds if the set of permissible securities is ordered and convex (such as equity). Otherwise, it need not hold. For example, when bidders offer standard debt securities, a second-price auction is superior. On the other hand, if bidders compete on the conversion ratio of convertible debt, a first- price auction yields higher revenues. Finally, we examine how different forms of moral hazard impact our results.

156 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
2023566
20221,134
2021637
2020708
2019830