考虑时间和资本因素的多Agent拍卖系统数学模型与数值模拟

创建了一类考虑时间和资本因素的多Agent拍卖系统的数学模型,定义了买方Agent的出价线程和出价函数,具有时间偏好和不同资本大小的买方Agent可采用不同的出价战术,不同的出价战术对各自和效用与系统效用产生不同影响.通过数值模拟,分析了采用不同出众战术下的买方Agent、卖方Agent及系统的效用.     

常数相对风险厌恶多单位拍卖的比较静态与定价结构

考虑竞价者具有常数相对风险厌恶时的多单位拍卖问题,讨论均衡出价与风险偏好以及价值分布之间的关系.在竞价者具有相同的风险偏好的对称拍卖情形,利用风险中性等价导出了比较静态的充要条件,这一充要条件综合了风险偏好和价值分布的变化.在竞价者具有不同的风险偏好的非对称拍卖中,导出了均衡出价关于风险偏好的线性定价结构,依据这一结构,对任意给定出价,竞价者要求的剩余是其风险厌恶参数的线性函数,并且可以分解为竞争性剩余和风险厌恶剩余.     

多物品拍卖的捆绑销售策略

拍卖商在拍卖多个不同物品的过程中,面临着是捆绑拍卖还是分开拍卖的问题.本文讨论在第二价格密封拍卖(维克里拍卖)方式下,拍卖商拍卖多个不同物品时,其所采取的最优策略(捆绑拍卖或是分开拍卖)与投标人的数量以及投标人对物品的估价的关系.     

拍卖网站多物品多批次拍卖收益分析研究

考虑到网上拍卖的特性,包括竞标者随机到达,末尾抢标效应,拍卖平台的存在和收费,以及多物品多批次,文中系统地研究了拍卖品不设置保留价和设置保留价时拍卖网站的收益问题,并利用动态规划模型求解了拍卖网站多物品多批次拍卖时的最优总收益,证明了在降低陈列费和增加佣金比例的同时,缩短拍卖时间有利于设计出激励相容的最优拍卖机制.     

拍卖市场上不同经验类型竞价者竞价行为研究

研究公共价值拍卖市场上不同经验类型竞价者的竞价行为.根据拍卖经验的不同可以把竞价人分成两类:天真者和理性者.通过建立"天真-理性"的竞价模型,分析了天真者与理性者最优出价策略,得到了在价值信号均匀分布情况下,天真者的事前期望支付大于理性者的事前期望支付;并得到了天真者的进化比例.     

密封第一价格拍卖中的竞拍者串谋分析——基于“强”卡特尔的第一价格预拍

已有密封一价拍卖竞拍者串谋均衡研究中存在不符合现实的诸多约束,鉴于此,在串谋只包含部分竞拍者、串谋成员与非串谋尔成员间形成独立、非对称以及连续的价值分布并同时存在竞价策略互动的假设下,建立串谋方和非串谋方互动的竞价优化模型以及拍卖方的保留价格优化模型,得到串谋方和非串谋方的最优竞拍出价以及竞拍方的最优保留价格。结果表明串谋方和非串谋方的出价策略不仅与自身的估价、竞标人数、串谋人数相关,也与对方的估价存在关联性;拍卖方的最优保留价格设定与非串谋方和串谋方的价值分布存在关联。     

考虑全局投标者后悔心理行为的组合拍卖的投标均衡策略

许多实验研究表明投标者在拍卖过程中往往表现出预期后悔心理行为,并且投标者的预期后悔心理行为将会对投标策略产生影响,但以往大多是针对单物品拍卖研究考虑投标者后悔心理行为的投标均衡策略,而针对多物品拍卖情形的研究较少关注。本文着重研究了考虑投标者后悔心理行为的组合拍卖的投标均衡策略问题,在全局投标者存在预期后悔心理行为的假设下,依据Engelbrecht-Wiggans和Katok提出的后悔函数刻画了投标者的后悔心理行为,在此基础上,构建了组合拍卖模型,通过分析给出了全局投标者投标均衡策略需要满足的充分和必要条件。进一步地,依据构建的模型,通过数值实验分析了局部投标者人数、组合效应系数和全局投标者后悔参数对全局投标者投标策略的影响。最后,通过一个关于无线电频谱组合拍卖的算例说明了本文给出的模型及投标均衡策略确定方法的潜在应用和优越性。     

两种记分函数下多属性拍卖投标均衡策略

以拍卖人期望收益最大化为机制设计目标,讨论两种不同偏好的记分函数条件下,最高得分密封投标拍卖和连续完全信息多属性英式拍卖中,卖者的最优投标策略和买者的最优拍卖设计问题,主要结论是:1)无论选择哪种拍卖方式和记分函数,拍卖人均有动机隐瞒自己的真实偏好,除非竞价人是同质的或参与人数足够多.2)竞价人最优属性策略qi*与拍卖...     

多物品网上拍卖机制中最优保留价比较分析

虑到网上拍卖的特性,包括竞标者随机到达、末尾抢标效应、拍卖平台的存在和收费等,文中系统地研究了多物品网上拍卖中的保留价问题.在同一分析框架下,分别求解了卖家不设定保留价和设定保留价时最优保留价所应满足的条件及影响因素,并证明了不公开保留价能给卖家带来更多的期望利润.     

车辆牌照拍卖模型

提出多个相同物品(如车辆牌照)同时密封拍卖的模型，给出对称均衡竞标策略；证明了该拍卖方式与第一价格密封连续拍卖产生相同的预期收益；对估价为均匀分布的拍卖预期收益进行了研究。     

How to bid in unified second-price auctions when requests are duplicated

In display advertising auctions, a unique display opportunity may trigger many bid requests being sent to the same buyer. Bid request duplication is an issue: programmatic bidding agents might bid against themselves. In a simplified setting of unified second-price auctions, the optimal solution for the bidder is to randomize the bid, which is quite unusual. Our results motivate the recent switch to a unified first-price auction by showing that a unified second-price auction could have been detrimental to all participants.     

Dynamic lot-sizing in sequential online retail auctions

Retailers often conduct non-overlapping sequential online auctions as a revenue generation and inventory clearing tool. We build a stochastic dynamic programming model for the seller’s lot-size decision problem in these auctions. The model incorporates a random number of participating bidders in each auction, allows for any bid distribution, and is not restricted to any specific price-determination mechanism. Using stochastic monotonicity/stochastic concavity and supermodularity arguments, we present a complete structural characterization of optimal lot-sizing policies under a second order condition on the single-auction expected revenue function. We show that a monotone staircase with unit jumps policy is optimal and provide a simple inequality to determine the locations of these staircase jumps. Our analytical examples demonstrate that the second order condition is met in common online auction mechanisms. We also present numerical experiments and sensitivity analyses using real online auction data.     

All-pay auctions with risk-averse players

We study independent private-value all-pay auctions with risk-averse players. We show that: (1) Players with low values bid lower and players with high values bid higher than they would bid in the risk neutral case. (2) Players with low values bid lower and players with high values bid higher than they would bid in a first-price auction. (3) Players’ expected utilities in an all-pay auction are lower than in a first-price auction. We also use perturbation analysis to calculate explicit approximations of the equilibrium strategies of risk-averse players and the seller’s expected revenue. In particular, we show that in all-pay auctions the seller’s expected payoff in the risk-averse case may be either higher or lower than in the risk neutral case.     

Comparing the Spanish and the discriminatory auction formats: A discrete model with private information

The Spanish Treasury is the only Treasury in the world that uses a hybrid system of discriminatory and uniform price auctions to sell government debt: winning bidders pay their bid price for each unit if this is lower than the weighted average price of winning bids (WAP), and pay the WAP otherwise. Following Gordy [Gordy, M., 1996. Multiple bids in a multiple-unit common-value auction. Board of Governors of the Federal Reserve System], we model the Spanish auction as a common value auction of multiple units with private information, allowing for multiple bids. Numerical analysis shows that bidders spread their bids more in the Spanish than in the discriminatory auction and bid higher for the first unit, and that the expected seller’s revenue is higher in the Spanish than in the discriminatory auction within a reasonable set of parameter values.     

Using bid data for the management of sequential,multi-unit,online auctions with uniformly distributed bidder valuations

Internet auctions for consumers’ goods are an increasingly popular selling venue. We have observed that many sellers, instead of offering their entire inventory in a single auction, split it into sequential auctions of smaller lots, thereby reducing the negative market impact of larger lots. Information technology also makes it possible to collect and analyze detailed bid data from online auctions. In this paper, we develop and test a new model of sequential online auctions to explore the potential benefits of using real bid data from earlier auctions to improve the management of future auctions. Assuming a typical truth-revealing auction model, we quantify the effect of the lot size on the closing price and derive a closed-form solution for the problem of allocating inventory across multiple auctions when bidder valuation distributions are known. We also develop a decision methodology for allocating inventory across multiple auctions that dynamically incorporates the results of previous auctions as feedback into the management of subsequent auctions, and updating the lot size and number of auctions. We demonstrate how information signals from previous auctions can be used to update the auctioneer’s beliefs about the customers’ valuation distribution, and then to significantly increase the seller’s profit potential. We use several examples to reveal the benefits of using detailed transaction data for the management of sequential, multi-unit, online auctions and we demonstrate how these benefits are influenced by the inventory holding costs, the number of bidders, and the dispersion of consumers’ valuations.     

Graphical method for identifying high outliers in construction contract auctions

Construction contract auctions are characterised by (1) a heavy emphasis on the lowest bid, as that is which usually determines the winner of the auction, (2) anticipated high outliers due to the presence of uncompetitive bids, (3) very small samples, and (4) uncertainty of the appropriate underlying density function model of the bids. This paper describes a graphical method for simultaneously identifying outliers and density functions by first removing candidate (high) outliers and then examining the goodness-of-fit of the resulting reduced samples by comparing the reduced sample predictability (by the expected value of the lowest order statistic) of the lowest bid with that of the equivalent predictability by Monte Carlo simulations of one of the common density functions. When applied to a set of 1073 auctions, the results indicate the appropriateness of censored and reduced sample lognormal models for a wide range of cut-off values. These are compared with cut-off values used in practice and to identify potential improvements.     

On the impact of low-balling: Experimental results in asymmetric auctions

The paper reports on a series of asymmetric auction experiments with private-independent values and two buyers. Maskin and Riley (2000) showed, under some conditions, that if one buyer has a greater probability than the other of not being able to bid, first-price auctions could yield lower revenues to the seller than second-price auctions. The data rejected this prediction because of an important overbidding when subjects received low values in first-price auctions. In this asymmetric setting, the observed overbidding cannot be explained by the usual risk aversion hypothesis and the detection of a learning pattern indicates that subjects used more an adaptive behaviour than a static one. An ad hoc bidding strategy for the buyers who are the most likely to bid explains the observed low bids better than the risk neutral equilibrium strategy. Finally, as subjects appear to have bid in equilibrium as if there were two other competitors instead of only one, their bidding behaviour can be thought to have displayed an over anxiousness about winning. Received: January 1999/Final version June 2001     

Exact methods for combinatorial auctions

This is a summary of the author’s PhD thesis supervised by Frits Spieksma and defended on 20 December 2006 at the Katholieke Universiteit Leuven. The thesis is written in English and is available from the author’s website (http://www.econ.kuleuven.be/dries.goossens/public). This work deals with combinatorial auctions, i.e., auctions where bidders can bid on sets of items. We study two special cases, namely the total quantity discount auction and the matrix bid auction.      

Nonparametric identification and estimation of score auctions in multi-attribute procurement

Score auctions are used in procurement to incorporate other attributes beyond price. We establish nonparametric econometric identification of bidders' pseudotypes (a measure of bidder's private cost), when bids are evaluated using a preannounced quasi-linear score, calculated on the basis of the submitted levels of the attributes. Hence, we extend the standard nonparametric method for independent private costs sealed-bid, first price auctions, to multi-attribute quasi-linear score auctions. We illustrate the result with an application to scoring bid data.     

All-pay auctions with pre- and post-bidding options

Motivated by the emergence of online penny or pay-to-bid auctions, in this study, we analyze the operational consequences of all-pay auctions competing with fixed list price stores. In all-pay auctions, bidders place bids, and highest bidder wins. Depending on the auction format, the winner pays either the amount of their bid or that of the second-highest bid. All losing bidders forfeit their bids, regardless of the auction format. Bidders may visit the store, both before and after bidding, and buy the item at the fixed list price. In a modified version, we consider a setting where bidders can use their sunk bid as a credit towards buying the item from the auctioneer at a fixed price (different from the list price). We characterize a symmetric equilibrium in the bidding/buying strategy and derive optimal list prices for both the seller and auctioneer to maximize expected revenue. We consider two situations: (1) one firm operating both channels (i.e. fixed list price store and all-pay auction), and (2) two competing firms, each operating one of the two channels.