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...     

基于不同核函数的非参数与参数利率模型的国债定价

以上海证券交易所的国债回购利率数据为样本,本文采用两种不同核函数:高斯核和抛物线核对非参数利率期限结构模型进行估计.结果显示:短期利率的密度函数是非正态的,扩散过程的漂移函数和扩散函数都是非线性的,高斯核比抛物线核对扩散函数拟合更平滑.然后,给出了基于非参数和参数利率模型的国债定价的方法,并对非参数利率模型、Vasicek模型、CIR模型、多项式样条静态模型进行国债定价预测比较与分析.     

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.     

The secretary problem with multiple job vacancies and batch candidate arrivals

We extend the secretary problem with multiple vacancies to allow batch arrival of candidates. We establish structural properties of the optimal policies. We show that the optimal reward is convex and submodular in the values of candidates, which means that there is benefit for having a candidate pool with more variable or less interdependent values. Similar properties continue to hold when there are multiple classes of vacancies. Our model is applicable to recruitment, dynamic auctions and sequential investment.     

Designing sniping agents

Sniping agents are increasingly being deployed to assist bidders in acquiring items in online auctions. This paper reviews the extant auction literature and proposes an overarching sniping agent design framework that could potentially increase the commercial viability of snipping agents. For better alignment between the functions of sniping agents and the needs of human bidders, we review existing literature based on three fundamentals: (1) knowledge about human bidder behavior, (2) awareness of the product(s) desired by a bidder, and (3) an understanding of the research on bidding agents and auction design. The output of this review is the explicit consideration of iterative combinatorial auction agent design, fuzzy set representation of the bidder’s preferences and dynamic derivation of bidding strategies according to the progress of ongoing auctions.     

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.     

基于数据包络分析的混合多属性第二分值拍卖机制

多属性拍卖在传统价格拍卖的基础上纳入了价格和质量多个属性,已广泛应用于许多领域。本文针对输入几乎没有先验结构且投标人数量足够大的情况,在以往有关多属性拍卖研究的基础上将单个投入扩展为多个投入,将物品的多个属性(价格、完成时间、劳动力数量、质量等因素)合理划分为投入或产出,设计了运行有效的基于数据包络分析的多属性第二分值拍卖机制。与其他方法相比,数据包络分析方法可以有效解决多投入多产出问题,结合多目标规划方法,可以帮助采购方在最大化自身利益的同时,找到整体表现更好的供应商。该机制满足个人理性和激励相容,与传统第二分值拍卖机制相比,在吸引投标人的前提下能够最大化拍卖人的利益。     

Estimating intermediate price transitions in online auctions

This paper discusses a statistical model regarding intermediate price transitions of online auctions. The objective was to characterize the stochastic process by which prices of online auctions evolve and to estimate conditional intermediate price transition probabilities given current price, elapsed auction time, number of competing auctions, and calendar time. Conditions to ensure monotone price transitions in the current price and number of competing auctions are discussed and empirically validated. In particular, we show that over discrete periods, the intermediate price transitions are increasing in the current price, decreasing in the number of ongoing auctions at a diminishing rate, and decreasing over time. These results provide managerial insight into the effect of how online auctions are released and overlap. The proposed model is based on the framework of generalized linear models using a zero‐inflated gamma distribution. Empirical analysis and parameter estimation is based on data from eBay auctions conducted by Dell. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

Non-linear anonymous pricing combinatorial auctions

In combinatorial auctions the pricing problem is of main concern since it is the means by which the auctioneer signals the result of the auction to the participants. In order for the auction to be regarded as fair among the various participants the price signals should be such that a participant that has won a subset of items knows why his bid was a winning bid and that agents that have not acquired any item easily can detect why they lost. The problem in the combinatorial auction setting is that the winner determination problem is a hard integer programming problem and hence a linear pricing scheme supporting the optimal allocation might not exist.