多物品价格歧视拍卖模型

本文将单物品的M-参数、对数凹效用拍卖推广到多物品价格歧视拍卖.我们得到了出价函数为均衡出价函数的充要条件.     

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.     

具有损失厌恶偏好的Muthoo交替出价谈判博弈研究

现实的谈判中往往存在谈判破裂的风险,Muthoo基于参与人理性,提出了刻画具有谈判破裂风险的交替出价谈判博弈模型.然而实验经济学和心理学研究表明,决策主体通常具有损失厌恶行为.文章对具有损失厌恶行为的Muthoo交替出价谈判博弈进行研究.首先将在过去谈判阶段的最高出价作为参与人的参考点,这使得收益与均衡策略依赖于谈判历史.然后构建子博弈完美均衡,该均衡通过当前阶段的参考点依赖于谈判历史;基于子博弈完美均衡策略满足静态的马尔科夫策略、立刻接受以及接受-拒绝无差异性等三条性质,证明了子博弈完美均衡的唯一性;最后分析子博弈完美均衡关于损失厌恶行为的敏感性及其收敛性.发现:参与人受益于对手的损失厌恶行为,而因自身的损失厌恶行为遭受损失.     

基于网上拍卖的共同价值托投标分析

基于信息不对称条件下的共同价值模型,刻画了网上拍卖过程中可能存在的托投标行为,并运用博弈理论结合竞价关系求解了竞标者的赢标概率和最优竞价策略．研究发现,在共同价值模型下,参与竞标的人数与嬴者诅咒的发生存在联系;在最高出价者赢标的概率模型基础上,分别建立了是否存在托投标行为时的竞标者收益模型,并求解了竞标者的均衡竞价策略．     

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。     

博弈参与人的偏好对最优反应的影响分析

在现实社会中，每个人都有自己的偏好，因此在博弈过程中，参与人的不同偏好在其选择策略时起着不同的作用。本文运用多目标决策方法研究了总需求不确定情况下具有风险偏好的企业决策者关于一种产品价格博弈模型和均衡，并进一步讨论了参与人具有相同偏好和不同偏好情况下风险厌恶程度、价格对需求影响程度等参数对参与人最优反应的影响。     

基于条件风险值准则的供应链回购契约协调策略

研究了由具有风险偏好的零售商和风险中性的供应商组成的两级供应链回购契约协调问题.针对具有风险偏好的零售商,考虑了风险中性、风险厌恶和风险喜好三种态度,建立了由风险厌恶程度和悲观系数两个参数描述的基于条件风险值(CVaR)的集成目标决策函数.推导了不同风险偏好态度下的零售商最优订货决策,分析了不同风险偏好参数下的零售商订货决策变化情况.给出了能够完全协调风险偏好零售商和风险中性供应商的供应链回购契约协调机制.最后,进行了数值计算,验证了设计的供应链回购契约协调策略的有效性.结果表明,在给出的回购契约协调机制下,考虑风险偏好情况下的零售商最优订货决策能够保证整个供应链系统实现最优绩效,而供应链成员期望利润却随不同的风险偏好参数而不同.     

风险厌恶下的供应链收益共享契约协调模型研究

收益共享契约是实现供应链系统绩效改善或完美协调的一种机制.考虑了零售商与供应商分别具有风险厌恶决策偏好情况下,在随机市场需求下建立了由单供应商和单零售商组成的二级供应链的收益共享契约模型,并对模型进行了分析,揭示了供应商和零售商的风险厌恶决策偏好对收益共享契约参数的影响.研究结果表明:当销售商(供应商)的风险厌恶控制在...     

跨期的预防性努力投资决策研究-基于约束的Ross更加风险厌恶的刻画

在跨期的预防性努力投资决策问题中,一个Ross更加风险厌恶的个体未必会投资更多的预防性努力.为了解决这种不一致性,本文基于约束的Ross更加风险厌恶的刻画,获得了与个体风险偏好相一致的比较静态结果:当现在1单位财富的预防性努力投资致使个体将来的财富均值增加额的现值不超过1时,那么一个线性约束的Ross更加风险厌恶的个体...     

个体对股票投资的风险态度研究

传统理论认为个体是风险厌恶的,展望理论提出个体是损失厌恶的,对于损失的感受程度比赢得要强烈得多。本文通过实验表明,大部分个体对于股票投资是风险追求,而不是风险厌恶的,而且在两个参考点之外的区间个体更偏好风险,而在两个参考点之内的区间对风险的偏好程度相对要小。     

Large auctions with risk-averse bidders

We study private-value auctions with n risk-averse bidders, where n is large. We first use asymptotic analysis techniques to calculate explicit approximations of the equilibrium bids and of the seller’s revenue in any k-price auction (k = 1, 2, . . .). These explicit approximations show that in all large k-price auctions the effect of risk-aversion is O(1/n ²) small. Hence, all large k-price auctions with risk-averse bidders are O(1/n ²) revenue equivalent. The generalization, that all large auctions are O(1/n ²) revenue equivalent, is false. Indeed, we show that there exist auction mechanisms for which the limiting revenue as ${n\longrightarrow \infty }We study private-value auctions with n risk-averse bidders, where n is large. We first use asymptotic analysis techniques to calculate explicit approximations of the equilibrium bids and of the seller’s revenue in any k-price auction (k = 1, 2, . . .). These explicit approximations show that in all large k-price auctions the effect of risk-aversion is O(1/n ²) small. Hence, all large k-price auctions with risk-averse bidders are O(1/n ²) revenue equivalent. The generalization, that all large auctions are O(1/n ²) revenue equivalent, is false. Indeed, we show that there exist auction mechanisms for which the limiting revenue as n? ￥{n\longrightarrow \infty } with risk-averse bidders is strictly below the risk-neutral limit. Therefore, these auction mechanisms are not revenue equivalent to large k-price auctions even to leading-order as n? ￥{n\longrightarrow \infty }.     

Risk-averse decision making in overbooking problem

Traditional literature studying overbooking problems focuses on risk-neutral decision makers. In this paper, we propose a multi-period overbooking model incorporating risk-aversion and extend well-known structural results (the 3-region policy) under the risk-neutral case to the risk-averse one on the basis of an exponential utility function. We also show that the optimal policy for the risk-neutral decision maker can be obtained by letting the risk-aversion parameter approach to zero under the risk-averse case. Therefore, the extant results under the risk-neutral case can be interpreted as a special case of ours. We also investigate how the optimal policy changes with some cost parameters and the decision maker's degree of risk-aversion. Numerical results suggest that the optimal bounds in the 3-region policy may increase or decrease with the decision maker's degree of risk-aversion.     

First- and second-price sealed-bid auctions applied to push and pull supply contracts

We investigate a newsvendor-type retailer sourcing problem under demand uncertainty who has the option to source from multiple suppliers. The suppliers’ manufacturing costs are private information. A widely used mechanism to find the least costly supplier under asymmetric information is to use a sealed-bid reverse auction. We compare the combinations of different simple auction formats (first- and second-price) and risk sharing supply contracts (push and pull) under full contract compliance, both for risk-neutral and risk-averse retailer and suppliers. We show the superiority of a first-price push auction for a risk-neutral retailer. However, only the pull contracts lead to supply chain coordination. If the retailer is sufficiently risk-averse, the pull is preferred over the push contract. If suppliers are risk-averse, the first-price push auction remains the choice for the retailer. Numerical examples illustrate the allocation of benefits between the retailer and the (winning) supplier for different number of bidders, demand uncertainty, cost uncertainty, and degree of risk-aversion.     

面向电子逆向拍卖的多属性报价建议模型

针对多属性拍卖中报价的复杂性和现有报价指导模型的局限性,提出了一个以拍卖方的总价值提升为基本约束,以投标人的利润最大化为目标的多属性报价建议模型,并引入二元变量解决了定性属性的推荐问题。当投标人具有不同的投标能力和偏好时,模型可根据投标人的投标要求进行报价推荐;当存在单位价值相同的推荐报价时,模型设置了相应的约束以鼓励早投标行为。最后,还从理论上证明了该模型的稳定性,并通过算例说明了模型的可行性。     

Option pricing under regime-switching models: Novel approaches removing path-dependence

A well-known approach for the pricing of options under regime-switching models is to use the regime-switching Esscher transform (also called regime-switching mean-correcting martingale measure) to obtain risk-neutrality. One way to handle regime unobservability consists in using regime probabilities that are filtered under this risk-neutral measure to compute risk-neutral expected payoffs. The current paper shows that this natural approach creates path-dependence issues within option price dynamics. Indeed, since the underlying asset price can be embedded in a Markov process under the physical measure even when regimes are unobservable, such path-dependence behavior of vanilla option prices is puzzling and may entail non-trivial theoretical features (e.g., time non-separable preferences) in a way that is difficult to characterize. This work develops novel and intuitive risk-neutral measures that can incorporate regime risk-aversion in a simple fashion and which do not lead to such path-dependence side effects. Numerical schemes either based on dynamic programming or Monte-Carlo simulations to compute option prices under the novel risk-neutral dynamics are presented.     

On being balanced in an unbalanced world

This paper examines the case of a procurement auction for a single project, in which the breakdown of the winning bid into its component items determines the value of payments subsequently made to bidder as the work progresses. Unbalanced bidding, or bid skewing, involves the uneven distribution of mark-up among the component items in such a way as to attempt to derive increased benefit to the unbalancer but without involving any change in the total bid. One form of unbalanced bidding for example, termed Front Loading (FL), is thought to be widespread in practice. This involves overpricing the work items that occur early in the project and underpricing the work items that occur later in the project in order to enhance the bidder's cash flow. Naturally, auctioners attempt to protect themselves from the effects of unbalancing—typically reserving the right to reject a bid that has been detected as unbalanced. As a result, models have been developed to both unbalance bids and detect unbalanced bids but virtually nothing is known of their use, success or otherwise. This is of particular concern for the detection methods as, without testing, there is no way of knowing the extent to which unbalanced bids are remaining undetected or balanced bids are being falsely detected as unbalanced. This paper reports on a simulation study aimed at demonstrating the likely effects of unbalanced bid detection models in a deterministic environment involving FL unbalancing in a Texas DOT detection setting, in which bids are deemed to be unbalanced if an item exceeds a maximum (or fails to reach a minimum) ‘cut-off’ value determined by the Texas method. A proportion of bids are automatically and maximally unbalanced over a long series of simulated contract projects and the profits and detection rates of both the balancers and unbalancers are compared. The results show that, as expected, the balanced bids are often incorrectly detected as unbalanced, with the rate of (mis)detection increasing with the proportion of FL bidders in the auction. It is also shown that, while the profit for balanced bidders remains the same irrespective of the number of FL bidders involved, the FL bidder's profit increases with the greater proportion of FL bidders present in the auction. Sensitivity tests show the results to be generally robust, with (mis)detection rates increasing further when there are fewer bidders in the auction and when more data are averaged to determine the baseline value, but being smaller or larger with increased cut-off values and increased cost and estimate variability depending on the number of FL bidders involved. The FL bidder's expected benefit from unbalancing, on the other hand, increases, when there are fewer bidders in the auction. It also increases when the cut-off rate and discount rate is increased, when there is less variability in the costs and their estimates, and when less data are used in setting the baseline values.     

Fraction auctions: The tradeoff between efficiency and running time

This paper studies the sales of a single indivisible object where bidders have continuous valuations. In Grigorieva et al. [14] it was shown that, in this setting, query auctions necessarily allocate inefficiently in equilibrium. In this paper we propose a new sequential auction, called the c-fraction auction. We show the existence of an ex-post equilibrium, called bluff equilibrium, in which bidders behave truthfully except for particular constellations of observed bids at which it is optimal to pretend a slightly higher valuation. We show c-fraction auctions guarantee approximate efficiency at any desired level of accuracy, independent of the number of bidders, when bidders choose to play the bluff equilibrium. We discuss the running time and the efficiency in the bluff equilibrium. We show that by changing the parameter c of the auction we can trade off efficiency against running time.     

Real-World Forward Rate Dynamics With Affine Realizations

We investigate the existence of affine realizations for Lévy driven interest rate term structure models under the real-world probability measure, which so far has only been studied under an assumed risk-neutral probability measure. For models driven by Wiener processes, all results obtained under the risk-neutral approach concerning the existence of affine realizations are transferred to the general case. A similar result holds true for models driven by compound Poisson processes with finite jump size distributions. However, in the presence of jumps with infinite activity we obtain severe restrictions on the structure of the market price of risk; typically, it must even be constant.     

Robust strategic bidding in auction-based markets

In this paper, we propose an alternative methodology for devising revenue-maximizing strategic bids under uncertainty in the competitors’ bidding strategy. We focus on markets endowed with a sealed-bid uniform-price auction with multiple divisible products. On recognizing that the bids of competitors may deviate from equilibrium and are of difficult statistical characterization, we proposed a two-stage robust optimization model with equilibrium constraints aiming to devise risk-averse strategic bids. The proposed model is a trilevel optimization problem that can be recast as a particular instance of a bilevel program with equilibrium constraints. Reformulation procedures are proposed to find a single-level equivalent formulation suitable for column-and-constraint generation (CCG) algorithm. Results show that even for the case in which an imprecision of 1% is observed on the rivals’ bids in the equilibrium point, the robust solution provides a significant risk reduction (of 79.9%) in out-of-sample tests. They also indicate that the best strategy against high levels of uncertainty on competitors’ bid approaches to a price-taker offer, i.e., bid maximum capacity at marginal cost.