Bidding In Auctions Research Articles

Optimal bidding in hourly and quarter-hourly electricity price auctions: Trading large volumes of power with market impact and transaction costs

This paper addresses the question of how much to bid to maximize the profit when trading in two electricity markets: the hourly Day-Ahead Auction and the quarter-hourly Intraday Auction. For optimal coordinated bidding many price scenarios are examined, the own non-linear market impact is estimated by considering empirical supply and demand curves, and a number of trading strategies is used. Additionally, we provide theoretical results for risk neutral agents. The application study is conducted using the German market data, but the presented methods can be easily utilized with other two consecutive auctions. This paper contributes to the existing literature by evaluating the costs of electricity trading, i.e. the price impact and the transaction costs. The empirical results for the German EPEX market show that it is far more profitable to minimize the price impact rather than maximize the arbitrage.

Uninformed Bidding in Sequential Auctions

Abstract We consider a private-value auction with one-sided incomplete information in which two objects are sold in a sequence of two second-price auctions. The buyers have multiunit demand and are asymmetrically informed at the ex ante stage of the game. One buyer perfectly knows his type, and the other buyer is uninformed about her own type. We consider interim information acquisition by the uninformed buyer and derive an asymmetric equilibrium that is shown to produce a declining price sequence across both sales. The supermartingale property of the price sequence stems from the uninformed buyer’s incentives to gather private information, which leads to aggressive bidding in the first-stage auction.

Collaborative Flow-shop Scheduling Using Simulated Annealing and First Price Sealed Bid Auction to Minimize Total Cost and Make-span

Collaborative Flow-shop Scheduling Using Simulated Annealing and First Price Sealed Bid Auction to Minimize Total Cost and Make-span

Sunk Cost Analysis of Frequency Spectrum Auction Prices in Indonesia Using Data Envelopment Analysis

The purpose of this study is to investigate the sunk cost argument on the auction price of the frequency spectrum by measuring the efficiency of the frequency license fee paid by the auction winner. The efficiency method employs a nonparametric approach, namely Data Envelopment Analysis (DEA) with the Linear Programming method, with the hypothesis model tested using Path Analysis. The dataset under consideration was Indonesia's Big Three Service Providers (2015-2020). The results show that the spectrum auction price is efficient in its impact on service prices, revenues, and income taxes. The spectrum auction price has no effect, lending credence to the argument that the spectrum auction price is considered a sunk cost in the telecommunications industry. The research reason is that the higher the auction price, combined with the lower cost of service due to high competition, the harder it is for small businesses to win the auction. The winning bidder will remain under the control of the prominent organizers, so the government issues a merger policy for small businesses to compete in spectrum auction bids.

Risk-Free Bidding in Complement-Free Combinatorial Auctions

We study risk-free bidding strategies in combinatorial auctions with incomplete information. Specifically, what is the maximum profit that a complement-free (subadditive) bidder can guarantee in a multi-item combinatorial auction? Suppose there are n bidders and Bi is the value that bidder i has for the entire set of items. We study the above problem from the perspective of the first bidder, Bidder 1. In this setting, the worst case profit guarantees arise in a duopsony, that is when n = 2, so this problem then corresponds to playing an auction against a budgeted adversary with budget B2. We present worst-case guarantees for two simple and widely-studied combinatorial auctions; namely, the sequential and simultaneous auctions, for both the first-price and second-price case. In the general case of distinct items, our main results are for the class of fractionally subadditive (XOS) bidders, where we show that for both first-price and second-price sequential auctions Bidder 1 has a strategy that guarantees a profit of at least \((\sqrt {B_{1}}-\sqrt {B_{2}})^{2}\) when B2 ≤ B1, and this bound is tight. More profitable guarantees can be obtained for simultaneous auctions, where in the first-price case, Bidder 1 has a strategy that guarantees a profit of at least \(\frac {(B_{1}-B_{2})^{2}}{2B_{1}}\), and in the second-price case, a bound of B1 − B2 is achievable. We also consider the special case of sequential auctions with identical items, for which we provide tight guarantees for bidders with subadditive valuations.

Buyout Decisions of Level-K Bidders in Second-Price Auctions

Buyout Decisions of Level-K Bidders in Second-Price Auctions

Robust Screens for Noncompetitive Bidding in Procurement Auctions

We document a novel bidding pattern observed in procurement auctions from Japan: winning bids tend to be isolated, and there is a missing mass of close losing bids. This pattern is suspicious in the following sense: its extreme forms are inconsistent with competitive behavior under arbitrary information structures. Building on this observation, we develop systematic tests of competitive behavior in procurement auctions that allow for general information structures as well as nonstationary unobserved heterogeneity. We provide an empirical exploration of our tests, and show they can help identify other suspicious patterns in the data.

Impact of Process Misconception in Becker-DeGroot-Marschak Single Response Value Elicitation Procedures: An Experimental Investigation in Consumer Behavior Using the IKEA Effect

Consumer researchers frequently employ valuation experiments to assess consumer opinions and test related hypotheses. One popular method used in many such experiments is the Becker- DeGroot-Marschak (BDM) single-response value elicitation procedure that initiates an incentive for the subjects to respond with their true valuation by utilizing a random bid to which the participants’ bid is compared. However, the “random bid” is not a straightforward concept, and the participants may not fully understand the mechanics of the bidding process. Therefore, they may incorrectly associate the bidding mechanism with a conventional auction bidding process in which the highest bidder wins, causing biased valuation outcomes. In this paper, we introduce a comprehension measurement step to eliminate the process comprehension bias in BDM valuation experiments. We also discuss the potential impact of the treatment of “zero” bidders in the BDM procedure. The present work shows that the size and statistical significance of past consumer research results are positively correlated with the participant comprehension of the valuation procedure. The results suggest that consumer research using a single-response value elicitation procedure, which initiates an incentive for the subjects to respond with their true valuation, may not be trusted if the comprehension level is not controlled.

5G-Enabled UAV-to-Community Offloading: Joint Trajectory Design and Task Scheduling

Due to line-of-sight communication links and distributed deployment, Unmanned Aerial Vehicles (UAVs) have attracted substantial interest in agile Mobile Edge Computing (MEC) service provision. In this paper, by clustering multiple users into independent communities based on their geographic locations, we design a 5G-enabled UAV-to-community offloading system. A system throughput maximization problem is formulated, subjected to the transmission rate, atomicity of tasks and speed of UAVs. By relaxing the transmission rate constraint, the mixed integer non-linear program is transformed into two subproblems. We first develop an average throughput maximization-based auction algorithm to determine the trajectory of UAVs, where a community-based latency approximation algorithm is developed to regulate the designed auction bidding. Then, a dynamic task admission algorithm is proposed to solve the task scheduling subproblem within one community. Performance analyses demonstrate that our designed auction bidding can guarantee user truthfulness, and can be fulfilled in polynomial time. Extensive simulations based on real-world data in health monitoring and online YouTube video services show that our proposed algorithm is able to maximize the system throughput while guaranteeing the fraction of served users.

Dispatching Model in Online Taxi System by Using Stable Marriage and First Price Sealed Bid Auction Models

Dispatching Model in Online Taxi System by Using Stable Marriage and First Price Sealed Bid Auction Models

Reference Price Effects in First-price Private-value Auctions

External reference points, such as outside options or budget constraints, are common in bidding environments. We experimentally investigate the impact of external reference points for bidding in first-price auctions with independent private values. We find that the presence of a reference point distorts bidding behaviour. There are “reference price effects” consistent with a preference for certainty and anchoring bias. To establish robustness, we conduct a second experiment that controls for bidders’ first-order beliefs. After controlling for beliefs, the reference price effect dominates. We observe that the imposition of a ceiling on the opponent’s maximum bid set at the upper bound of the risk-neutral Nash equilibrium support is strong enough to reverse the well-documented pattern of overbidding in first-price auctions and indeed to induce significant underbidding. The findings inform on the implications of auction formats that involve reference points, and specifically buy-it-now price options that are common in internet auction listings.

Projection of Private Values in Auctions

We explore how taste projection—the tendency to overestimate how similar others’ tastes are to one’s own—affects bidding in auctions. In first-price auctions with private values, taste projection leads bidders to exaggerate the intensity of competition and, consequently, to overbid—irrespective of whether values are independent, affiliated, or (a)symmetric. Moreover, the optimal reserve price is lower than the rational benchmark, and decreasing in the extent of projection and the number of bidders. With an uncertain common-value component, projecting bidders draw distorted inferences about others’ information. This misinference is stronger in second-price and English auctions, reducing their allocative efficiency compared to first-price auctions. (JEL D11, D44, D82, D83)

Multi-armed bandits for bid shading in first-price real-time bidding auctions

Online advertisements are bought through a mechanism called real-time bidding (RTB). In RTB, the ads are auctioned in real-time on every webpage load. The ad auctions can be of two types: second-price or first-price auctions. In second-price auctions, the bidder with the highest bid wins the auction, but they only pay the second-highest bid. This paper focuses on first-price auctions, where the buyer pays the amount that they bid. This research evaluates how multi-armed bandit strategies optimize the bid size in a commercial demand-side platform (DSP) that buys inventory through ad exchanges. First, we analyze seven multi-armed bandit algorithms on two different offline real datasets gathered from real second-price auctions. Then, we test and compare the performance of three algorithms in a production environment. Our results show that real data from second-price auctions can be used successfully to model first-price auctions. Moreover, we found that the trained multi-armed bandit algorithms reduce the bidding costs considerably compared to the baseline (naïve approach) on average 29%and optimize the whole budget by slightly reducing the win rate (on average 7.7%). Our findings, tested in a real scenario, show a clear and substantial economic benefit for ad buyers using DSPs.

An Auction Bidding Approach to Balance Performance Bonuses in Vehicle Routing Problems with Time Windows

In the field of operations research, the vehicle routing problem with time windows (VRPTW) has been widely studied because it is extensively used in practical applications. Real-life situations discussed in the relevant research include time windows and vehicle capabilities. Among the constraints in a VRPTW, the practical consideration of the fairness of drivers’ performance bonuses has seldom been discussed in the literature. However, the shortest routes and balanced performance bonuses for all sales drivers are usually in conflict. To balance the bonuses awarded to all drivers, an auction bidding approach was developed to address this practical consideration. The fairness of performance bonuses was considered in the proposed mathematical model. The nearest urgent candidate heuristic used in the auction bidding approach determined the auction price of the sales drivers. The proposed algorithm both achieved a performance bonus balance and planned the shortest route for each driver. To evaluate the performance of the auction bidding approach, several test instances were generated based on VRPTW benchmark data instances. This study also involved sensitivity and scenario analyses to assess the effect of the algorithm’s parameters on the solutions. The results show that the proposed approach efficiently obtained the optimal routes and satisfied the practical concerns in the VRPTW.

“Now or Later?” When to Deploy Qualification Screening in Open-Bid Auction for Re-Sourcing

Designing Open-bid Procurement Auction with Supplier Qualification Screenings Manufacturers often use re-sourcing initiatives to keep their suppliers’ pricing competitive; e.g., new entrant suppliers are identified and invited to compete with the incumbent supplier for supply contracts in an open-bid auction. To ensure that entrant suppliers have the capability of executing the contract, the conventional approach for many manufacturers is to conduct qualification screenings on all the entrants prior to auction bidding and only allow qualified entrant suppliers to compete in the auction. In “‘Now or Later?’ When to Deploy Qualification Screening in Open-Bid Auction for Re-Sourcing”, Zhang, Chen, and Katok explore an alternative arrangement of this process where all entrant suppliers are invited for bidding first before qualification screenings are selectively conducted afterward to determine the contract winner. This new approach helps reduce the waste of manufacturers’ screening efforts on suppliers with uncompetitive bids but in the meantime introduces incentives for less competitive supplier bidding behavior. They provide analytical and numerical evidence that this new approach could be very effective in managing manufacturers’ procurement costs.

Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids

This study aims to plan a cost-minimizing charging schedule for electric buses with fast charging stations. The paper conceptualizes the problem as a three-stage procedure, which is oriented around the participation of an electric bus aggregator in a day-ahead energy auction. First, the aggregation stage determines the bid parameters of buses. With bid parameters, aggregated cost-minimizing charging plans are obtained in the second stage conceived as the hourly day-ahead auction. The disaggregation of hourly plans into feasible minutely charging schedules is the third stage. The main contribution is the formulation of mixed-integer linear programming aggregation models to determine charging availability expressed as minimum and maximum hourly energy requirements taking into account detailed, minutely characteristics and constraints of the charging equipment and the buses. No price forecasts are required, and the plans adjust to the wholesale prices of energy. Defining only a few aggregated bids parameters used in linear programming constraints and incorporating them into the auction model is another contributing factor of this paper, allowing the scheduling of storage-based participants economically. The proposed methodology has been verified on a recently published case study of a real-world bus service operated on the Ohio State University campus. We show that the auction-based charging of all 22 buses outperforms as-soon-as-possible schedules by 7% to even 28% of daily cost savings. Thanks to the aggregated bids, buses can flexibly shift charges between high- and low-price periods while preserving constraints of the charging equipment and timetables.

Shilling, Squeezing, Sniping. A further explanation for late bidding in online second-price auctions

Several studies provide empirical evidence for sniping (i.e., waiting until the last few seconds to bid) in second-price internet auctions, particularly in auctions at eBay. This evidence was regarded as puzzling and an anomaly for an extended period: How could sniping be consistent with rational behaviour in second-price auctions, where theory predicts that bids’ timing plays no role and there is no incentive to bid less than one’s private value.An essential contribution to this puzzling issue has been the insight by Bose and Daripa (2017) that late bidding is itself a response to the shilling. Their paper explains well late bidding for repeating auctions. However, late bidding also occurs in non-repeated auctions.This paper aims to show that bidders can expect shilling behaviour even in non-repeated auctions, i.e., when perishables are on the counter. For this, we introduce the notion of squeezing. It describes an upstream step to the shilling to substantially reduce the seller’s risk to become the highest bidder. We rationalize the aforementioned results for non-repeated auctions by considering the squeezing strategy.

서울지역 아파트의 경매낙찰가율에 영향을 미치는 요인에 관한 연구 - 시점수정 낙찰가율과 법원경매 낙찰가율에 미치는 영향요인에 대한 비교연구 -

Existing studies on the real estate auction market commonly use the auction successful bid price of court auction. However, there is a limitation on using the auction successful bid price rate as an indicator for real estate market participant's decision-making due to the time difference between the timing of appraisal and the date of pricing the auction bid. From this perspective, this study identified the factors affecting the auction successful bid price rate in the Seoul apartment auction market through comparative verification regarding the factors affecting both the time-adjusted auction successful bid price rate and that of the court auction. The results of the analysis are as follows. First, it was found that the rate of change in the actual transaction price index had a negative (-) effect on the corrected auction winning price rate, however, a significant positive (+) effect on the auction winning price rate of the court auction information. Second, it was found that trading volume, change rate of land price, and elapsed years, had a positive(+) effect on the auction winning price rate.

Auction theory and a note on game mechanisms

Abstract This paper will review important topics on the subject of auction theory and mechanism design, these include: efficiency first and foremost, also revenue comparison between different types of auctions and the issue of incentive compatibility, individual rationality with the general idea and proof that bilateral trade is inefficient. Mechanism design theory tells us that if buyers and sellers both have private information full efficiency is impossible, however Vickrey auction (single unit auction) will be efficient i.e. will put the goods in the hands of the buyers that value them most. However, the conclusion from this paper is that because of overvaluation of bidders the main result is inefficient, i.e. bids are too high. When weak and strong bidders are compared the main conclusion is that strong bidders’ expected payoff is higher in second price auction (SPA), while weak bidder prefers first price auction (FPA) bid.

Fairness and Efficiency in Online Advertising Mechanisms

Online advertising often involves targeting ads to certain types of consumers where ads are commonly sold by generalized second price auctions. However, such an auction or mechanism could be considered unfair if similar consumers are consistently shown different ads or consistently receive different payoffs. Results show that such ascending bid auctions may result in unfair treatment and additionally that uncertainty regarding an ad’s value can result in inefficiency. An alternative way to assign ads to consumers is presented called the random assignment mechanism. Results show that the random assignment can improve fairness while improving efficiency in some circumstances.