Real-time Bidding for Time Constrained Impression Contracts in First and Second Price Auctions - Theory and Algorithms

We study the optimal bids and allocations in a real-time auction for heterogeneous items subject to the requirement that specified collections of items of given types be acquired within given time constraints. The problem is cast as a continuous time optimization problem that can, under certain weak assumptions, be reduced to a convex optimization problem. Focusing on the standard first and second price auctions, we first show, using convex duality, that the optimal (infinite dimensional) bidding policy can be represented by a single finite vector of so-called ''pseudo-bids''. Using this result we are able to show that the optimal solution in the second price case turns out to be a very simple piecewise constant function of time. This contrasts with the first price case that is more complicated. Despite the fact that the optimal solution for the first price auction is genuinely dynamic, we show that there remains a close connection between the two cases and that, empirically, there is almost no difference between optimal behavior in either setting. This suggests that it is adequate to bid in a first price auction as if it were in fact second price. Finally, we detail methods for implementing our bidding policies in practice with further numerical simulations illustrating the performance.

Publicly Verifiable M + 1st-Price Auction Fit for IoT with Minimum Storage

In an M + 1 st-price auction, all bidders submit their bids simultaneously, and the M highest bidders purchase M identical goods at the M + 1 st bidding price. Previous research is constructed based on trusted managers such as a trusted third party (TTP), trusted mix servers, and honest managers. All of the previous auctions are not fit for edge-assisted IoT since they need TTP. In this paper, we formalize a notion of commutative bi-homomorphic multiparty encryption and achieve no-TTP M + 1 -st auction based on blockchain with public verifiability. Our M + 1 st auction guarantees financial fairness, robustness, and correctness without TTP and is secure under a malicious model for the first time. Our M + 1 st auction can be executed over a distributed network and is thus fit for edge-assisted IoT. Furthermore, our formalized commutative bi-homomorphic multiparty encryption can be used in various applications for edge-assisted IoT, which needs to protect privacy and correctness.

Measurement of Collusion in Open Ascending Price Auctions in Agricultural Commodity Markets

This paper derives a method of measuring the degree of collusion among the bidders in an open ascending repetitive price auction in agricultural commodity markets in India. This paper first derives the bidders’ behaviour’s theoretical structure and then a measure of collusion formation. Finally, the degree of the cartel has been computed using time series wholesale price data of potato and onion crops. This research’s findings are helpful for the study of the link between the supply of the agriculture commodity and the degree of collusion. Using the proposed method in this research, if the Agricultural Produce Market Committee (APMC) measures cartel for each market and publish periodically, it will help farmers choose the right market to sell the produce. The farmers would select the market where the degree of collusion is relatively lower. Identifying different small cartel groups at different times with respective to the supply of the agriculture commodity would help avoid the incidence of distress selling by farmers, which is the main hindrance in developing the farming community in India. JEL Classification: C7,D44,L1,L4,Q1

An Empirical Study on Forecasting Production and Price of Tea in India

Tea is a very indispensable beverage for Indian population as we rank the world’s largest consumer of black tea. Indian tea industry had been facing many downfalls for the past few years in terms of low price, excess supply, losing flavour and all this as a whole had affected the performance of the tea industry in India. With India being the second largest producer of tea globally, the production of tea in India can be subdivided into North India and South India. The current study focuses on the comparative analysis between North India, South India and India in terms of their trends in area, production, yield, export quantity, export price, auction price and auction quantity of tea. Compounded Annual growth rate (CAGR) was the tool used to find the trends of various variables. This study also focuses on the forecasting the production and auction prices of tea in India till 2023using Autoregressive Integrated Moving Average (ARIMA) model. The results of the present study areindicating that all the variables like area, production, yield, export quantity, export price, auction price and auction quantity of tea had shown a positive trend annually, except for that of North India’s export quantity. Production and auction prices were forecasted till 2023 using different ARIMA models amongst which ARIMA (1,1,0) proved to be the best fit model for study period.

Fast Core Pricing for Rich Advertising Auctions

Standard ad auction formats do not immediately extend to settings where multiple size configurations and layouts are available to advertisers. In these settings, the sale of web advertising space increasingly resembles a combinatorial auction with complementarities, where truthful auctions such as the Vickrey–Clarke–Groves (VCG) auction can yield unacceptably low revenue. In “Fast Core Pricing for Rich Advertising Auctions,” Niazadeh, Hartline, Immorlica, Khani, and Lucier study and suggest core-selecting auctions, which boost revenue by setting payments so that no group of agents, including the auctioneer, can jointly improve their utilities by switching to a different outcome. Their main result is a combinatorial algorithm that finds an approximate bidder-optimal core point with an almost linear number of calls to the welfare-maximization oracle. This algorithm is faster than previously proposed heuristics in the literature and has theoretical guarantees. By accompanying the theoretical study with an experimental study based on Microsoft Bing Ad Auction data, the authors conclude that core pricing is implementable even for very time-sensitive practical use cases such as real-time online advertising and can yield more revenue than the VCG or generalized second price auction.

Leveling the Playing Field for Risk-Averse Agents in Security-Bid Auctions

We introduce risk-averse bidders in a security-bid auction to analyze how the security design affects bidders’ equilibrium behavior and, as a result, the revenue and efficiency of the auction. We show that steeper securities provide more insurance because they allow bidders to smooth payoffs across realizations. Such insurance levels the playing field for more-risk-averse bidders, inducing them to bid more aggressively. As a consequence, the auction’s allocative efficiency weakly increases when the seller switches from a flatter to a steeper security. Furthermore, we prove that when bidders are homogeneously and sufficiently risk averse, the only security that guarantees Pareto efficiency is the steepest, that is, a call option. We also determine the relationship between the security design and the auction format. In particular, we show that for convex and superconvex families of securities, the first-price auction yields higher expected revenues, provided a technical condition, whereas for subconvex families, the second price yields higher expected revenues, provided that bidders are moderately risk averse. Finally, we show that steeper securities also attract higher entry from an ex ante perspective, when entry is costly, and discuss the effects that the presence of risk aversion has on informal auctions. This paper was accepted by Gustavo Manso, finance.

A First-Price Sealed-Bid Asymmetric Auction When Two Bidders Have Respective CRRA and General Utility Functions

We study a first-price auction with two bidders where one bidder is characterized by a constant relative risk aversion utility function (i.e., a concave power function) while the other has a general concave utility function. We establish the existence and uniqueness of the optimal strategic markups and analyze the effects of one bidder’s risk aversion level on the optimal strategic markups of him and his opponent’s, the allocative efficiency of the auction, and the seller’s expected revenue, respectively.

Impacts of hub nodes on the spread of Name-Your-Own-Price auction

In the Name-Your-Own-Price (NYOP) auction, the spread of bidding information among buyers is incredibly important for both buyers and sellers. However, the impact of hub nodes on the spread of bidding information is less investigated. In this research, we proposed a directed distance index, and used it to explore the roles of hub nodes during an NYOP auction. The results showed significant impacts of hub nodes on buyers’ behaviors and seller profits, but the impacts highly depend on the fading speed of information. When information fades fast, the hub nodes should be more valued to increase buyers’ bidding intention and make them bid more wisely. Seller’s profits will also be increased. While information fades slow, the hub nodes and the regular nodes should be approximately valued. Moreover, we explored the case of sharing failed bids, and found that the roles of hub nodes become more salient when buyers are more willing to share the failed bids.

EXPRESS: First-Price Auctions in Online Display Advertising

We link the rapid and dramatic move from second-price to first-price auction format in the display advertising market to the move from the waterfalling mechanism employed by publishers for soliciting bids in a pre-ordered cascade over exchanges, to an alternate header bidding strategy that broadcasts the request for bid to all exchanges simultaneously. First, we argue that the move by the publishers from waterfalling to header bidding was a revenue improving move for publishers in the old regime when exchanges employed second-price auctions. Given the publisher move to header bidding, we show that exchanges move from second-price to first-price auctions to increase their expected clearing prices. Interestingly, when all exchanges move to first-price auctions, each exchange faces stronger competition from other exchanges and some exchanges may end up with lower revenue than when all exchanges use second-price auctions; yet, all exchanges move to first-price auctions in the unique equilibrium of the game. We show that the new regime hinders the exchanges’ ability to differentiate in equilibrium. Furthermore, it allows the publishers to achieve the revenue of the optimal mechanism despite not having direct access to the advertisers.