February 12, 2001
Models of auctions or tendering processes are introduced. In every round of bidding the players select their bid from a probability distribution and whenever a bid is unsuccessful, it is discarded and replaced. For simple models, the probability distributions evolve to a stationary power law with the exponent dependent only on the number of players. For most situations, the system converges towards a state where all players are identical. A number of variations of this model are introduced and the application of these models to the dynamics of market makers is discussed. The effect of price uncertainty on bid distributions is presented. An underlying market structure generates heterogenous agents which do not have power law bid distribution in general.
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August 24, 2006
We characterize the statistical properties of a large number of online auctions run on eBay. Both stationary and dynamic properties, like distributions of prices, number of bids etc., as well as relations between these quantities are studied. The analysis of the data reveals surprisingly simple distributions and relations, typically of power-law form. Based on these findings we introduce a simple method to identify suspicious auctions that could be influenced by a form of fra...
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We characterize the statistical properties of a large number of agents on two major online auction sites. The measurements indicate that the total number of bids placed in a single category and the number of distinct auctions frequented by a given agent follow power-law distributions, implying that a few agents are responsible for a significant fraction of the total bidding activity on the online market. We find that these agents exert an un-proportional influence on the fina...
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Online auctions have expanded rapidly over the last decade and have become a fascinating new type of business or commercial transaction in this digital era. Here we introduce a master equation for the bidding process that takes place in online auctions. We find that the number of distinct bidders who bid $k$ times, called the $k$-frequent bidder, up to the $t$-th bidding progresses as $n_k(t)\sim tk^{-2.4}$. The successfully transmitted bidding rate by the $k$-frequent bidder...
May 3, 2011
Information technology has revolutionized the traditional structure of markets. The removal of geographical and time constraints has fostered the growth of online auction markets, which now include millions of economic agents worldwide and annual transaction volumes in the billions of dollars. Here, we analyze bid histories of a little studied type of online auctions --- lowest unique bid auctions. Similarly to what has been reported for foraging animals searching for scarce ...
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In lowest unique bid auctions, $N$ players bid for an item. The winner is whoever places the \emph{lowest} bid, provided that it is also unique. We use a grand canonical approach to derive an analytical expression for the equilibrium distribution of strategies. We then study the properties of the solution as a function of the mean number of players, and compare them with a large dataset of internet auctions. The theory agrees with the data with striking accuracy for small pop...
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The goal of an auction is to determine commodity prices such that all participants are perfectly happy. Such a solution is called a competitive equilibrium and does not exist in general. For this reason we are interested in solutions which are similar to a competitive equilibrium. The article introduces two relaxations of a competitive equilibrium for general auctions. Both relaxations determine one price per commodity by solving a difficult non-convex optimization problem. T...
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The dynamics of financial markets are driven by the interactions between participants, as well as the trading mechanisms and regulatory frameworks that govern these interactions. Decision-makers would rather not ignore the impact of other participants on these dynamics and should employ tools and models that take this into account. To this end, we demonstrate the efficacy of applying opponent-modeling in a number of simulated market settings. While our simulations are simplif...
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We develop extensions to auction theory results that are useful in real life scenarios. 1. Since valuations are generally positive we first develop approximations using the log-normal distribution. This would be useful for many finance related auction settings since asset prices are usually non-negative. 2. We formulate a positive symmetric discrete distribution, which is likely to be followed by the total number of auction participants, and incorporate this into auction ...
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