Abstract

Research concerning various types of auctions, such as English auctions, Dutch auctions, highest-price sealed-bid auctions, and second-price sealed-bid auctions, is always a topic of considerable interest in interdisciplinary fields. The type of auction, known as a lowest unique bid auction (LUBA), has also attracted significant attention. Various models have been proposed, but they often fail to explain satisfactorily the real bid-distribution characteristics. This paper discusses LUBA bid-distribution characteristics, including the inverted-J shape and the exponential decrease in the upper region. The authors note that this type of distribution, which initially increases and later decreases, cannot be derived from the symmetric Nash equilibrium framework based on perfect information that has previously been used. A novel optimization model based on non-perfect information is presented. The kernel of this model is the premise that agents make decisions to achieve maximum profit based on imaginary information or assumptions regarding the behavior of others.

Highlights

  • Auctions, which represent a typical human economic behavior, have a long history: records indicate that auctions were held as early as 500 B.C., and they have evolved into various kinds of new auctions [1]

  • It is clear that players in lowest unique bid auction (LUBA) and lowest unique positive integer game (LUPI) are faced with the same strategic conflict in attempting to choose bids that are both low and unique [5]

  • Research concerning various types of auctions is a topic of considerable interest in various interdisciplinary fields of science

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Summary

Introduction

Auctions, which represent a typical human economic behavior, have a long history: records indicate that auctions were held as early as 500 B.C., and they have evolved into various kinds of new auctions [1]. If we suppose a bid probability distribution based on the symmetrical Nash equilibrium that contains an increasing regime, we can identify two points k1 < k2 such that the bid probability will be f(k1)

Results of varying parameters
Conclusions

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