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<p>This paper detects bidding behaviors in an auction with the random cutoff, where a winning bid needs to be above and the closest to the random cutoff. In this auction, each bidder is eager to predict the random cutoff in order to use the predicted random cutoff as bid. This paper investigates the symmetric and asymmetric bidding strategies in this auction. Furthermore, under the asymmetric bidding strategy, one of deep learning models, the transformer model is used to forecast the random cutoff. The result shows that the predicted random cutoff turns out to be a winner with probability of about 13 percent. This paper contributes to economic literature in terms of investigating the connection between a deep learning model and an auction based on the economic theory.</p>

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Competitive Bidding Strategy in an Auction with Random Cutoff - Randomness is Always Unpredictable?

  • 期刊论文

  • 发表日期：

    2025年10月9日

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  • Jin Hyung Lee

摘要

This paper detects bidding behaviors in an auction with the random cutoff, where a winning bid needs to be above and the closest to the random cutoff. In this auction, each bidder is eager to predict the random cutoff in order to use the predicted random cutoff as bid. This paper investigates the symmetric and asymmetric bidding strategies in this auction. Furthermore, under the asymmetric bidding strategy, one of deep learning models, the transformer model is used to forecast the random cutoff. The result shows that the predicted random cutoff turns out to be a winner with probability of about 13 percent. This paper contributes to economic literature in terms of investigating the connection between a deep learning model and an auction based on the economic theory.