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Optimal bidding in auctions of mixed populations of bidders

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  • Lorentziadis, Panos L.
Abstract
A mixed population of bidders consists of two asymmetric groups. Members of the first group are game-theoretic players, who maximize their expected profit and incorrectly believe that their opponents act similarly. The second group of bidders adopts an irrational strategy: they either choose their bids randomly following a given probability distribution, in a “naïve” form of bidding, or follow a decision-theoretic approach, maximizing their expected profit under the assumption that all other bids are random. In a sealed bid private-value procurement auction we examine the optimal strategy of a new player, who has perfect knowledge of the structure of the mixed bidder population and enters the auction. The optimal bid of the new bidder is derived when the cost and mark-up follow a uniform distribution in [0,1]. The effect of the relative size of the group of game-theoretic bidders and the population size on the optimal bid price is established.

Suggested Citation

  • Lorentziadis, Panos L., 2012. "Optimal bidding in auctions of mixed populations of bidders," European Journal of Operational Research, Elsevier, vol. 217(3), pages 653-663.
    • Handle: RePEc:eee:ejores:v:217:y:2012:i:3:p:653-663
    DOI: 10.1016/j.ejor.2011.07.047
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    References listed on IDEAS

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    3. Qunwei Wang & Cheng Cheng & Dequn Zhou, 2020. "Multi-round auctions in an emissions trading system considering firm bidding strategies and government regulations," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1403-1421, October.
    4. Romero Morales, Dolores & Steinberg, Richard, 2014. "Revenue deficiency under second-price auctions in a supply-chain setting," European Journal of Operational Research, Elsevier, vol. 233(1), pages 131-144.
    5. Wang, Chao & Guo, Peijun, 2017. "Behavioral models for first-price sealed-bid auctions with the one-shot decision theory," European Journal of Operational Research, Elsevier, vol. 261(3), pages 994-1000.
    6. Paulo Fagandini & Ingemar Dierickx, 2023. "Computing Profit-Maximizing Bid Shading Factors in First-Price Sealed-Bid Auctions," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1009-1035, March.

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