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Bidding Strategies for Simultaneous Ascending Auctions

Author

Listed:
  • Wellman Michael P

    (University of Michigan, wellman@umich.edu)

  • Osepayshvili Anna

    (University of Michigan, annaose@umich.edu)

  • MacKie-Mason Jeffrey K

    (University of Michigan, jmm@umich.edu)

  • Reeves Daniel

    (Yahoo! Research, dreeves@yahoo-inc.com)

Abstract

Simultaneous ascending auctions present agents with various strategic problems, depending on preference structure. As long as bids represent non-repudiable offers, submitting non-contingent bids to separate auctions entails an exposure problem: bidding to acquire a bundle risks the possibility of obtaining an undesired subset of the goods. With multiple goods (or units of a homogeneous good) bidders also need to account for their own effects on prices. Auction theory does not provide analytic solutions for optimal bidding strategies in the face of these problems. We present a new family of decision-theoretic bidding strategies that use probabilistic predictions of final prices: self-confirming distribution-prediction strategies. Bidding based on these is provably not optimal in general. But evidence using empirical game-theoretic methods we developed indicates the strategy is quite effective compared to other known methods when preferences exhibit complementarities. When preferences exhibit substitutability, simpler demand-reduction strategies address the own price effect problem more directly and perform better.

Suggested Citation

  • Wellman Michael P & Osepayshvili Anna & MacKie-Mason Jeffrey K & Reeves Daniel, 2008. "Bidding Strategies for Simultaneous Ascending Auctions," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 8(1), pages 1-43, December.
    • Handle: RePEc:bpj:bejtec:v:8:y:2008:i:1:n:27
    DOI: 10.2202/1935-1704.1461
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    References listed on IDEAS

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    Cited by:

    1. Wellman, Michael P. & Sodomka, Eric & Greenwald, Amy, 2017. "Self-confirming price-prediction strategies for simultaneous one-shot auctions," Games and Economic Behavior, Elsevier, vol. 102(C), pages 339-372.

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