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Repeated Bidding with Dynamic Value

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  • Benjamin Heymann
  • Alexandre Gilotte
  • R'emi Chan-Renous

Abstract

We consider a repeated auction where the buyer's utility for an item depends on the time that elapsed since his last purchase. We present an algorithm to build the optimal bidding policy, and then, because optimal might be impractical, we discuss the cost for the buyer of limiting himself to shading policies.

Suggested Citation

  • Benjamin Heymann & Alexandre Gilotte & R'emi Chan-Renous, 2023. "Repeated Bidding with Dynamic Value," Papers 2308.01755, arXiv.org.
    • Handle: RePEc:arx:papers:2308.01755
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    References listed on IDEAS

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    1. Navdeep S. Sahni, 2015. "Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 203-247, September.
    2. Navdeep S. Sahni, 2015. "Erratum to: Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 249-250, September.
    3. Navdeep Sahni, 2015. "Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 203-247, September.
    4. Navdeep Sahni, 2015. "Erratum to: Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 249-250, September.
    5. Hana Choi & Carl F. Mela & Santiago R. Balseiro & Adam Leary, 2020. "Online Display Advertising Markets: A Literature Review and Future Directions," Information Systems Research, INFORMS, vol. 31(2), pages 556-575, June.
    6. Michael Braun & Wendy W. Moe, 2013. "Online Display Advertising: Modeling the Effects of Multiple Creatives and Individual Impression Histories," Marketing Science, INFORMS, vol. 32(5), pages 753-767, September.
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