IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2102.08754.html
   My bibliography  Save this paper

A Regret Analysis of Bilateral Trade

Author

Listed:
  • Nicol`o Cesa-Bianchi

    (TSE)

  • Tommaso Cesari

    (TSE)

  • Roberto Colomboni

    (IIT)

  • Federico Fusco
  • Stefano Leonardi

Abstract

Bilateral trade, a fundamental topic in economics, models the problem of intermediating between two strategic agents, a seller and a buyer, willing to trade a good for which they hold private valuations. Despite the simplicity of this problem, a classical result by Myerson and Satterthwaite (1983) affirms the impossibility of designing a mechanism which is simultaneously efficient, incentive compatible, individually rational, and budget balanced. This impossibility result fostered an intense investigation of meaningful trade-offs between these desired properties. Much work has focused on approximately efficient fixed-price mechanisms, i.e., Blumrosen and Dobzinski (2014; 2016), Colini-Baldeschi et al. (2016), which have been shown to fully characterize strong budget balanced and ex-post individually rational direct revelation mechanisms. All these results, however, either assume some knowledge on the priors of the seller/buyer valuations, or a black box access to some samples of the distributions, as in D{\"u}tting et al. (2021). In this paper, we cast for the first time the bilateral trade problem in a regret minimization framework over rounds of seller/buyer interactions, with no prior knowledge on the private seller/buyer valuations. Our main contribution is a complete characterization of the regret regimes for fixed-price mechanisms with different models of feedback and private valuations, using as benchmark the best fixed price in hindsight. More precisely, we prove the following bounds on the regret: $\bullet$ $\widetilde{\Theta}(\sqrt{T})$ for full-feedback (i.e., direct revelation mechanisms); $\bullet$ $\widetilde{\Theta}(T^{2/3})$ for realistic feedback (i.e., posted-price mechanisms) and independent seller/buyer valuations with bounded densities; $\bullet$ $\Theta(T)$ for realistic feedback and seller/buyer valuations with bounded densities; $\bullet$ $\Theta(T)$ for realistic feedback and independent seller/buyer valuations; $\bullet$ $\Theta(T)$ for the adversarial setting.

Suggested Citation

  • Nicol`o Cesa-Bianchi & Tommaso Cesari & Roberto Colomboni & Federico Fusco & Stefano Leonardi, 2021. "A Regret Analysis of Bilateral Trade," Papers 2102.08754, arXiv.org.
  • Handle: RePEc:arx:papers:2102.08754
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2102.08754
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nicolò Cesa-Bianchi & Gábor Lugosi & Gilles Stoltz, 2006. "Regret Minimization Under Partial Monitoring," Mathematics of Operations Research, INFORMS, vol. 31(3), pages 562-580, August.
    2. Maxime C. Cohen & Ilan Lobel & Renato Paes Leme, 2020. "Feature-Based Dynamic Pricing," Management Science, INFORMS, vol. 66(11), pages 4921-4943, November.
    3. William Vickrey, 1961. "Counterspeculation, Auctions, And Competitive Sealed Tenders," Journal of Finance, American Finance Association, vol. 16(1), pages 8-37, March.
    4. Myerson, Roger B. & Satterthwaite, Mark A., 1983. "Efficient mechanisms for bilateral trading," Journal of Economic Theory, Elsevier, vol. 29(2), pages 265-281, April.
    5. Josef Broder & Paat Rusmevichientong, 2012. "Dynamic Pricing Under a General Parametric Choice Model," Operations Research, INFORMS, vol. 60(4), pages 965-980, August.
    6. Devanur, Nikhil R. & Peres, Yuval & Sivan, Balasubramanian, 2019. "Perfect Bayesian Equilibria in repeated sales," Games and Economic Behavior, Elsevier, vol. 118(C), pages 570-588.
    7. Gábor Bartók & Dean P. Foster & Dávid Pál & Alexander Rakhlin & Csaba Szepesvári, 2014. "Partial Monitoring---Classification, Regret Bounds, and Algorithms," Mathematics of Operations Research, INFORMS, vol. 39(4), pages 967-997, November.
    8. Arnoud V. den Boer & N. Bora Keskin, 2020. "Discontinuous Demand Functions: Estimation and Pricing," Management Science, INFORMS, vol. 66(10), pages 4516-4534, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nicol`o Cesa-Bianchi & Tommaso Cesari & Roberto Colomboni & Federico Fusco & Stefano Leonardi, 2021. "Bilateral Trade: A Regret Minimization Perspective," Papers 2109.12974, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nicol`o Cesa-Bianchi & Tommaso Cesari & Roberto Colomboni & Federico Fusco & Stefano Leonardi, 2021. "Bilateral Trade: A Regret Minimization Perspective," Papers 2109.12974, arXiv.org.
    2. Lau, Stephanie, 2011. "Investment incentives in bilateral trading," Games and Economic Behavior, Elsevier, vol. 73(2), pages 538-552.
    3. Scott Fay & Robert Zeithammer, 2017. "Bidding for Bidders? How the Format for Soliciting Supplier Participation in NYOP Auctions Impacts Channel Profit," Management Science, INFORMS, vol. 63(12), pages 4324-4344, December.
    4. Tafreshian, Amirmahdi & Masoud, Neda, 2022. "A truthful subsidy scheme for a peer-to-peer ridesharing market with incomplete information," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 130-161.
    5. Kos, Nenad & Messner, Matthias, 2013. "Extremal incentive compatible transfers," Journal of Economic Theory, Elsevier, vol. 148(1), pages 134-164.
    6. Loertscher, Simon & Mezzetti, Claudio, 2021. "A dominant strategy, double clock auction with estimation-based tatonnement," Theoretical Economics, Econometric Society, vol. 16(3), July.
    7. David C. Parkes & Jayant Kalagnanam, 2005. "Models for Iterative Multiattribute Procurement Auctions," Management Science, INFORMS, vol. 51(3), pages 435-451, March.
    8. Dütting, Paul & Talgam-Cohen, Inbal & Roughgarden, Tim, 2017. "Modularity and greed in double auctions," LSE Research Online Documents on Economics 83199, London School of Economics and Political Science, LSE Library.
    9. Hamsa Bastani & David Simchi-Levi & Ruihao Zhu, 2022. "Meta Dynamic Pricing: Transfer Learning Across Experiments," Management Science, INFORMS, vol. 68(3), pages 1865-1881, March.
    10. Song, Yangwei, 2018. "Efficient Implementation with Interdependent Valuations and Maxmin Agents," Rationality and Competition Discussion Paper Series 92, CRC TRR 190 Rationality and Competition.
    11. Jesse A. Schwartz & Quan Wen, 2008. "A Revelation Principle for Dominant Strategy Implementation," Vanderbilt University Department of Economics Working Papers 0819, Vanderbilt University Department of Economics.
    12. Kazumura, Tomoya & Mishra, Debasis & Serizawa, Shigehiro, 2020. "Mechanism design without quasilinearity," Theoretical Economics, Econometric Society, vol. 15(2), May.
    13. Xuejun Zhao & Ruihao Zhu & William B. Haskell, 2022. "Learning to Price Supply Chain Contracts against a Learning Retailer," Papers 2211.04586, arXiv.org.
    14. Loertscher, Simon & Marx, Leslie M., 2020. "A dominant-strategy asset market mechanism," Games and Economic Behavior, Elsevier, vol. 120(C), pages 1-15.
    15. Philippe Jehiel & Laurent Lamy, 2018. "A Mechanism Design Approach to the Tiebout Hypothesis," Journal of Political Economy, University of Chicago Press, vol. 126(2), pages 735-760.
    16. repec:cte:werepe:we081207 is not listed on IDEAS
    17. Yoon, Kiho, 2008. "The participatory Vickrey-Clarke-Groves mechanism," Journal of Mathematical Economics, Elsevier, vol. 44(3-4), pages 324-336, February.
    18. Matsushima, Hitoshi & Noda, Shunya, 2023. "Mechanism design with general ex-ante investments," Journal of Mathematical Economics, Elsevier, vol. 106(C).
    19. Schnizler, Bjorn & Neumann, Dirk & Veit, Daniel & Weinhardt, Christof, 2008. "Trading grid services - a multi-attribute combinatorial approach," European Journal of Operational Research, Elsevier, vol. 187(3), pages 943-961, June.
    20. Samuel Antill & Darrell Duffie, 2021. "Augmenting Markets with Mechanisms [Optimal Execution of Portfolio Transactions]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 1665-1719.
    21. M. Yenmez, 2015. "Incentive compatible market design with applications," International Journal of Game Theory, Springer;Game Theory Society, vol. 44(3), pages 543-569, August.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2102.08754. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.