A Regret Analysis of Bilateral Trade
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Abstract (arXiv)
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"utting 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 widetildeTheta(√T) for full-feedback (i.e., direct revelation mechanisms); bullet widetildeTheta(T2/3) 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.
Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 17 of its 49 references that are in the map. First posted on arXiv 16 Feb 2021.
Builds on
17 of 49 references.
References · 17
- 2019Introduction to Multi-Armed Banditscited by 475
- 2013Bandits with Knapsackscited by 163
- 2014Bandits with concave rewards and convex knapsackscited by 83
- 2015The Sample Complexity of Revenue Maximizationcited by 48
- 2013Learning Prices for Repeated Auctions with Strategic Buyerscited by 37
- 2016Sample Complexity of Automated Mechanism Designcited by 24
- 2015Learning in Auctions: Regret is Hard, Envy is Easycited by 23
- 2018Dynamic Pricing with Finitely Many Unknown Valuationscited by 23
- 2020Efficient Two-Sided Markets with Limited Informationcited by 14
- 2017Approximating Gains from Trade in Two-sided Markets via Simple Mechanismscited by 11
- 2015Learning and Efficiency in Games with Dynamic Populationcited by 9
- 2016(Almost) Efficient Mechanisms for Bilateral Tradingcited by 8
5 more
- 2017Multi-scale Online Learning and its Applications to Online Auctionscited by 8
- 2017Fixed Price Approximability of the Optimal Gain From Tradecited by 8
- 2014Reallocation Mechanismscited by 6
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Citing papers per year: 2021: 1; 2022: 3; 2023: 6; 2024: 4; 2025: 2; 2026: 3.
19 papers.
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- 2021Bilateral Trade: A Regret Minimization Perspectivecited by 29
- 2023No-Regret Learning in Bilateral Trade via Global Budget Balancecited by 17
- 2022An α-regret analysis of Adversarial Bilateral Tradecited by 16
- 2023Repeated Bilateral Trade Against a Smoothed Adversarycited by 15
- 2023The Role of Transparency in Repeated First-Price Auctions with Unknown Valuationscited by 15
- 2023An Online Learning Theory of Brokeragecited by 8
- 2024Fair Online Bilateral Tradecited by 4
- 2024A Parametric Contextual Online Learning Theory of Brokeragecited by 4
- 2024Market Making without Regretcited by 4
- 2023Learning Thresholds with Latent Values and Censored Feedbackcited by 3
- 2023Adaptive maximization of social welfarecited by 2
- 2025A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokeragecited by 2
7 more
- 2026The Sample Complexity of Uniform Approximation for Multi-Dimensional CDFs and Fixed-Price Mechanismscited by 2
- 2025Markets with Heterogeneous Agents: Dynamics and Survival of Bayesian vs. No-Regret Learnerscited by 1
- 2022An Application of Online Learning to Spacecraft Memory Dump Optimizationcited by 0
- 2022Double Auctions with Two-sided Bandit Feedbackcited by 0
- 2024Trading Volume Maximization with Online Learningcited by 0
- 2026Regret Minimization in Bilateral Trade With Perturbed Marketscited by 0
- 2026Breaking the T3/4 Barrier for Regret Minimization With Bi-Dimensional CDFscited by 0
- 2026Breaking the T3/4 Barrier for Regret Minimization With Bi-Dimensional CDFs22 Jul 2026
- 2026Regret Minimization in Bilateral Trade With Perturbed Markets11 May 2026
- 2026The Sample Complexity of Uniform Approximation for Multi-Dimensional CDFs and Fixed-Price Mechanisms11 Feb 2026
- 2025A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokerage3 Mar 2025
- 2025Markets with Heterogeneous Agents: Dynamics and Survival of Bayesian vs. No-Regret Learners12 Feb 2025
- 2024Market Making without Regret21 Nov 2024
- 2024A Parametric Contextual Online Learning Theory of Brokerage22 May 2024
- 2024Fair Online Bilateral Trade22 May 2024
- 2024Trading Volume Maximization with Online Learning21 May 2024
- 2023Learning Thresholds with Latent Values and Censored Feedback7 Dec 2023
- 2023No-Regret Learning in Bilateral Trade via Global Budget Balance18 Oct 2023
- 2023An Online Learning Theory of Brokerage18 Oct 2023
7 more
- 2023Adaptive maximization of social welfare14 Oct 2023
- 2023The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations14 Jul 2023
- 2023Repeated Bilateral Trade Against a Smoothed Adversary21 Feb 2023
- 2022An α-regret analysis of Adversarial Bilateral Trade13 Oct 2022
- 2022Double Auctions with Two-sided Bandit Feedback13 Aug 2022
- 2022An Application of Online Learning to Spacecraft Memory Dump Optimization14 Feb 2022
- 2021Bilateral Trade: A Regret Minimization Perspective8 Sep 2021
- 2021Bilateral Trade: A Regret Minimization Perspectivecited by 29
- 2023No-Regret Learning in Bilateral Trade via Global Budget Balancecited by 17
- 2022An α-regret analysis of Adversarial Bilateral Tradecited by 16
- 2023Repeated Bilateral Trade Against a Smoothed Adversarycited by 15
- 2023The Role of Transparency in Repeated First-Price Auctions with Unknown Valuationscited by 15
- 2023An Online Learning Theory of Brokeragecited by 8
- 2024Fair Online Bilateral Tradecited by 4
- 2024A Parametric Contextual Online Learning Theory of Brokeragecited by 4
- 2024Market Making without Regretcited by 4
- 2023Learning Thresholds with Latent Values and Censored Feedbackcited by 3
- 2023Adaptive maximization of social welfarecited by 2
- 2025A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokeragecited by 2
12 most cited of 19 All 19 (JSON)
- 2026Breaking the T3/4 Barrier for Regret Minimization With Bi-Dimensional CDFs22 Jul 2026
- 2026Regret Minimization in Bilateral Trade With Perturbed Markets11 May 2026
- 2026The Sample Complexity of Uniform Approximation for Multi-Dimensional CDFs and Fixed-Price Mechanisms11 Feb 2026
- 2025A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokerage3 Mar 2025
- 2025Markets with Heterogeneous Agents: Dynamics and Survival of Bayesian vs. No-Regret Learners12 Feb 2025
- 2024Market Making without Regret21 Nov 2024
- 2024A Parametric Contextual Online Learning Theory of Brokerage22 May 2024
- 2024Fair Online Bilateral Trade22 May 2024
- 2024Trading Volume Maximization with Online Learning21 May 2024
- 2023Learning Thresholds with Latent Values and Censored Feedback7 Dec 2023
- 2023No-Regret Learning in Bilateral Trade via Global Budget Balance18 Oct 2023
- 2023An Online Learning Theory of Brokerage18 Oct 2023
12 newest of 19 All 19 (JSON)