Dynamic Double Auctions: Toward First Best

40 Pages Posted: 3 Aug 2018 Last revised: 18 May 2021

See all articles by Santiago Balseiro

Santiago Balseiro

Columbia University - Columbia Business School, Decision Risk and Operations; Google Research

Vahab Mirrokni

Google Research

Renato Paes Leme

Google Inc.

Song Zuo

Google Research

Date Written: July 19, 2019

Abstract

We study the problem of designing dynamic double auctions for two-sided markets in which a platform intermediates the trade between one seller offering independent items to multiple buyers, repeatedly over a finite horizon, when agents have private values. Motivated by online platforms for advertising, ride-sharing, and freelancing markets, we seek to design mechanisms satisfying the following properties: no positive transfers, i.e., the platform never asks the seller to make payments nor are buyers ever paid and periodic individual rationality, i.e., every agent derives a non-negative utility from every trade opportunity. We provide mechanisms satisfying these requirements that are asymptotically efficient and budget-balanced with high probability as the number of trading opportunities grows. Moreover, we show that the average expected profit obtained by the platform under these mechanisms asymptotically approaches first best (the maximum possible welfare generated by the market). We also extend our approach to general environments with complex, combinatorial preferences.

Keywords: double auctions, two-sided markets, dynamic mechanism design, revenue management

Suggested Citation

Balseiro, Santiago and Mirrokni, Vahab and Paes Leme, Renato and Zuo, Song, Dynamic Double Auctions: Toward First Best (July 19, 2019). Columbia Business School Research Paper No. 18-64, Available at SSRN: https://ssrn.com/abstract=3213460 or http://dx.doi.org/10.2139/ssrn.3213460

Santiago Balseiro (Contact Author)

Columbia University - Columbia Business School, Decision Risk and Operations ( email )

3022 Broadway
New York, NY 10027
United States

Google Research ( email )

Vahab Mirrokni

Google Research ( email )

Renato Paes Leme

Google Inc. ( email )

1600 Amphitheatre Parkway
Second Floor
Mountain View, CA 94043
United States

Song Zuo

Google Research ( email )

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