Dynamic Double Auctions: Toward First Best

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