Decentralized Trading Networks: Equilibria and Fairness

2026-02-24

AI Summary

This study investigates the inherent tension between stability and fairness in decentralized bilateral contract trading networks, with a focus on the inequitable utility allocation among agents under core-stable outcomes. Employing a trading network game framework, the analysis integrates Nash and competitive equilibrium concepts, bidding dynamics, and a stochastic price-clock market model to demonstrate that non-essential agents necessarily receive zero utility in the core, while even essential agents may also obtain zero utility. The main contributions include proving that a class of Nash equilibria can be supported as competitive equilibria, establishing novel convergence results for dynamic mechanisms toward equilibrium, and rigorously characterizing the theoretical limits of fairness within core solutions—thereby deepening the understanding of fairness constraints in decentralized markets.

Technology Category

• Game Theory and Economic Paradigms: Fair Division
• Multiagent Systems: Mechanism Design
• Reasoning under Uncertainty: Decision/Utility Theory

Application Category

• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments
• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

We explore stability and fairness considerations in decentralized networked markets with bilateral contracts, building on the trading networks framework [Hatfield et al., 2013]. In our trading network game, we show that a well-defined subset of Nash equilibria can be supported as competitive equilibria. Considering an offer-based trading dynamic as well as a stochastic price clock market, we prove new convergence results to Nash equilibrium and competitive equilibrium, providing a rationale for stability properties in decentralized, dynamic trading networks. Turning to the tension between fairness and (core) stability, we prove several negative results: inessential agents always receive zero utility in any core outcome, and even essential agents can get zero utility in all core outcomes.

Problem

• decentralized trading networks
• fairness
• stability
• core outcomes
• Nash equilibrium

Innovation

• decentralized trading networks
• competitive equilibrium
• Nash equilibrium convergence
• fairness-stability tradeoff
• core outcomes