Automated Market Making for Goods with Perishable Utility

2025-11-20

AI Summary

This paper addresses challenges in decentralized markets for time-sensitive utility commodities—such as hourly-billed compute resources—including inefficient price discovery, high transaction latency, and insufficient supply-side incentives, all stemming from temporal utility decay. To tackle these issues, we propose a time-indexed capacity-based automated market maker (AMM) mechanism. Our contributions are threefold: (1) a load-driven concave pricing model that decouples price discovery from resource allocation; (2) a premium-sharing pool coupled with a “Cheapest Feasible Matching” (CFM) algorithm, which incentivizes early and full capacity staking as well as truthful cost reporting by suppliers; and (3) verifiable execution combined with dynamic supply analysis to ensure market clearing. We theoretically establish the existence and uniqueness of equilibrium quotes, and prove that CFM achieves bounded regret under mild assumptions, asymptotically approaching the optimal benchmark performance.

Technology Category

• Multiagent Systems: Mechanism Design
• Search and Optimization: Distributed Search
• Game Theory and Economic Paradigms: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Security and Privacy: Data transparency and provenance

Abstract

We study decentralized markets for goods whose utility perishes in time, with compute as a primary motivation. Recent advances in reproducible and verifiable execution allow jobs to pause, verify, and resume across heterogeneous hardware, which allow us to treat compute as time indexed capacity rather than bespoke bundles. We design an automated market maker (AMM) that posts an hourly price as a concave function of load--the ratio of current demand to a "floor supply" (providers willing to work at a preset floor). This mechanism decouples price discovery from allocation and yields transparent, low latency trading. We establish existence and uniqueness of equilibrium quotes and give conditions under which the equilibrium is admissible (i.e. active supply weakly exceeds demand). To align incentives, we pair a premium sharing pool (base cost plus a pro rata share of contemporaneous surplus) with a Cheapest Feasible Matching (CFM) rule; under mild assumptions, providers optimally stake early and fully while truthfully report costs. Despite being simple and computationally efficient, we show that CFM attains bounded worst case regret relative to an optimal benchmark.

Problem

• Designing automated market makers for perishable utility goods like compute capacity
• Establishing equilibrium conditions for transparent low latency trading mechanisms
• Aligning provider incentives through premium sharing and cheapest feasible matching

Innovation

• AMM uses concave price function of load
• Premium sharing pool with Cheapest Feasible Matching
• Decouples price discovery from allocation mechanism