An Analysis of Intent-Based Markets

Abstract: Mechanisms for decentralized finance on blockchains suffer from various problems, including suboptimal price execution for users, latency, and a worse user experience compared to their centralized counterparts. Recently, off-chain marketplaces, colloquially called `intent markets,' have been proposed as a solution to these problems. In these markets, agents called \emph{solvers} compete to satisfy user orders, which may include complicated user-specified conditions. We provide two formal models of solvers' strategic behavior: one probabilistic and another deterministic. In our first model, solvers initially pay upfront costs to enter a Dutch auction to fill the user's order and then exert congestive, costly effort to search for prices for the user. Our results show that the costs incurred by solvers result in restricted entry in the market. Further, in the presence of costly effort and congestion, our results counter-intuitively show that a planner who aims to maximize user welfare may actually prefer to restrict entry, resulting in limited oligopoly. We then introduce an alternative, optimization-based deterministic model which corroborates these results. We conclude with extensions of our model to other auctions within blockchains and non-cryptocurrency applications, such as the US SEC's Proposal 615.

• The paper presents two models—probabilistic auction and deterministic optimization—to analyze solver behavior in intent-based markets.
• It shows that costly entry and congestion restrict market participation, which can paradoxically enhance user welfare under controlled conditions.
• The deterministic model offers a framework for parameterizing solver incentives and guiding the design of more efficient decentralized exchange mechanisms.

An Analysis of Intent-Based Markets

This paper provides a comprehensive analysis of intent-based markets, a proposed solution aimed at improving decentralized finance (DeFi) mechanisms on blockchains. The authors acknowledge that while decentralized exchanges (DEXs) have grown in popularity, they still face significant challenges compared to centralized exchanges (CEXs) such as suboptimal price execution, latency, and user experience inefficiencies. Intent markets have been suggested to address these issues by creating a platform where agents, termed solvers, compete to execute user orders under predefined conditions.

Overview and Models

The paper presents two formal models of strategic solver behavior: a probabilistic auction-theoretic model and a deterministic optimization-based model. In the probabilistic framework, solvers pay entry costs to participate in a Dutch auction, subsequently exerting costly effort to find prices. This setup aims to explore the impact of entry and congestion costs on market participation.

The paper's key findings indicate that the costs incurred by solvers result in restricted market entry. The authors demonstrate that under certain conditions with costly effort and congestion, limiting entry could paradoxically enhance user welfare by promoting a controlled oligopoly.

Detailed Findings and Implications

• Costly Entry and Effort: In markets where solvers face upfront entry costs, the equilibrium number of market participants is significantly reduced. The modeling shows that for exponentially and uniformly distributed solver prices, the solver entry remains minimal relative to potential entrants. For Pareto-distributed prices, while market entry is less restricted, significant bid shading limits user benefits.
• Congestive Costs: The paper establishes that costly effort linked to congestive market conditions can reduce user welfare. This conclusion suggests that entry limitation by a planner could be beneficial—in markets with severe congestion, fewer solvers might enhance user experience by focusing efforts more efficiently.
• Deterministic Model: The deterministic approach uses utility functions to model solver incentives, promising a framework that can be parameterized with empirical data. This leads to a mechanism analogous to a Dutch auction in achieving social welfare maximization and verifying if solvers offer true price improvements.

Practical and Theoretical Implications

Practically, the research highlights the importance of understanding solver costs when designing intent-based markets. Improved welfare outcomes hinge on striking a balance between allowing free entry and managing congestion costs. Theoretically, it underscores the need for judiciously orchestrated market structures, encouraging further exploration of hybrid models for multi-asset markets or correlated costs among solvers.

Future Directions

The paper suggests several avenues for future research, including extending these models to handle more complex market interactions across multiple assets and empirically estimating congestion costs for better market design. Additionally, insights from intent-based mechanisms could inform developments in non-cryptocurrency applications, such as proposed SEC market reforms and the evolution of proposer-builder separation in blockchain systems.

In conclusion, the paper provides a structured analysis of intent-based markets, emphasizing the nuanced interplay between entry costs, solver strategies, and user welfare. While offering a viable path to enhance DeFi experiences, the research calls for strategic market planning and iterative design adaptation to accommodate evolving financial landscapes.