Trading in CEXs and DEXs with Priority Fees and Stochastic Delays

Paper: arXiv 2602.10798

Authors: Philippe Bergault, Yadh Hafsi, Leandro Sánchez-Betancourt

Abstract

We develop a mixed control framework that combines absolutely continuous controls with impulse interventions subject to stochastic execution delays. The model extends current impulse control formulations by allowing (i) the controller to choose the mean of the stochastic delay of their impulses, and allowing (ii) for multiple pending orders, so that several impulses can be submitted and executed asynchronously at random times. The framework is motivated by an optimal trading problem between centralized (CEX) and decentralized (DEX) exchanges. In DEXs, traders control the distribution of the execution delay through the priority fee paid, introducing a fundamental trade-off between delays, uncertainty, and costs. We study the optimal trading problem of an agent exploiting trading signals in CEXs and DEXs. From a mathematical perspective, we derive the associated dynamic programming principle of this new class of impulse control problems, and establish the viscosity properties of the corresponding quasi-variational inequalities. From a financial perspective, our model provides insights on how to carry out execution across CEXs and DEXs, highlighting how traders manage latency risk optimally through priority fee selection. We show that employing the optimal priority fee has a significant outperformance over non-strategic fee selection.

Complexity vs Empirical Score

• Math Complexity: 8.5/10
• Empirical Rigor: 3.5/10
• Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper provides a rigorous mathematical framework extending stochastic delay impulse control and viscosity solutions to multi-order DEX priority fee settings. While technically impressive and highly novel theoretically, it focuses primarily on mathematical proofs and stylized numerical illustrations rather than empirical data analysis or real-world backtesting.

Research Flowchart

  flowchart TD
    A[Research Goal: Optimize CEX-DEX Trading & Priority Fees under Stochastic Delays] --> B[Inputs: CEX Trading Signals, DEX Gas Fees & Latency Distributions]
    B --> C[Methodology: Mixed Control Framework combining Continuous Control & Impulse Interventions]
    C --> D[Math Process: Derive Dynamic Programming Principle & Viscosity Solutions for QVIs]
    D --> E[Computational Optimization: Strategic Selection of Priority Fee & Async Pending Orders]
    E --> F[Outcomes: Optimal Latency Risk Management & Significant Outperformance over Non-Strategic Fees]

Cited References (35)

1. Optimal execution with stochastic delay (2023)
2. Price discovery on decentralized exchanges (2026)
3. Optimal fees for liquidity provision in automated market makers — → 2508.08152
4. Do Longer Block Times Impair Market Efficiency in Decentralized Markets? (2025)
5. The need for fees at a dex: How increases in fees can increase dex trading volume (2022)
6. Optimal exit time for liquidity providers in automated market makers — → 2509.06510
7. Decentralised finance and automated market making: Execution and speculation (2025) — link
8. Deviations from Tradition: Stylized Facts in the Era of DeFi — → 2510.22834

9 of 35 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.