A mathematical framework for modelling CLMM dynamics in continuous time

TL;DR

This paper introduces a rigorous continuous-time mathematical framework for modeling CLMMs in DeFi, analyzing liquidity dynamics, arbitrage strategies, and the impact of trading fees on price processes.

Contribution

It provides a novel measure-valued process model for CLMM liquidity evolution and derives closed-form solutions for various arbitrage strategies, highlighting the role of trading fees.

Findings

Liquidity profiles modeled as measure-valued processes

Closed-form solutions for arbitrage strategies

Trading fees constrain price process diffusion

Abstract

This paper develops a rigorous mathematical framework for analyzing Concentrated Liquidity Market Makers (CLMMs) in Decentralized Finance (DeFi) within a continuous-time setting. We model the evolution of liquidity profiles as measure-valued processes and characterize their dynamics under continuous trading. Our analysis encompasses two critical aspects of CLMMs: the mechanics of concentrated liquidity provision and the strategic behavior of arbitrageurs. We examine three distinct arbitrage models -- myopic, finite-horizon, and infinite-horizon with discounted and ergodic controls -- and derive closed-form solutions for optimal arbitrage strategies under each scenario. Importantly, we demonstrate that the presence of trading fees fundamentally constrains the admissible price processes, as the inclusion of fees precludes the existence of diffusion terms in the price process to avoid infinite fee generation. This finding has significant implications for CLMM design and market efficiency.