A Tick-by-Tick Solution for Concentrated Liquidity Provisioning

TL;DR

This paper presents a convex optimization approach for tick-level liquidity provisioning in automated market makers, revealing that concentrating liquidity near the current price often isn't optimal.

Contribution

It introduces a novel convex optimization framework for concentrated liquidity provisioning and challenges the common assumption that proximity to the current price is optimal.

Findings

Optimal liquidity distribution often not near current price

Convex optimization effectively models liquidity provisioning

Strategy depends on swap volume and volatility estimates

Abstract

Automated market makers with concentrated liquidity capabilities are programmable at the tick level. The maximization of earned fees, plus depreciated reserves, is a convex optimization problem whose vector solution gives the best provision of liquidity at each tick under a given set of parameter estimates for swap volume and price volatility. Surprisingly, early results show that concentrating liquidity around the current price is usually not the best strategy.