Partially Active Automated Market Makers

TL;DR

This paper introduces the partially active automated market maker (PA-AMM), which divides reserves into active and passive parts to reduce adverse selection costs and improve liquidity provider wealth, with a trade-off in asset weight stability.

Contribution

It proposes a novel PA-AMM mechanism that dynamically adjusts active reserves to enhance market efficiency and liquidity provider returns, addressing limitations of traditional CFMMs.

Findings

PA-AMM reduces adverse selection costs compared to CFMMs.

The mechanism improves liquidity provider wealth.

Asset weights may deviate from target weights, but can be optimized.

Abstract

We introduce a new class of automated market maker (AMM), the \emph{partially active automated market maker} (PA-AMM). PA-AMM divides its reserves into two parts, the active and the passive parts, and uses only the active part for trading. At the top of every block, such a division is done again to keep the active reserves always being \(\lambda\)-portion of total reserves, where \(\lambda \in (0, 1]\) is an activeness parameter. We show that this simple mechanism reduces adverse selection costs, measured by loss-versus-rebalancing (LVR), and thereby improves the wealth of liquidity providers (LPs) relative to plain constant-function market makers (CFMMs). As a trade-off, the asset weights within a PA-AMM pool may deviate from their target weights implied by its invariant curve. Motivated by the optimal index-tracking problem literature, we also propose and solve an optimization problem that balances such deviation and the reduction of LVR.