Saved in:
Bibliographic Details
Main Authors: Assmann, Björn, Degenbaev, Ulan
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2604.16898
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866914486282092544
author Assmann, Björn
Degenbaev, Ulan
author_facet Assmann, Björn
Degenbaev, Ulan
contents Many automated market makers can be understood through the geometry of their trading orbits, the sets of states reachable from one another through swaps. In prominent designs, this geometry is captured by a simple closed-form invariant such as the constant product $xy$ in Uniswap or a weighted geometric mean $x^w y^{1-w}$ in Balancer. This paper explains why these forms arise by deriving them from three basic assumptions: validity invariance (swaps preserve the validity of states), Pareto efficiency (no state on an orbit weakly dominates another), and unit invariance (changing measurement units does not change the mechanism). Together, these force every trading orbit of a two-asset AMM to be a level set of a weighted geometric mean $x^w y^{1-w}$. Applied pairwise, the axioms extend the classification to $n$-asset pools: orbits are level sets of $\prod_i x_i^{w_i}$ with positive weights $w_i$ summing to $1$. Imposing token-relabeling symmetry then pins down the weights, recovering the constant-product form $xy$ in the two-asset case and $\prod_i x_i$ in general. The main text provides an intuitive proof sketch and discusses fees and liquidity operations. Complete proofs and a machine-checked Lean 4 formalization accompany the paper.
format Preprint
id arxiv_https___arxiv_org_abs_2604_16898
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle From Swap Axioms to Weighted Geometric Means: A Characterization of AMMs
Assmann, Björn
Degenbaev, Ulan
Distributed, Parallel, and Cluster Computing
Computer Science and Game Theory
91B26, 91G99, 68V20
Many automated market makers can be understood through the geometry of their trading orbits, the sets of states reachable from one another through swaps. In prominent designs, this geometry is captured by a simple closed-form invariant such as the constant product $xy$ in Uniswap or a weighted geometric mean $x^w y^{1-w}$ in Balancer. This paper explains why these forms arise by deriving them from three basic assumptions: validity invariance (swaps preserve the validity of states), Pareto efficiency (no state on an orbit weakly dominates another), and unit invariance (changing measurement units does not change the mechanism). Together, these force every trading orbit of a two-asset AMM to be a level set of a weighted geometric mean $x^w y^{1-w}$. Applied pairwise, the axioms extend the classification to $n$-asset pools: orbits are level sets of $\prod_i x_i^{w_i}$ with positive weights $w_i$ summing to $1$. Imposing token-relabeling symmetry then pins down the weights, recovering the constant-product form $xy$ in the two-asset case and $\prod_i x_i$ in general. The main text provides an intuitive proof sketch and discusses fees and liquidity operations. Complete proofs and a machine-checked Lean 4 formalization accompany the paper.
title From Swap Axioms to Weighted Geometric Means: A Characterization of AMMs
topic Distributed, Parallel, and Cluster Computing
Computer Science and Game Theory
91B26, 91G99, 68V20
url https://arxiv.org/abs/2604.16898