Axioms for Constant Function Market Makers

ABSTRACT We study axiomatic foundations for different classes of automated market makers (AMMs). Our main results are a characterization of a generalization of constant product market makers (CPMMs), popular in decentralized finance, and a characterization of the Logarithmic Market Scoring Rule AMM, popular in prediction markets. The first class is characterized by the combination of independence and scale invariance, whereas the second is characterized by the combination of independence and translation invariance. The two classes are, therefore, distinguished by a different invariance property that is motivated by different interpretations of the numéraire in the two applications, but pinned down by the same separability property. Moreover, we characterize the CPMM as trader‐optimal among scale invariant, independent, symmetric and sufficiently funded AMMs. Our results add to a formal analysis of mechanisms used in practice and connect the most popular class of decentralized finance (DeFi) AMMs to the most popular class of prediction market AMMs.

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Publication Details

Journal
Mathematical Finance
Published
2026-06-25
DOI
https://doi.org/10.1111/mafi.70041
Primary Topic
Sports Analytics and Performance
Type
article
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article

Axioms for Constant Function Market Makers

Mateusz Kwaśnicki, Akaki Mamageishvili, Christoph Schlegel
Mathematical Finance
Sports Analytics and Performance
article

Axioms for Constant Function Market Makers

Mateusz Kwaśnicki, Akaki Mamageishvili, Christoph Schlegel
article en

Abstract

ABSTRACT We study axiomatic foundations for different classes of automated market makers (AMMs). Our main results are a characterization of a generalization of constant product market makers (CPMMs), popular in decentralized finance, and a characterization of the Logarithmic Market Scoring Rule AMM, popular in prediction markets. The first class is characterized by the combination of independence and scale invariance, whereas the second is characterized by the combination of independence and translation invariance. The two classes are, therefore, distinguished by a different invariance property that is motivated by different interpretations of the numéraire in the two applications, but pinned down by the same separability property. Moreover, we characterize the CPMM as trader‐optimal among scale invariant, independent, symmetric and sufficiently funded AMMs. Our results add to a formal analysis of mechanisms used in practice and connect the most popular class of decentralized finance (DeFi) AMMs to the most popular class of prediction market AMMs.

Mathematical Finance
Wrocław University of Science and Technology (PL), Unchained Labs (United States) (US), Kantonsschule Enge (CH), AGH University of Krakow (PL)
Openalex Percentile: Top 3%
Sports Analytics and Performance
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