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Automated Market Makers in Cryptoeconomic Systems: A Taxonomy and Archetypes

Daniel Kirste, Niclas Kannengießer, Ricky Lamberty, Ali Sunyaev

TL;DR

The paper addresses the challenge of designing effective automated market makers (AMMs) in cryptoeconomic systems by proposing a unified taxonomy and a set of archetypes to enable systematic comparison across designs. It combines literature analysis with empirical evaluation of real-world AMMs to derive a taxonomy consisting of 16 dimensions and 43 characteristics, then develops three archetypes—Price-discovering LP-based AMM, Price-adopting LP-based AMM, and Price-discovering Supply-sovereign AMM—that reflect distinct approaches to liquidity sourcing and price discovery. The work demonstrates that appropriate AMM design is key to ensuring sufficient liquidity and adequate token price discovery, with supply-sovereign AMMs offering promising avenues for token issuance and self-sovereign cryptoeconomic systems, though most existing literature centers on price-discovering LP-based models. By providing a practical taxonomy and archetypes, the paper offers actionable blueprints for engineers and researchers to tailor AMMs to diverse use cases, bridging software engineering and economics and supporting more sustainable decentralized markets. The study also highlights the prevalence of gray literature in AMM development and outlines future research directions, including quantitative evaluations of archetypes and novel incentive mechanisms to sustain liquidity while maintaining price efficiency.

Abstract

Designing automated market makers (AMMs) is crucial for decentralized token exchanges in cryptoeconomic systems. At the intersection of software engineering and economics, AMM design is complex and, if done incorrectly, can lead to financial risks and inefficiencies. We developed an AMM taxonomy for systematically comparing AMM designs and propose three AMM archetypes that meet key requirements for token issuance and exchange. This work bridges software engineering and economic perspectives, providing insights to help developers design AMMs tailored to diverse use cases and foster sustainable cryptoeconomic systems.

Automated Market Makers in Cryptoeconomic Systems: A Taxonomy and Archetypes

TL;DR

The paper addresses the challenge of designing effective automated market makers (AMMs) in cryptoeconomic systems by proposing a unified taxonomy and a set of archetypes to enable systematic comparison across designs. It combines literature analysis with empirical evaluation of real-world AMMs to derive a taxonomy consisting of 16 dimensions and 43 characteristics, then develops three archetypes—Price-discovering LP-based AMM, Price-adopting LP-based AMM, and Price-discovering Supply-sovereign AMM—that reflect distinct approaches to liquidity sourcing and price discovery. The work demonstrates that appropriate AMM design is key to ensuring sufficient liquidity and adequate token price discovery, with supply-sovereign AMMs offering promising avenues for token issuance and self-sovereign cryptoeconomic systems, though most existing literature centers on price-discovering LP-based models. By providing a practical taxonomy and archetypes, the paper offers actionable blueprints for engineers and researchers to tailor AMMs to diverse use cases, bridging software engineering and economics and supporting more sustainable decentralized markets. The study also highlights the prevalence of gray literature in AMM development and outlines future research directions, including quantitative evaluations of archetypes and novel incentive mechanisms to sustain liquidity while maintaining price efficiency.

Abstract

Designing automated market makers (AMMs) is crucial for decentralized token exchanges in cryptoeconomic systems. At the intersection of software engineering and economics, AMM design is complex and, if done incorrectly, can lead to financial risks and inefficiencies. We developed an AMM taxonomy for systematically comparing AMM designs and propose three AMM archetypes that meet key requirements for token issuance and exchange. This work bridges software engineering and economic perspectives, providing insights to help developers design AMMs tailored to diverse use cases and foster sustainable cryptoeconomic systems.
Paper Structure (51 sections, 9 equations, 4 figures, 6 tables)

This paper contains 51 sections, 9 equations, 4 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Background and Related Research
  3. Cryptoeconomic Systems and Distributed Ledger Technology
  4. Cryptoeconomic Systems
  5. Cryptoeconomic Systems based on Distributed Ledger Technology
  6. Automated Market Makers
  7. Principal Purposes of Automated Market Makers
  8. Decentralized Token Exchange
  9. Token Issuance
  10. Methods
  11. AMM Taxonomy Development
  12. Conceptual-to-Empirical (Iteration 0)
  13. Conceptual-to-Empirical (Iteration 1)
  14. Empirical-to-Conceptual (Iteration 2)
  15. Conceptual-to-empirical (Iteration 3)
  16. ...and 36 more sections

Figures (4)

  • Figure 1: Illustration of AMM component of Uniswap v2 zinsmeister_uniswap_2020
  • Figure 2: Architecture of the Price-discovering LP-based AMM and process of trade execution
  • Figure 3: Architecture of the Price-adopting LP-based AMM and process of trade execution
  • Figure 4: Architecture of the Price-discovering Supply-sovereign AMM and process of trade execution