Automated Market Makers in Cryptoeconomic Systems: A Taxonomy and Archetypes
Daniel Kirste, Niclas Kannengie{\ss}er, Ricky Lamberty, Ali Sunyaev
TL;DR
This paper presents a systematic taxonomy and archetypes for automated market makers in cryptoeconomic systems, aiming to improve design, reduce risks, and support diverse decentralized token exchange use cases.
Contribution
It introduces a comprehensive taxonomy and three archetypes for AMMs, bridging software engineering and economic perspectives to guide better design.
Findings
Proposed a taxonomy for comparing AMM designs
Identified three key AMM archetypes
Provided insights for tailored AMM development
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.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFinancial Markets and Investment Strategies · Complex Systems and Time Series Analysis · Stock Market Forecasting Methods
Methodsfail