Augmenting Batch Exchanges with Constant Function Market Makers
Geoffrey Ramseyer, Mohak Goyal, Ashish Goel, David Mazi\`eres

TL;DR
This paper formalizes the integration of constant function market makers into batch exchanges, analyzing tradeoffs among desirable properties, and introduces a convex program for computing market equilibria under certain conditions.
Contribution
It provides a formal axiomatic framework for combining CFMMs with batch exchanges, explores property conflicts, and extends Arrow-Debreu market equilibrium computation.
Findings
Identified key axioms for batch exchanges and CFMMs.
Analyzed property conflicts such as Pareto optimality and price coherence.
Developed a convex program for market equilibrium with WGS demand functions.
Abstract
Batch auctions are a classical market microstructure, acclaimed for their fairness properties, and have received renewed interest in the context of blockchain-based financial systems. Constant function market makers (CFMMs) are another market design innovation praised for their computational simplicity and applicability to liquidity provision via smart contracts. Liquidity provision in batch exchanges is an important problem, and CFMMs have recently shown promise in being useful within batch exchanges. Different real-world implementations have used fundamentally different approaches towards integrating CFMMs in batch exchanges, and there is a lack of formal understanding of different design tradeoffs. We first provide a minimal set of axioms that are well-accepted rules of batch exchanges and CFMMs. These are asset conservation, uniform valuations, a best response for limit orders,…
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
TopicsEconomic theories and models · Auction Theory and Applications · Stochastic processes and financial applications
