CLVR Ordering of Transactions on AMMs

Paper: arXiv 2408.02634

Abstract

This paper introduces a trade ordering rule that aims to reduce intra-block price volatility in Automated Market Maker (AMM) powered decentralized exchanges. The ordering rule introduced here, Clever Look-ahead Volatility Reduction (CLVR), operates under the (common) framework in decentralized finance that allows some entities to observe trade requests before they are settled, assemble them into “blocks”, and order them as they like. On AMM exchanges, asset prices are continuously and transparently updated as a result of each trade and therefore, transaction order has high financial value. CLVR aims to order transactions for traders’ benefit. Our primary focus is intra-block price stability (minimizing volatility), which has two main benefits for traders: it reduces transaction failure rate and allows traders to receive closer prices to the reference price at which they submit their transactions accordingly. We show that CLVR constructs an ordering which approximately minimizes price volatility with a small computation cost and can be trivially verified externally.

Complexity vs Empirical Score

• Math Complexity: 5.0/10
• Empirical Rigor: 7.0/10
• Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper presents a novel algorithm (CLVR) with clear computational complexity analysis and theoretical bounds, but the core methodology is relatively intuitive (greedy local minimization) rather than heavily advanced. Empirically, it uses simulation on synthetic data extrapolated from empirical sources, reports quantitative results (95% failure reduction, 85% volatility reduction), and discusses practical implementation aspects, indicating strong data/implementation focus.

Research Flowchart

  flowchart TD
  A["Research Goal: Reduce intra-block price volatility<br>in AMM DEXs"] --> B["Framework: Decentralized Finance<br>Block Building & Transaction Ordering"]
  B --> C["Key Methodology: CLVR Ordering Rule<br>Look-ahead Volatility Reduction"]
  C --> D["Data/Input: Trade Requests<br>Price Reference"]
  D --> E["Process: Greedy Approximation<br>Minimizes volatility with low compute"]
  E --> F["Computational Process:<br>Construct Transaction Ordering"]
  F --> G["Key Outcome 1: Reduced Price Volatility<br>Minimizes intra-block swings"]
  F --> H["Key Outcome 2: Lower Failure Rate<br>Closer execution prices"]
  G & H --> I["Final Outcome: Verifiable<br>Efficient Trade Execution"]

Cited References (58)

1. Credible decentralized exchange design via verifiable sequencing rules (2023)
2. MEV Makes Everyone Happy under Greedy Sequencing Rule (2023)
3. Flash boys 2.0: Frontrunning in decentralized exchanges, miner extractable value, and consensus instability (2020)
4. Data Independent Order Policy Enforcement: Limitations and Solutions (2023) — link
5. Uniswap v2 Core (2020)
6. The conceptual flaws of decentralized automated market making (2023)
7. Proposer-builder separation, payment for order flows, and centralization in blockchain (2024)
8. The Power of Default: Measuring the Effect of Slippage Tolerance in Decentralized Exchanges (2023)

3 of 58 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.