Paper: arXiv 2410.09983

Authors: Andrey Urusov, Rostislav Berezovskiy, Yury Yanovich

Abstract

Decentralized finance (DeFi) has revolutionized the financial landscape, with protocols like Uniswap offering innovative automated market-making mechanisms. This article explores the development of a backtesting framework specifically tailored for concentrated liquidity market makers (CLMM). The focus is on leveraging the liquidity distribution approximated using a parametric model, to estimate the rewards within liquidity pools. The article details the design, implementation, and insights derived from this novel approach to backtesting within the context of Uniswap V3. The developed backtester was successfully utilized to assess reward levels across several pools using historical data from 2023 (pools Uniswap v3 for pairs of altcoins, stablecoins and USDC/ETH with different fee levels). Moreover, the error in modeling the level of rewards for the period under review for each pool was less than 1%. This demonstrated the effectiveness of the backtester in quantifying liquidity pool rewards and its potential in estimating LP’s revenues as part of the pool rewards, as focus of our next research. The backtester serves as a tool to simulate trading strategies and liquidity provision scenarios, providing a quantitative assessment of potential returns for liquidity providers (LP). By incorporating statistical tools to mirror CLMM pool liquidity dynamics, this framework can be further leveraged for strategy enhancement and risk evaluation for LPs operating within decentralized exchanges.

Complexity vs Empirical Score

  • Math Complexity: 5.5/10
  • Empirical Rigor: 6.5/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper provides a practical mathematical framework for backtesting Uniswap V3 concentrated liquidity pools with less than 1% error using 2023 historical data. It offers a solid mix of DEX mechanics formulation and GPU-accelerated empirical validation across multiple pool types.

Research Flowchart

  flowchart TD
    A[Research Goal: Develop Backtesting Framework for Uniswap V3 CLMM] --> B[Input Data: 2023 Historical Pool Data<br/>Altcoins, Stablecoins, USDC/ETH]
    B --> C[Methodology: Estimate Liquidity Distribution via Parametric Model]
    C --> D[Backtester Execution: Simulate Trading Strategies & Rewards]
    D --> E[Outcome: High-Precision Reward Quantification<br/>Error Level < 1%]
    E --> F[Future Application: LP Revenue Estimation & Strategy Optimization]

Cited References (77)

  1. Ethereum White Paper: A Next Generation Smart Contract & Decentralized Application Platform (2013) — link
  2. Bitcoin: A Peer-to-Peer Electronic Cash System (2008) — link
  3. On public and private blockchains (2015) — link
  4. Ethereum: Solidity (2018) — link
  5. GASOL: gas analysis and optimization for ethereum smart contracts, in: Tools and Algorithms for the Construction and Analysis of Systems - 26th International Conference, TACAS 2020, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020, Dublin, Ireland, April 25-30, 2020, Proceedings, Part II, 2020, pp. 118–125.
  6. EthIR: A Framework for High-Level Analysis of Ethereum Bytecode (2018) — link
  7. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare (2015)
  8. “Blockchain-Based Supply Chain for Postage Stamps”, Informatics, vol. 5, No. 4, p. 42, 11 2018.
and 69 more
  1. Source repository for coursework. — link
  2. Scipy Documentation, coo matrix — link
  3. Ethereum: HardHat — link
  4. The Art of Computer Programming (1968)
  5. Opcodes for the EVM — link
  6. Design Patterns for Gas Optimization in Ethereum (2020) — link
  7. The singular value decomposition: Its computation and some applications (1980) — link
  8. Introduction to the Theory of Computation (1996)
  9. Smart contracts (2021) — link
  10. Sereum: Protecting Existing Smart Contracts Against Re-Entrancy Attacks (2019) — link
  11. A Survey on Ethereum Systems Security: Vulnerabilities, Attacks, and Defenses (2020) — link
  12. Empirical review of automated analysis tools on 47,587 Ethereum smart contracts (2020) — link
  13. Fundamentals of Nonparametric Bayesian Inference (2017) — link
  14. The ability to regulate emotion is associated with greater well-being, income, and socioeconomic status. (2010) — link
  15. Expected returns and expected dividend growth (2005)
  16. Dividend policy, growth, and the valuation of shares (1961)
  17. Dividend premium: Are dividend-paying stocks worth more? (2018)
  18. Stocks for the long run: The definitive guide to financial market returns & long-term investment strategies (2021)
  19. Blockchain mutability: Challenges and proposed solutions (2019)
  20. Ouroboros: A Provably Secure Proof-of-Stake Blockchain Protocol (2017) — link
  21. Bitcoin’s energy consumption is underestimated: A market dynamics approach (2020) — link
  22. Ethereum White Paper: A Next Generation Smart Contract & Decentralized Application Platform (2014) — link
  23. Ethereum, smart contracts, DApps (2020)
  24. Formalizing and securing relationships on public networks (1997)
  25. Mastering ethereum: building smart contracts and dapps (2018)
  26. Ethereum: A secure decentralised generalised transaction ledger (2014)
  27. Dividends: A 400-Year-Old Practice ({2021})
  28. Impact of dividend policy on shareholders’ value: a study of Indian firms (2009)
  29. Dividend policy decisions (2010)
  30. What are dividends?
  31. Transaction fees optimization in the Ethereum blockchain (2022) — link
  32. Gasol: Gas analysis and optimization for ethereum smart contracts (2020)
  33. Tokenizing assets with dividend payouts—a legally compliant and flexible design (2023) — link
  34. Optimal Portfolio Sold-Out via Blockchain Tokenization (2020) — link
  35. Financial Instruments Generation via Tokenization into Commodity (2020) — link
  36. Token Standard for Heterogeneous Assets Digitization into Commodity (2019) — link
  37. Application of blockchain for secure data transmission in distributed state estimation (2021)
  38. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare (2018)
  39. Implementation of Tokenised Supply Chain Using Blockchain Technology (2020)
  40. A review of Blockchain Technology applications for financial services (2022) — link
  41. Profiling gas consumption in solidity smart contracts (2022) — link
  42. Liquidity Math in Uniswap v3 (2021) — link
  43. Deconstructing Decentralized Exchanges (2019)
  44. An overview of Web3 technology: Infrastructure, applications, and popularity (2024) — link
  45. An empirical study on the complexity, security and maintainability of Ethereum-based decentralized applications (DApps) (2023) — link
  46. Digital exchange attributes and the risk of closure (2023) — link
  47. A New Era of Blockchain-Powered Decentralized Finance (DeFi) - A Review (2022) — link
  48. Uniswap Whitepaper (2018) — link
  49. EIP-20: ERC-20 Token Standard (2015) — link
  50. Token Standard for Heterogeneous Assets Digitization into Commodity (2019) — link
  51. Tokens, Types, and Standards: Identification and Utilization in Ethereum (2020) — link
  52. Uniswap v2 Core (2020) — link
  53. Uniswap v3 Core (2021) — link
  54. Strategic Liquidity Provision in Uniswap V3 (2023) — link
  55. Risks and Returns of Uniswap V3 Liquidity Providers (2022) — link
  56. Data Mining of Uniswap Decentralized Exchange (2022) — link
  57. Differential Liquidity Provision in Uniswap v3 and Implications for Contract Design (2022) — link
  58. Uniswap Liquidity Provision: An Online Learning Approach (2024) — link
  59. UNISWAP: Impermanent Loss and Risk Profile of a Liquidity Provider (2021) — link
  60. Measuring DeFi risk (2024) — link
  61. Loan Portfolio Dataset From MakerDAO Blockchain Project (2024) — link
  62. Stablecoins 2.0 (2020) — link
  63. While stability lasts: A stochastic model of noncustodial stablecoins (2022) — link
  64. In Search for Stability in Crypto-Assets: Are Stablecoins the Solution? (2019) — link
  65. Quantifying Loss in Automated Market Makers (2022) — link
  66. Thorough mathematical modelling and analysis of Uniswap v3 (2023)
  67. Impermanent loss in uniswap v3 (2021) — link
  68. FLAIR: A Metric for Liquidity Provider Competitiveness in Automated Market Makers — → 2306.09421
  69. Uniswap V3 Backtester: Source Code and Scripts (2024) — link

1 of 77 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.