Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/183992
Title: An exploratory study on DeFi protocols
Authors: Tay, Denise Jia Ying
Keywords: Computer and Information Science
Issue Date: 2025
Publisher: Nanyang Technological University
Source: Tay, D. J. Y. (2025). An exploratory study on DeFi protocols. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/183992
Abstract: This report conducts a comparative analysis of liquidation mechanisms across three leading decentralized finance (DeFi) lending protocols, Aave, Compound, and MakerDAO, and across multiple protocol versions. The study explores how differing architectural choices influence protocol solvency, gas efficiency, and liquidator incentives, particularly under stress conditions. Drawing on technical documentation and smart contract analysis, the report identifies key design patterns, including auction-based models, fixed spread systems, and reserve-based absorption mechanisms. These are evaluated against major market stress events such as Black Thursday (March 2020), the DAI oracle glitch (November 2020), and the FTX collapse and CRV exploit (November 2022). In addition to architectural comparisons, the report conducts a data-driven analysis of gas usage during liquidation events, using Dune Analytics to extract and compare on-chain gas efficiency metrics across Ethereum and Layer 2 chains, highlighting Compound v3's absorption model and Aave v3's Layer 2 deployments, demonstrating how protocol upgrades have enhanced execution efficiency. The findings show that protocols have evolved toward more robust and scalable liquidation mechanisms, though each model entails different trade-offs between cost, risk containment, and decentralization. Based on these insights, the report concludes with practical recommendations tailored to different user profiles, ranging from liquidators and passive users, offering a framework for navigating and assessing DeFi lending protocols in a risk-aware and efficiency-conscious manner.
URI: https://hdl.handle.net/10356/183992
Schools: College of Computing and Data Science 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:CCDS Student Reports (FYP/IA/PA/PI)

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