Bonding Curve Research Group Library ๐Ÿ“š
  • About the BCRG
  • About this Library
  • โ™ป๏ธFrom Static to Dynamic Supply Tokens
  • โžฐWhat are Bonding Curves?
  • ๐Ÿ—ƒ๏ธDifferentiating Primary & Secondary AMMs
  • ๐Ÿค–Modeling & Simulating Bonding Curves
  • ๐ŸŽ›๏ธBonding Curve Parameter Matrix & Trade-Off Decisions
    • Initial Supply
    • Initial Reserve
    • Initial Price
    • Reserve Ratio
    • Mint Fee
    • Burn Fee
    • Max Supply
  • โ˜ ๏ธAttack Vectors
    • Liquidations
    • Sandwich trading
    • Front Running
    • Backrunning
    • Solutions
  • ๐Ÿ““Case Studies
    • ๐Ÿค–Aavegotchi
      • Bonding Curve Design
      • Pricing Algorithm
      • Governance and Tokenomics
        • Avegotchi DAO Evoution
    • ๐Ÿ‘ฃCarbon
      • Asymmetric Liquidity
      • Adjustable Bonding Curves
      • Matching, Routing & Arbitrage in AMMs
      • MEV Resistance
    • ๐Ÿ“ˆContinuous Organization (cOrg)
      • cOrg Token Bonding Curve Model
        • The Decentralized Autonomous Trust
        • Bonding Curve Contract Dynamics in Investment and Sale Operations
    • ๐ŸฎCoW Protocol
      • Loss Versus Rebalancing (LVR)
        • Deep dive into Loss-Versus-Rebalancing (LVR)
      • Batch Trading & Function-Maximizing AMMs
      • Implementation - COW AMM
    • โš™๏ธDXDao
      • DXdao Bonding Curve
    • โš“Gyroscope
      • The Gyro Bonding Curve
      • Elliptic Concentrated Liquidity Pools (E-CLP)
      • Gyro Consolidated Price Feeds
        • Consolidated Price Feed Approach
    • ๐Ÿ•‰๏ธOlympus DAO
      • Range Bound Stability
    • ๐Ÿ’ธ Public Goods Token Performance Analysis
  • ๐Ÿ„ Engineering for Resilience with Primary Issuance Markets
  • ๐Ÿ’ปBCRG Github Repos
  • ๐Ÿ“ฝ๏ธBCRG Video Library
  • ๐Ÿ“–Glossary
  • ๐Ÿ”ŽToken Engineering Courses & Resources
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  1. Attack Vectors

Liquidations

PreviousAttack VectorsNextSandwich trading

Last updated 9 months ago

In decentralized finance, lending protocols such as Maker and Aave offer a significant opportunity for Miner Extractable Value (MEV) through liquidations. These platforms require users to deposit collateral, like ETH, which can then be used to lend assets to others. Borrowers can leverage their collateral to borrow up to a certain percentage of its value, as determined by the protocol. For example, with a borrowing limit set at 30%, depositing 100 DAI allows a user to borrow up to 30 DAI worth of other assets. This collateralization ensures the protocol's solvency and limits the borrowing capacity based on the collateral's value.

The MEV opportunity arises when the value of a borrowerโ€™s collateral declines due to market fluctuations, causing the borrowed amount to exceed the permissible limit. If, for instance, the borrowed assets surpass 30% of the collateral's value, the protocol allows for liquidation. This mechanism is similar to a in traditional finance, where the borrower must either repay the loan or face liquidation of their collateral. In DeFi, anyone can initiate the liquidation process, covering the borrowed amount and receiving a portion of the liquidation fee as a reward. This fee serves as an incentive for liquidators to act swiftly, ensuring the protocol's stability by repaying the lenders promptly.

MEV searchers, therefore, compete intensely to identify liquidation opportunities by rapidly parsing blockchain data. Their goal is to be the first to submit a liquidation transaction, thereby securing the liquidation fee. This competition drives the need for sophisticated algorithms and real-time monitoring to detect fluctuations in collateral values and execute liquidation transactions efficiently, maximizing the profit potential from these opportunities.

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