Research Summary
The report provides an in-depth analysis of the Arcadia Collateral Risk Simulation, detailing its architecture, progress, and future goals. It outlines the various components of the simulation, including the asset, chain, asset metadata, and liquidation process. The report also discusses the Orchestrator class, which allows for parallel execution of simulations, and the Borrower models based on Arcadia v1 Borrow data.
Key Takeaways
Arcadia Simulation Architecture
- Comprehensive Structure: The Arcadia simulation architecture is composed of various modules and classes that interact to simulate asset liquidation processes within the Arcadia v2 Lending Protocol. These include the asset, chain, asset metadata, and liquidation process.
- Asset and Chain: The asset is the fundamental unit representing various financial instruments, while the chain refers to a specific blockchain, providing necessary details for interaction.
- Liquidation Process: The liquidation process includes configuration settings that outline the rules and parameters for how liquidations are conducted. The Liquidation Engine is the core system responsible for managing liquidations.
Orchestrator Class
- Parallel Execution: The Orchestrator class allows for the parallel execution of simulations. It sets up various risk scenarios in which collateral assets and numeraire pairs are exposed to different market conditions.
- Key Methods: The Orchestrator has three key methods: prepare_simulation(), worker(), and execute(). These methods set up the simulation, organize and carry out the simulation for specific parameters, and initiate the simulation in parallel, respectively.
Borrower Models
- Based on Arcadia v1 Borrow Data: The report introduces three different Borrower Models based on Arcadia v1 Borrow data. These models help to arrive at the collateral distribution of a potential collateral portfolio at the initiation of the borrower accounts.
Progress and Future Goals
- Week 5 Progress: During week 5, the implementation of Orchestrator.py was completed and three different Borrower Models were introduced.
- Goals for Week 6: The team’s goals for week 6 include refinement of the simulation, gathering more borrower data, and testing more verification and validation scenarios on real-world test cases.
Actionable Insights
- Understanding the Arcadia Simulation Architecture: The detailed breakdown of the Arcadia simulation architecture provides valuable insights into the functioning of the Arcadia v2 Lending Protocol. This understanding can be useful for stakeholders and potential investors in the protocol.
- Exploring the Orchestrator Class: The Orchestrator class’s ability to execute simulations in parallel can be a significant factor in the efficiency and scalability of the Arcadia v2 Lending Protocol. Further exploration of this class and its methods could provide insights into potential improvements and optimizations.
- Assessing Borrower Models: The Borrower Models based on Arcadia v1 Borrow data can provide a realistic representation of borrower behavior. Analyzing these models could help in predicting future borrower behavior and assessing the risk associated with different borrower profiles.
