Alris Agent Documentation
  • 👋Alris - AI-Powered Yield Optimizer
  • Overview
    • ⭐️ what is alris
    • 💡What alris do
    • ✨Token Utility
  • How alris invest your money
    • Overview
    • Data Flow in Alris Protocol
    • Risk model
    • Rebalancing
  • Data Flow in Alris Protocol
  • Alris Risk Model
    • Overview: How the Alris Risk Model Works
    • Volatility Risk
    • Liquidity Risk
    • Protocol Risk
    • Combining the risks
  • Alral engine and Rebalancing
    • Alral Engine: Overview and Role in Alris
    • Alral engine
    • Rebalancing in Alris Protocol
Powered by GitBook
On this page
  1. Alris Risk Model

Overview: How the Alris Risk Model Works

The Alris Risk Model, powered by the Alral engine, evaluates and manages investment risks to optimize returns in the decentralized finance (DeFi) ecosystem. It operates by:

  1. Collecting Real-Time Data: The model continuously gathers data on market conditions, liquidity pool performance, and protocol reliability from blockchain transactions, price oracles, and DeFi protocols.

  2. Assessing Risks: It evaluates three key risk types:

    • Volatility Risk: Measures asset price fluctuations to ensure stability.

    • Liquidity Risk: Determines how easily assets can be traded without affecting prices.

    • Protocol Risk: Assesses the security and reliability of DeFi platforms.

  3. Combining Risks: Individual risk metrics are weighted and combined into an overall risk score (RtotalR_{\text{total}}) using a mathematical formula. This score guides investment decisions.

  4. Dynamic Portfolio Rebalancing: The model uses the risk score and user-defined risk preferences to automatically adjust fund allocations, ensuring alignment with investment goals while adapting to market changes.

By integrating real-time data analysis, comprehensive risk evaluation, and automated adjustments, the Alris Risk Model provides a robust and adaptive approach to DeFi portfolio management.


PreviousData Flow in Alris ProtocolNextVolatility Risk

Last updated 4 months ago