Balancer Simulations
  • Getting Started
  • Understanding Balancer AMMs
    • Balancer Basics
    • Use cases
  • Simulation Packages
    • Model Overview
    • Pool Functions
    • Pool Exploration
  • Code & Instructions
    • Dynamic weights changing
    • Arbitrage agent
    • Balancer: the Python edition
      • ActionDecoder
      • pool_state_updates.py
      • partial_state_update_blocks.py
      • Spot Price calculation
      • balancer_constants.py
      • balancer_math.py
      • balancer_pool.py
      • Verification & Limitations
    • Naming Convention
    • Adding On-chain Transaction Data and USD Prices
    • Modeling Time
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Getting Started

Balancer Simulations is an open-source cadCAD model and simulation framework, developed by the Token Engineering Community.

NextBalancer Basics

Last updated 4 years ago

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Welcome to Balancer Simulations!

Balancer Simulations is a project of TE-AMM and the Token Engineering Community, funded by grants from and , and kicked off by .

It aims to build infrastructure and knowledge for rigorous Balancer Token Engineering to leverage the full power of Balancer Pools as a core building block in DeFi.

We invite any project building on Balancer Pools to join our and benefit from Balancer Simulations.

  • Analyze existing Balancer Pools using on-chain transaction data, understand pool characteristics, strengths, and weaknesses

  • Gain intuition by exploring pool variants, observe system behavior over time, derive the most valuable monitoring metrics for your use case

  • Run experiments based on historical transactions, mix historical and synthetic transactions to model particular market scenarios

  • Develop and test adaptive Dynamic AMM solutions, like Dynamic Weights Changing, test and optimize controls and feedback loops

  • Model agent behavior and apply Reinforcement Learning to run stress tests for a proposed system design

All research and models are available through open source repositories, and will be further developed by TE-AMM.

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