Algorithmic Stablecoins: A Simulator for the Dual-Token Model in Normal and Panic Scenarios

In the decentralized finance landscape, algorithmic stablecoins offer a promising solution for stabilizing the value of cryptocurrencies without relying on centralized collaterals. However, models like the dual-token system are vulnerable to depeg events, as demonstrated by the catastrophic collapse of the Terra-Luna ecosystem in 2022, which saw over 50 billion dollars in market capitalization evaporate in just a few days. This work proposes DualTokenSim, a Python simulator designed to analyze the behavior of cryptocurrencies based on the dual-token model under both normal and panic scenarios. The simulator uses automated market makers and a stochastic process to simulate price dynamics and user behavior. The aim is to offer an environment in which to explore and analyze solutions for improving the resilience of algorithmic stablecoins during periods of market instability.