Simulating Protocol Economics In DeFi A Game Theory Approach

The financial logic of these protocols is largely driven by token incentive structures: who receives rewards, when, and for what behavior.
By designing robust systems, developers must understand how these incentives interact under various market conditions, a challenge that is addressed in the field of quantitative foundations for decentralized finance protocols.
Traditional analysis often relies on equilibrium concepts from economics or on empirical data from running protocols, echoing the discussions in studies such as establishing equilibrium in token supply with game theory.
When combined with game theory, simulation becomes a powerful tool to predict strategic behavior and to identify potential vulnerabilities, as explored in game theory meets DeFi protocols modeling tokenomics for optimal incentives.
Simulating protocol economics provides a dynamic sandbox where designers can test, validate, and refine incentive structures before launch, a process that benefits from a deeper understanding of token incentive structures.
By building a sandbox that mirrors protocol behavior, designers can iterate quickly, spot problems early, and reduce the cost of failure—an approach grounded in the principles outlined in the work on quantitative foundations for decentralized finance protocols.

Token incentives are the engine that drives user behavior, and the reward function may be linear or incorporate more complex dynamics, as discussed in the mathematical foundations of DeFi tokenomics and incentive design.

In the case study of liquidity mining in a DEX, the simulation ran for 500 epochs, each representing one day, and the results illustrate how reward rates and lock‑up periods influence both liquidity growth and token price dynamics—phenomena that are closely examined in research on predicting market dynamics in DeFi token pools with game theory.