On Waterfall's cryptoeconomic forecast

This work presents a system dynamics modeling approach to evaluate critical economic metrics on the Waterfall platform, a decentralized public network. The constructed model serves as a significant tool for understanding the intricate economic processes within the platform and supports informed decision-making by stakeholders. By using input parameters such as the number of network validators and transactions per second (TPS) over time, the model projects key metrics like the inflation rate and total supply of coins, providing insights into the platform's economic stability. The Waterfall platform is designed as a scalable smart contract ecosystem, underpinned by cryptoeconomics, to ensure a self- sustaining and self-regulating environment that maximizes stakeholder benefits. The platform's mainnet, launched in June 2024, has shown consistency between testnet results and theoretical calculations, demonstrating the robustness of the underlying economic model. However, as with any economic system, forecasting is essential for decision-making and improving efficiency. The system dynamics model allows for the exploration of different scenarios, considering various growth assumptions for validators and TPS, to project future economic conditions of the platform. Three scenarios – pessimistic, realistic, and optimistic – are considered, each with distinct growth trajectories for the number of validators and TPS. The outcomes highlight that while the initial stages of the network are characterized by high reward rates due to a smaller number of validators, these rates decline as more validators join, affecting the inflation rate over time. The relationship between the minting of new coins (as validator rewards) and the burning of transaction fees determines the system's inflationary dynamics. Under certain conditions, an increase in TPS could lead to deflation, enhancing the platform's economic sustainability. The results suggest that Waterfall's cryptoeconomic model has a strong potential for long-term stability and growth. The model's flexibility allows for adjustments based on real-time data and expert judgments, making it a valuable tool for both internal stakeholders and external analysts. This approach could also be applied to studying the cryptoeconomics of other decentralized networks, providing a broader understanding of their economic stability and long-term viability.