Improving DeFi Mechanisms with Dynamic Games and Optimal Control: A Case Study in Stablecoins

TL;DR

This paper introduces a novel Stackelberg game-based control scheme for stablecoins, improving resilience against depegging and outperforming existing adaptive mechanisms through extensive simulations.

Contribution

It proposes a new control framework based on Stackelberg games for stablecoins, enhancing stability and outperforming existing adaptive schemes.

Findings

Mitigates adverse depeg events in stablecoins.

Outperforms existing adaptive redemption schemes in simulations.

Demonstrates robustness across various market conditions.

Abstract

Stablecoins are a class of cryptocurrencies which aim at providing consistency and predictability, typically by pegging the token's value to that of a real world asset. Designing resilient decentralized stablecoins is a challenge, and prominent stablecoins today either (i) give up on decentralization, or (ii) rely on user-owned cryptocurrencies as collateral, exposing the token to exogenous price fluctuations. In this latter category, it is increasingly common to employ algorithmic mechanisms to automate risk management, helping maintain the peg. One example of this is Reflexer's RAI, which adapts its system-internal exchange rate (redemption price) to secondary market conditions according to a proportional control law. In this paper, we take this idea of active management a step further, and introduce a new kind of control scheme based on a Stackelberg game model between the token protocol and its users. By doing so, we show that (i) we can mitigate adverse depeg events that inevitably arise in a fixed-redemption scheme such as MakerDao's DAI and (ii) generally outperform a simpler, adaptive-redemption scheme such as RAI in the task of targeting a desired market price. We demonstrate these results through extensive simulations over a range of market conditions.