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稳定币脱锚后的均值场博弈与锚定恢复

文章 arXiv papers · 作者: Hardhik Mohanty et al.

总结

本文建模分析法币抵押型稳定币脱锚期间,套利者与散户交易者如何在一级和二级市场互动。其动态智能体均值场博弈将市场摩擦与均衡价格和净订单流联系起来,使作者能够分析推动价格回归锚定水平的力量,并评估市场基础设施何时可能不足。

模型根据三次历史脱锚事件校准,能够重现观察到的恢复半衰期,并将大部分稳定价格的力量归因于一级市场套利。敏感性分析还发现一个非线性阈值,超过该阈值后,恢复速度会大幅减慢。摘录没有指出具体事件、提供参数估计,也没有说明该框架在这些案例之外的适用程度,因此这些发现应视为基于模型的证据,而非对锚定恢复的普遍解释。

核心观点

  • 均值场博弈刻画稳定币脱锚期间套利者与散户交易者之间的策略互动。
  • 该框架将市场摩擦与一级、二级市场的均衡价格和隐含订单流联系起来。
  • 经校准的模型重现了三个历史事件中观察到的恢复半衰期。
  • 模型中,大部分稳定价格的力量来自一级市场套利。
  • 敏感性分析发现了与锚定恢复变慢相关的非线性阈值。

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# Who Restores the Peg? A Mean-Field Game Approach to Model Stablecoin Market Dynamics


# Who Restores the Peg? A Mean-Field Game Approach to Model Stablecoin Market Dynamics









USDC and USDT are the dominant stablecoins pegged to \$1 with a total market capitalization of over \$300B and rising. Stablecoins make dollar value globally accessible with secure transfer and settlement. Yet in practice, these stablecoins experience periods of stress and de-pegging from their \$1 target, posing significant systemic risks. The behavior of market participants during these stress events and the collective actions that either restore or break the peg are not well understood. This paper addresses the question: who restores the peg?. We develop a dynamic, agent-based mean-field game framework for fiat-collateralized stablecoins, in which a large population of arbitrageurs and retail traders strategically interact across primary and secondary markets during a de-peg episode. The key advantage of this equilibrium formulation is that it endogenously maps market frictions into a market-clearing price path and implied net order flows, allowing us to attribute peg-reverting pressure by channel and to stress-test when a given infrastructure becomes insufficient for recovery. Using three historical de-peg events, we show that the calibrated equilibrium reproduces observed recovery half-lives and yields an order flow decomposition in which system-wide stress is predominantly stabilized by primary-market arbitrage. Finally, a quantitative sensitivity analysis identifies a non-linear breakdown threshold, beyond which a de-peg becomes markedly slower to reverse.

在遵守原作品许可的前提下,附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写,并非原文副本。