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Mean-Field Game Analysis of Stablecoin Peg Recovery

Article arXiv papers · Author: Hardhik Mohanty et al.
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Summary

The paper models how arbitrageurs and retail traders interact across primary and secondary markets during a de-peg in fiat-collateralized stablecoins. Its dynamic, agent-based mean-field game connects market frictions to equilibrium prices and net order flows, allowing the authors to attribute pressure that moves prices back toward the peg and assess when market infrastructure may be inadequate.

Calibrated on three historical de-peg events, the model reproduces observed recovery half-lives and attributes most stabilizing pressure to primary-market arbitrage. Sensitivity analysis also finds a nonlinear threshold beyond which recovery becomes substantially slower. The excerpt does not identify the events, provide parameter estimates, or describe how well the framework generalizes beyond those cases, so its findings should be read as model-based evidence rather than a universal account of peg recovery.

Key ideas

  • A mean-field game represents strategic interactions between arbitrageurs and retail traders during stablecoin de-pegs.
  • The framework links market frictions to equilibrium prices and implied order flows across primary and secondary markets.
  • The calibrated model reproduces recovery half-lives observed in three historical episodes.
  • Primary-market arbitrage accounts for most of the modeled stabilizing pressure.
  • Sensitivity analysis identifies a nonlinear threshold associated with slower peg recovery.

Tags

CryptoArbitrageMarket microstructureMean reversionStatistics
Full text
# 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.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.