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Information Structures in Stablecoin Markets

Brian Zhu

TL;DR

The paper develops a two-risk global-game model of stablecoins that incorporates a non-strategic large seller and uncertainty in reserve-asset information. It shows that selling pressure faced by holders rises when a large sale occurs, and that the overall run probability can be decomposed into collateral risk $R_0$ and large-sale risk $R_1$, with each component responding differently to public and private information precision. By decomposing risks and solving for a unique equilibrium switching strategy, the work identifies regions in the fundamentals space where runs are more sensitive to information structure and highlights how opacity can, under some conditions, stabilize markets. The analysis has practical regulatory implications, linking testable predictions to real-world depegging episodes and informing information-design policies such as the GENIUS Act and potential cryptographic reserve-verification mechanisms.

Abstract

Stablecoins have historically depegged due from par to large sales, possibly of speculative nature, or poor reserve asset quality. Using a global game which addresses both concerns, we show that the selling pressure on stablecoin holders increases in the presence of a large sale. While precise public knowledge reduces (increases) the probability of a run when fundamentals are strong (weak), interestingly, more precise private signals increase (reduce) the probability of a run when fundamentals are strong (weak), potentially explaining the stability of opaque stablecoins. The total run probability can be decomposed into components representing risks from large sales and poor collateral. By analyzing how these risk components vary with respect to information uncertainty and fundamentals, we can split the fundamental space into regions based on the type of risk a stablecoin issuer is more prone to. We suggest testable implications and connect our model's implications to real-world applications, including depegging events and the no-questions-asked property of money.

Information Structures in Stablecoin Markets

TL;DR

The paper develops a two-risk global-game model of stablecoins that incorporates a non-strategic large seller and uncertainty in reserve-asset information. It shows that selling pressure faced by holders rises when a large sale occurs, and that the overall run probability can be decomposed into collateral risk and large-sale risk , with each component responding differently to public and private information precision. By decomposing risks and solving for a unique equilibrium switching strategy, the work identifies regions in the fundamentals space where runs are more sensitive to information structure and highlights how opacity can, under some conditions, stabilize markets. The analysis has practical regulatory implications, linking testable predictions to real-world depegging episodes and informing information-design policies such as the GENIUS Act and potential cryptographic reserve-verification mechanisms.

Abstract

Stablecoins have historically depegged due from par to large sales, possibly of speculative nature, or poor reserve asset quality. Using a global game which addresses both concerns, we show that the selling pressure on stablecoin holders increases in the presence of a large sale. While precise public knowledge reduces (increases) the probability of a run when fundamentals are strong (weak), interestingly, more precise private signals increase (reduce) the probability of a run when fundamentals are strong (weak), potentially explaining the stability of opaque stablecoins. The total run probability can be decomposed into components representing risks from large sales and poor collateral. By analyzing how these risk components vary with respect to information uncertainty and fundamentals, we can split the fundamental space into regions based on the type of risk a stablecoin issuer is more prone to. We suggest testable implications and connect our model's implications to real-world applications, including depegging events and the no-questions-asked property of money.
Paper Structure (18 sections, 5 theorems, 11 equations, 4 figures, 2 tables)

This paper contains 18 sections, 5 theorems, 11 equations, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Institutional Details.
  3. Related Literature.
  4. Model
  5. Complete Information Game
  6. Agents and the Market.
  7. Timeline.
  8. Utilities.
  9. Equilibrium.
  10. Global Game
  11. Timeline (Global Game).
  12. Utilities (Global Game).
  13. Equilibrium (Global Game).
  14. Results
  15. Discussion
  16. ...and 3 more sections

Key Result

proposition 2.1

Under Assumption 1, there exists a unique equilibrium $(x^\star_0,x^\star_1)$ in switching strategies of the global game in which $x^\star_0<x^\star_1$.

Figures (4)

  • Figure 1: A diagram of collateral risk (red) and large sale risk (blue). The horizontal axis represents the value of fundamentals and the vertical axis represents probabilities.
  • Figure 2: Diagram of how collateral risk and large sale risk change with respect to the precision of the common prior. The horizontal axis represents the prior mean $\mu$.
  • Figure 3: Comparison of priors with different precisions with critical run thresholds marked. The horizontal axis represents fundamental values $\theta$.
  • Figure 4: Diagram of how collateral risk and large sale risk change with respect to the precision of private signals. The horizontal axis represents the prior mean $\mu$.

Theorems & Definitions (6)

  • remark 1
  • proposition 2.1
  • proposition 3.1
  • proposition 3.2
  • proposition 3.3
  • proposition 3.4