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Real-time Risk Metrics for Programmatic Stablecoin Crypto Asset-Liability Management (CALM)

Marcel Bluhm, Adrian Cachinero Vasiljević, Sébastien Derivaux, Søren Terp Hørlück Jessen

TL;DR

This paper tackles risk management for on-chain stablecoins by introducing Crypto Asset-Liquidity Management (CALM), a framework of two metrics—capital at risk (CaR) and a funding-gap-based liquidity measure—that adapt Basel-inspired principles to transparent, real-time on-chain data. It demonstrates applicability with MakerDAO and its DAI, showing how CaR and CR quantify capital adequacy and how the funding-gap metric exposes short-tenor liquidity risks under stressed conditions. The results reveal a fragile capitalization position (CR around 0.416) and identifiable short-term liquidity gaps, guiding governance recommendations like dynamic recapitalization and increased PSM liquidity. The work highlights regulatory relevance and the potential for embedded supervision using public-blockchain data to monitor and manage risk in stablecoin systems.

Abstract

Stablecoins have turned out to be the "killer" use case of the growing digital asset space. However, risk management frameworks, including regulatory ones, have been largely absent. In this paper, we address the critical question of measuring and managing risk in stablecoin protocols, which operate on public blockchain infrastructure. The on-chain environment makes it possible to monitor risk and automate its management via transparent smart-contracts in real-time. We propose two risk metrics covering capitalization and liquidity of stablecoin protocols. We then explore in a case-study type analysis how our risk management framework can be applied to DAI, the biggest decentralized stablecoin by market capitalisation to-date, governed by MakerDAO. Based on our findings, we recommend that the protocol explores implementing automatic capital buffer adjustments and dynamic maturity gap matching. Our analysis demonstrates the practical benefits for scalable (prudential) risk management stemming from real-time availability of high-quality, granular, tamper-resistant on-chain data in the digital asset space. We name this approach Crypto Asset-Liability Management (CALM).

Real-time Risk Metrics for Programmatic Stablecoin Crypto Asset-Liability Management (CALM)

TL;DR

This paper tackles risk management for on-chain stablecoins by introducing Crypto Asset-Liquidity Management (CALM), a framework of two metrics—capital at risk (CaR) and a funding-gap-based liquidity measure—that adapt Basel-inspired principles to transparent, real-time on-chain data. It demonstrates applicability with MakerDAO and its DAI, showing how CaR and CR quantify capital adequacy and how the funding-gap metric exposes short-tenor liquidity risks under stressed conditions. The results reveal a fragile capitalization position (CR around 0.416) and identifiable short-term liquidity gaps, guiding governance recommendations like dynamic recapitalization and increased PSM liquidity. The work highlights regulatory relevance and the potential for embedded supervision using public-blockchain data to monitor and manage risk in stablecoin systems.

Abstract

Stablecoins have turned out to be the "killer" use case of the growing digital asset space. However, risk management frameworks, including regulatory ones, have been largely absent. In this paper, we address the critical question of measuring and managing risk in stablecoin protocols, which operate on public blockchain infrastructure. The on-chain environment makes it possible to monitor risk and automate its management via transparent smart-contracts in real-time. We propose two risk metrics covering capitalization and liquidity of stablecoin protocols. We then explore in a case-study type analysis how our risk management framework can be applied to DAI, the biggest decentralized stablecoin by market capitalisation to-date, governed by MakerDAO. Based on our findings, we recommend that the protocol explores implementing automatic capital buffer adjustments and dynamic maturity gap matching. Our analysis demonstrates the practical benefits for scalable (prudential) risk management stemming from real-time availability of high-quality, granular, tamper-resistant on-chain data in the digital asset space. We name this approach Crypto Asset-Liability Management (CALM).
Paper Structure (9 sections, 4 equations, 7 figures, 3 tables)

This paper contains 9 sections, 4 equations, 7 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Literature Review
  3. CALM Risk Metrics and Framework
  4. Capitalization
  5. Liquidity Coverage Ratio
  6. Case Study: A CALM Approach to Real-Time Risk Metrics for MakerDAO
  7. Overview of MakerDAO
  8. CALM Risk Metrics for MakerDao
  9. Conclusion

Figures (7)

  • Figure 1: MakerDAO’s Balance Sheet over time (see https://dune.com/queries/2840463/4743803)
  • Figure 2: Capital at Risk over time by risk source (see https://dune.com/queries/3286476/5501452)
  • Figure 3: Capital at Risk over time by asset type (see https://dune.com/queries/3274044/5480144)
  • Figure 4: Capital Ratio over time (see https://dune.com/queries/3286476/5515381)
  • Figure 5: Expected DAI redemptions under stress, by tenor (see https://dune.com/queries/3286476/5515552)
  • ...and 2 more figures