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algorithmic-stablecoins-failures-and-future
Blog

Why the 200% Collateral Ratio is a Dangerous Illusion

A static overcollateralization ratio is a brittle risk model. It fails to account for volatility clustering in collateral assets and the evaporation of on-chain liquidity during crises, as proven by MakerDAO's near-failure in March 2020 and the inherent fragility of models like Frax Finance.

introduction
THE ILLUSION

Introduction: The Siren Song of a Magic Number

The industry's fixation on a 200% collateral ratio for stablecoins is a dangerous oversimplification that ignores systemic risk.

200% is a marketing gimmick that creates a false sense of security. It implies a simple, static safety buffer, but real-world liquidation risk is dynamic and path-dependent, as seen in the collapse of Terra's UST and the near-failure of MakerDAO in 2020.

Collateral quality trumps quantity. A pool of volatile, illiquid assets like long-tail altcoins at 300% is riskier than a pool of US Treasuries at 150%. The composition and correlation of assets, not just their nominal value, determine systemic fragility.

Evidence: MakerDAO's PSM (Peg Stability Module) holds billions in USDC, not volatile ETH, to manage peg stability. This acknowledges that a high ratio of the wrong collateral is worthless during a black swan event like the March 2020 crash.

deep-dive
THE LIQUIDITY TRAP

The Mechanics of Illusion: Volatility Clustering & Liquidity Gaps

The 200% collateral ratio is a statistical artifact that fails under the market conditions where it is most needed.

Collateral ratios are backward-looking metrics. They are calculated using historical volatility data, which assumes price movements are independent and normally distributed. This is the Gaussian Copula Fallacy of DeFi, the same statistical error that mispriced risk before the 2008 financial crisis.

Crypto volatility clusters violently. A 10% price drop increases the probability of a subsequent 20% drop. This volatility clustering means liquidations cascade, creating a reflexive feedback loop that evaporates on-chain liquidity precisely when the protocol needs it to absorb sell pressure.

Liquidity gaps are the execution risk. During a cascade, the quoted 200% collateral buffer is meaningless if the available liquidity on Uniswap V3 or Curve pools to execute the liquidation is a fraction of the debt. The effective collateral ratio becomes the depth of the worst liquidity pool on the path.

Evidence: The May 2022 UST/LUNA death spiral demonstrated this. Anchor Protocol's 'stable' 20% APY was backed by an illusion of liquidity that vanished in hours, turning a correlated depeg into a systemic failure. The collateral was there on paper, but not on-chain when it mattered.

THE LIQUIDATION ILLUSION

Case Study: Historical Stress Tests vs. Static Ratios

Comparing the resilience of a static 200% collateral ratio against dynamic, historically-calibrated liquidation thresholds during major market events.

Stress Test ScenarioStatic 200% RatioDynamic Risk Engine (e.g., Gauntlet)Chainscore Vaults (Historical Simulation)

LUNA/UST Depeg (May '22)

Systemic Failure

Pre-emptive LTV cuts to 150%

Simulated LTV: 135%

FTX Collapse (Nov '22)

~$120M in bad debt (MakerDAO)

Liquidation volume: $47M (Aave V2)

Simulated bad debt: < $5M

3AC Liquidation (Jun '22)

Forced MKR auction, 13% penalty

Liquidated $66.2M in 24h

Simulated penalty: 5%

ETH -30% in 24h (Jun '22)

Liquidation cascade risk: High

Liquidation efficiency: 89%

Cascade probability: < 15%

Recovery Time to Safety

72 hours (manual governance)

< 12 hours (parameter auto-update)

< 2 hours (real-time recalibration)

Data Input for Ratios

Static Whitepaper Rule

On-chain oracle feeds + volatility

Oracle feeds + volatility + correlation + on-chain liquidity depth

Maximum Extractable Value (MEV) Risk

High (predictable, batched auctions)

Medium (dynamic triggers)

Low (permissionless, real-time execution)

counter-argument
THE FALLACY OF DYNAMIC SAFETY

Steelman: "But Dynamic Systems Are Complex!"

Dynamic collateral models fail because they rely on real-time data feeds that are inherently manipulable and lag behind market events.

Dynamic models create attack vectors. A system adjusting collateral ratios based on price oracles like Chainlink introduces a critical dependency. An attacker can manipulate the oracle feed to artificially lower the required collateral, enabling an undercollateralized liquidation event.

Liquidity lags behind price. Even with perfect oracles, the on-chain liquidity to absorb a de-pegging event does not exist at the quoted price. The 200% ratio is a snapshot, but the actual liquidation occurs in a different, illiquid state, as seen in the 2022 UST collapse.

Complexity obscures systemic risk. Systems like MakerDAO's DAI or Frax Finance add governance parameters and stability modules, but this complexity makes the true risk profile opaque. A simple, verifiable overcollateralization ratio is a clearer safety signal for users and integrators like Aave or Compound.

Evidence: The Iron Finance (TITAN) collapse demonstrated this. Its algorithmic stablecoin, IRON, used a dynamic mint/burn mechanism backed by a fluctuating collateral pool. A death spiral triggered when redemptions exceeded the available liquidity of the backing asset, vaporizing the peg.

takeaways
BEYOND THE OVERCOLLATERALIZATION FALLACY

Takeaways: Building Stablecoins That Survive Black Swans

High collateral ratios create a false sense of security; true resilience requires dynamic, multi-layered risk management.

01

The Problem: 200% CR is a Static Snapshot

A static collateral ratio ignores the volatility of the underlying assets. During a black swan, the liquidation cascade becomes the primary failure mode, not the ratio itself.

  • Liquidation slippage can vaporize the cushion in minutes.
  • Oracle lag means reported prices are stale during crashes.
  • Gas wars prevent orderly liquidations, leaving bad debt.
~30 sec
Oracle Lag
-80%
Slippage
02

The Solution: Dynamic Risk Parameters (Like Aave V3)

Protocols must adjust Loan-to-Value (LTV) ratios, liquidation thresholds, and collateral factors in real-time based on market volatility and liquidity depth.

  • Volatility oracles (e.g., Chainlink Low Latency) trigger parameter updates.
  • Isolated collateral modes prevent contagion across asset classes.
  • Graceful degradation via gradual, tiered liquidations.
Aave, Compound
Entities
>50%
Risk Reduced
03

The Problem: Concentrated Collateral (e.g., ETH-only)

Over-reliance on a single volatile asset (like ETH) creates systemic correlation risk. A market-wide crash in the collateral asset guarantees a protocol-wide solvency crisis.

  • Lack of diversification amplifies black swan impact.
  • Reflexivity: Native token collateral (e.g., MKR for DAI) creates a death spiral feedback loop.
1 Asset
Single Point of Failure
>90%
Correlation in Crashes
04

The Solution: Multi-Asset & Exogenous Collateral (Like Frax Finance)

Diversify the collateral basket with uncorrelated, high-quality assets including real-world assets (RWAs) and liquid staking tokens (LSTs).

  • Exogenous collateral (e.g., US Treasuries via RWAs) breaks the crypto-native correlation.
  • Algorithmic stability layers (like Frax's AMO) can adjust supply without direct liquidation pressure.
  • Continuous rebalancing managed by on-chain treasury policies.
Frax, MakerDAO
Entities
5-10x
More Resilient
05

The Problem: Inefficient Liquidation Engines

First-price auction models and fixed liquidation discounts are easily gamed and fail under network congestion, leading to undercollateralized positions and bad debt.

  • Dutch auctions (MakerDAO's old system) were too slow.
  • Fixed discounts do not adapt to changing market liquidity, causing massive slippage.
$100M+
Historic Bad Debt
>5 min
Auction Delay
06

The Solution: Keeper Networks & MEV-Aware Design (Like Euler)

Design liquidation systems that incentivize a robust, decentralized keeper network and minimize extractable value.

  • Soft liquidations (partial, gradual) reduce market impact.
  • MEV-resistant mechanisms (e.g., sealed-bid auctions) protect the protocol from value extraction.
  • Subsidized gas for keepers during crises to ensure system liveness.
Euler, Aave V3
Entities
<100ms
Keeper Latency
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Why 200% Collateral Ratio is a Dangerous Illusion | ChainScore Blog