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Risk Engine & Liquidation System

The risk engine is responsible for calculating margin requirements, monitoring positions, and executing liquidations when necessary. Unlike opaque systems that treat risk formulas as proprietary, use.com publishes all risk mathematics, enabling traders to independently calculate their exact liquidation prices.

Published Risk Formulas

Maintenance Margin Requirement (MMR)

MMR=max⁡(MMbase,k×∣Position_Notional∣)MMR = \max(MM_{base}, k \times |Position_Notional|)MMR=max(MMbase,k×∣Position_Notional∣)

Where:

MM_base: Base maintenance margin (e.g., 0.5% for BTC, 0.7% for ETH)
k: Risk tier scaling factor (0.0001 for Tier 1, higher for riskier assets)
Position_Notional: Position_Size × Mark_Price

Example (BTC):

Position: 10 BTC at $50,000 = $500,000 notional
MM_base: 0.5%
k: 0.0001
MMR: max(0.005, 0.0001 × $500,000) = max($2,500, $50) = $2,500 (0.5%)

Initial Margin Requirement (IMR)

IMR=1.5×MMRIMR = 1.5 \times MMRIMR=1.5×MMR

The 50% buffer above maintenance margin provides cushion before liquidation.

Liquidation Price

For long positions: Liquidation_Price=Entry_Price×(1−MMR1+Leverage)Liquidation_Price = Entry_Price \times \left(1 - \frac{MMR}{1 + Leverage}\right)Liquidation_Price=Entry_Price×(1−1+LeverageMMR)

For short positions: Liquidation_Price=Entry_Price×(1+MMR1+Leverage)Liquidation_Price = Entry_Price \times \left(1 + \frac{MMR}{1 + Leverage}\right)Liquidation_Price=Entry_Price×(1+1+LeverageMMR)

Example (Long Position):

Entry: $50,000
Leverage: 10×
MMR: 1%
Liquidation Price: $50,000 × (1 - 0.01/1.1) = $50,000 × 0.9909 = $49,545

The trader knows with certainty that liquidation begins at $49,545.

Mark Price Construction

Mark price is used for liquidations to prevent manipulation:

Mark_Price=λ×Oracle_TWAP+(1−λ)×Mid_BookMark_Price = \lambda \times Oracle_TWAP + (1 - \lambda) \times Mid_BookMark_Price=λ×Oracle_TWAP+(1−λ)×Mid_Book

Where:

λ: Oracle weight (0.6-0.9 based on liquidity)
Oracle_TWAP: Time-weighted average from multiple oracle sources (Chainlink, Pyth, etc.)
Mid_Book: (Best_Bid + Best_Ask) / 2

Rationale: Prevents attackers from triggering liquidations by manipulating the order book. Oracle weight increases for more liquid markets.

Liquidation Ladder System

Rather than liquidating entire positions at once, use.com employs a phased approach:

Phase 1 (Mark price reaches liquidation price):

Liquidate 25% of position
Fee: 0.5% to insurance fund
Method: Limit order at liquidation price

Phase 2 (If price continues adverse):

Liquidate additional 25%
Fee: 0.75% to insurance fund
Method: Limit order at worse price

Phase 3 (Final liquidation):

Liquidate remaining 50%
Fee: 1.0% to insurance fund
Method: Market order if necessary

Benefits:

Reduces market impact
Gives position chance to recover
Maximizes insurance fund contribution
Minimizes auto-deleveraging (ADL) probability

Bankruptcy Price

Bankruptcy_Price=Entry_Price×(1±1Leverage)Bankruptcy_Price = Entry_Price \times \left(1 \pm \frac{1}{Leverage}\right)Bankruptcy_Price=Entry_Price×(1±Leverage1)

Where ± depends on position direction (- for long, + for short).

Example (10× Long):

Entry: $50,000
Bankruptcy: $50,000 × (1 - 1/10) = $45,000

The difference between liquidation price ($49,545) and bankruptcy price ($45,000) is the liquidation buffer that protects the insurance fund.

Insurance Fund Mechanics

Purpose: Cover losses when liquidation price is worse than bankruptcy price.

Target Coverage: Coverage_Ratio=Insurance_Fund_BalanceTotal_Open_Interest>5%Coverage_Ratio = \frac{Insurance_Fund_Balance}{Total_Open_Interest} > 5\%Coverage_Ratio=Total_Open_InterestInsurance_Fund_Balance>5%

Funding Sources:

Liquidation fees (0.5-1.0% of liquidated position)
Funding rate contributions (when applicable)
Initial allocation from treasury

Usage Priority:

Cover liquidation losses (when liquidation < bankruptcy)
Maintain target coverage ratio
Excess distribution (when coverage > 10% for 90 days)

Transparency: Real-time dashboard showing balance, coverage ratio, 24h inflows/outflows, and historical trends.

Auto-Deleveraging (ADL)

When insurance fund is insufficient to cover losses, ADL reduces opposing positions.

Priority Formula: ADL_Priority=Profit_Percentage×LeverageADL_Priority = Profit_Percentage \times LeverageADL_Priority=Profit_Percentage×Leverage

Ranking: Highest score deleveraged first.

Example:

User A: +50% profit, 20× leverage → Score = 1,000
User B: +30% profit, 10× leverage → Score = 300
User C: +80% profit, 5× leverage → Score = 400

ADL Order: User A → User C → User B

Rationale: Most profitable + highest leverage = highest risk contribution to system.

Notification: Users in ADL queue receive warnings when coverage ratio falls below thresholds.

Risk Tiers

Assets are categorized into risk tiers affecting margin requirements:

Tier

Assets

MM_base

Max Leverage

Tier 1

BTC, ETH, USDT, USDC

0.5-0.7%

0.0001

100×

Tier 2

Top 20 alts

1.0-2.0%

0.0003

50×

Tier 3

Long-tail assets

2.0-5.0%

0.0010

20×

Dynamic Adjustment: Risk parameters can be adjusted within governance-approved bounds based on volatility and liquidity conditions.

Position Monitoring

Real-Time Checks (every 100ms):

Calculate mark price
Update unrealized PnL
Check margin ratio
Trigger liquidation if necessary

Margin Ratio: Margin_Ratio=EquityPosition_NotionalMargin_Ratio = \frac{Equity}{Position_Notional}Margin_Ratio=Position_NotionalEquity

Where:

Equity = Balance + Unrealized_PnL
Position_Notional = Position_Size × Mark_Price

Liquidation Trigger: When Margin_Ratio < MMR

Risk Limits

Position Size Limits: Prevent excessive concentration

Max_Position=Insurance_Fund×Risk_FactorMark_PriceMax_Position = \frac{Insurance_Fund \times Risk_Factor}{Mark_Price}Max_Position=Mark_PriceInsurance_Fund×Risk_Factor

Example (BTC):

Insurance Fund: 100 BTC
Risk Factor: 0.1 (10%)
Mark Price: $50,000
Max Position: (100 × 0.1) / 1 = 10 BTC per user

Open Interest Limits: Cap total open interest per symbol to manage systemic risk.

Stress Testing

Scenario Analysis: Monthly stress tests simulate:

20% price move in 1 hour
50% price move in 24 hours
Flash crash scenarios
Oracle failure scenarios

Insurance Fund Adequacy: Verify coverage remains > 5% under stress scenarios.

Conclusion

use.com's risk engine provides transparent, deterministic risk management through published formulas, phased liquidations, and real-time insurance fund monitoring. By enabling traders to independently calculate liquidation prices and verify system health, use.com eliminates the "black box" problem that has eroded trust in centralized exchanges.

Previous: ← Matching Engine & Order Book Design Next: Wallet Infrastructure & Custody Model →

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Updated on: 10/03/2026

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