Assets Standardization

Modular Risk-Weighted Virtual Collateral Engine (MRVCE)

To address the challenges of risk management and capital efficiency in restaking ecosystems, we propose a Modular Risk-Weighted Virtual Collateral Engine (MRVCE) โ€” a flexible, scalable, and transparent framework designed to enable decentralized underwriting without requiring on-chain token conversions.


๐ŸŽฏ Core Requirements

The proposed solution must:

  • Eliminate on-chain token conversions, reducing gas overhead.

  • Enable seamless interoperability across various restaked assets.

  • Account for individual asset risks, such as LBTCโ€™s compatibility vs. stETHโ€™s liquidity.

  • Provide transparency and auditability for both users and auditors.

  • Scale effortlessly as new restaked assets are introduced into the system.


โš™๏ธ Mechanism Design

A. Asset Classification & Risk Weighting

A dedicated module classifies all restaked assets based on dynamic risk parameters:

  • Price Volatility (on-chain and off-chain deviation)

  • Liquidity Depth (across CEX/DEX markets)

  • Correlation to Native Pairs (ETH or BTC)

  • Slashing and Unbonding Risks

  • Oracle Latency and Trust Assumptions

Example Dynamic Risk Weight Table:

Token
Risk Weight
Category

stETH

1.00

LST (ETH-native, high liquidity)

rETH

0.95

LST (medium liquidity)

LBTC

0.30

BTC-native, low compatibility

EIGEN

0.10

Governance, illiquid


B. Virtual Collateral Pool (VCP)

All restaked assets from operators are virtually converted into USD value via oracle feeds (Chainlink or TWAP-based) and assigned a Risk-Adjusted Value (RAV) using:

iniCopyEditRAV = Nominal Value ร— Risk Weight

This RAV acts as the underwriting capacity benchmark for operators.


C. Market Pair Converter

When an operator underwrites in a specific market (e.g., WETH/USDC):

  • The engine aggregates total RAV from the operator.

  • Virtually converts it to ETH or BTC equivalent using real-time oracle rates.

  • Records the contribution breakdown per token and associated risk weights.

๐Ÿ‘‰ No token swaps โ€” purely virtual accounting.


๐Ÿ’ก Advantages of This Approach

Dimension
Advantage

Fairness

Operators with higher quality assets receive higher capacity allocations.

Risk-Based Protection

Safeguards against volatile or illiquid collaterals.

Scalability

New restaked tokens can be integrated without restructuring the core system.

On-Chain Efficiency

Zero token swaps required, minimizing gas costs.

Flexibility & Compliance

Supports AVSs/operators with diverse restaking strategies.


๐Ÿ“Š Case Study Example

Operator A Holdings:

  • 2 stETH ($4,000)

  • 3 rETH ($6,000)

  • 1 LBTC ($60,000)

Total Nominal Value: $70,000

Case Study before and after adjust

Risk-Adjusted Values (RAV):

  • stETH: $4,000 ร— 1.00 = $4,000

  • rETH: $6,000 ร— 0.95 = $5,700

  • LBTC: $60,000 ร— 0.30 = $18,000

Total RAV: $27,700

Underwriting Capacity in ETH (if ETH = $2,000):

$27,700 รท $2,000 = 13.85 ETH

๐Ÿ” Closing Thought

This Modular Risk-Weighted Virtual Collateral Engine unlocks a highly composable, fair, and efficient underwriting infrastructure for the future of restaking-based ecosystems โ€” a system where capital efficiency, risk transparency, and operational scalability coexist by design.

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