Valuation frameworks for crypto assets
Class-based valuation frameworks for crypto assets.
BTC, ETH, HYPE, AAVE, LINK, DOGE, and ONDO are not the same economic object. CVL applies different valuation models by asset class, then exposes assumptions, caveats, and confidence.
Each class starts with a different model set and a different burden of evidence.
Assets primarily evaluated through scarcity, holder persistence, settlement demand, network security, and monetary premium.
Data coverage
Network metrics, realized value, holder behavior, settlement activity
Execution and settlement networks evaluated through fee generation, app capital, stablecoin activity, staking, and ecosystem depth.
Data coverage
Fees, TVL, stablecoin supply, active users, staking, app activity
Venue-linked tokens evaluated through fee pools, volume share, liquidity depth, token capture, and float pressure.
Data coverage
Fees, volumes, open interest, liquidity, supply schedules
Protocol assets evaluated through fees, protocol revenue, TVL efficiency, utilization, treasury value, and tokenholder capture.
Data coverage
TVL, protocol revenue, fees, utilization, treasury disclosures
Infrastructure networks evaluated through secured value, usage requests, integrations, revenue, and security collateral.
Data coverage
Usage, secured value, integrations, revenue, staking collateral
Compute and physical infrastructure networks evaluated through utilization, node economics, emissions, and demand durability.
Data coverage
Usage revenue, compute utilization, node economics, emissions
Real-world asset networks evaluated through AUM, fee take rate, regulatory risk, asset backing, and distribution reach.
Data coverage
AUM, fees, revenue, treasury backing, regulatory disclosures
Culture-linked assets evaluated through liquidity persistence, holder distribution, attention durability, and cycle sensitivity.
Data coverage
Liquidity, holder concentration, attention proxies, relative basket behavior
Assets that require custom classification before a valuation model can be applied responsibly.
Data coverage
Liquidity, utility review, comparable class mapping, persistence
Representative assets mapped by valuation gap, fundamental evidence, data completeness, and method confidence.
Valuation Gap Bubble Map
Static methodology preview. Live data pipeline not yet connected.
Coverage is static and methodological. Market data is not yet connected to this build. Treat as illustration only.
Dashboard structure inspired by ETHval’s multi-model Ethereum valuation interface. CVL extends the idea into an asset-class taxonomy across crypto assets.
This page shows the architecture of the valuation workbench: model sets by asset class, method confidence, source trails, and scenario sensitivity. It does not present live market outputs.