Crypto Value Lab v 0.1.0
X Substack

Valuation frameworks for crypto assets

VVV Valuation

Venice Token inherits the AI / Compute / DePIN model set.

Static methodology preview. Live data pipeline planned. Not investment advice.
VVV AI / DePIN Static methodology preview

Venice Token

Market cap: data pipeline not connected

Composite model-implied value

$49.0B Valuation gap 14%

Model Cards

The asset page uses the model set assigned to its asset class.

Usage revenue

Usage Revenue Multiple

Capitalizes revenue tied to compute, storage, bandwidth, or other network services.

Model-implied value method Applies a multiple to verified usage revenue.

Core inputs

usage revenueutilizationmultiple range

Reported usage should be separated from subsidized activity.

Capacity use

Compute Utilization

Evaluates demand relative to available compute or node capacity.

Model-implied value method Scores utilization and converts it into a model adjustment.

Core inputs

capacityutilizationpricingretention

High utilization can be temporary if incentives dominate.

Supply-side economics

Node Economics

Assesses node operator incentives and service supply durability.

Model-implied value method Compares node revenue and emissions against required supply-side returns.

Core inputs

node revenueemissionshardware costoperator churn

Operator economics can change quickly with token price and demand.

Token emissions

Demand / Emissions Balance

Tests whether demand can absorb issuance or incentive emissions.

Model-implied value method Applies an emissions adjustment to usage-based value.

Core inputs

emissionsorganic demandretentionfloat

Weak demand-emissions balance can overwhelm usage growth.

Scenario premium

Narrative Premium

Separates narrative-driven demand from sourceable fundamentals.

Model-implied value method Applies a bounded narrative premium in scenario analysis.

Core inputs

attentioncategory growthfundamental evidence

Narrative premium should be capped and transparent.

Fundamentals Panel

Current fundamental fields are static methodology categories, not live data.

Data completeness 49/100
Method confidence 34/100
Tokenholder capture Unclear
Fundamental evidence score 48/100
usage revenuecompute utilizationnode economicsemissions

Method Rating Panel

Confidence scores are class-level method ratings, not asset guidance.

Low confidence

42/100

Usage revenue evidence

The category needs better separation of organic demand from incentive-led activity.

Low confidence

45/100

Node economics

Operator economics and emissions are central but unevenly disclosed.

Scenario Simulator

A local assumption shell for scenario sensitivity.

Scenario sensitivity

Compute network scenario

Model-implied FDV $12.0B

Static methodology preview. Changes here recompute a local scenario number only.

Source Trail

Planned data sources for the valuation architecture.

CoinGecko

price, market cap, FDV, supply, and volume

Source

DefiLlama

TVL, fees, revenue, and DeFi volumes

Source

Coin Metrics

BTC-style realized cap, MVRV, and network metrics

Source

Dune or manual source trails

custom on-chain datasets and methodology notes

Source

Static methodology preview. Live data pipeline planned. Not investment advice. The displayed model-implied value is an architecture test for assumption-led valuation.