Valuation frameworks for crypto assets
Compute and physical infrastructure networks evaluated through utilization, node economics, emissions, and demand durability.
The model set is selected for the economic behavior of this asset class.
Static class view of valuation gap and evidence quality.
AI / DePIN Bubble Map
Static methodology preview. Live data pipeline not yet connected.
Each model states what it measures and where its confidence breaks down.
Capitalizes revenue tied to compute, storage, bandwidth, or other network services.
Core inputs
Reported usage should be separated from subsidized activity.
Evaluates demand relative to available compute or node capacity.
Core inputs
High utilization can be temporary if incentives dominate.
Assesses node operator incentives and service supply durability.
Core inputs
Operator economics can change quickly with token price and demand.
Tests whether demand can absorb issuance or incentive emissions.
Core inputs
Weak demand-emissions balance can overwhelm usage growth.
Separates narrative-driven demand from sourceable fundamentals.
Core inputs
Narrative premium should be capped and transparent.
Method confidence reflects evidence quality, source availability, and token-level capture clarity.
A local assumption shell for testing scenario sensitivity without live data.
Scenario sensitivity
Static methodology preview. Changes here recompute a local scenario number only.
Planned source families for turning this framework into a data-backed dashboard.
Assets currently mapped to this valuation class.