Valuation frameworks for crypto assets

CHZ Valuation

Chiliz inherits the Other / Niche model set.

Static methodology preview. Live data pipeline planned. Not investment advice.

CHZ Other Static methodology preview

Chiliz

Market cap: data pipeline not connected

Composite model-implied value

$38.2B Valuation gap -17%

Model Cards

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

Classification

Custom Method Required

Flags assets that need classification before model selection.

Model-implied value method No composite value until comparable class mapping is complete.

Core inputs

asset purposeeconomic claimusage data

Forcing a model too early creates false precision.

Classification

Comparable Asset Class Mapping

Maps a niche asset to the closest valuation class or hybrid.

Model-implied value method Weights model families by class similarity.

Core inputs

use casecash-flow analogynetwork demandliquidity

Hybrid assets may require several model families.

Market durability

Liquidity and Persistence

Assesses whether a niche asset has enough durable liquidity for valuation work.

Model-implied value method Applies liquidity and persistence screens before valuation ranges.

Core inputs

liquidity depthvolume persistenceholder distribution

Poor liquidity can dominate all other model outputs.

Utility review

Token Utility Review

Reviews whether token utility has economic relevance.

Model-implied value method Classifies utility strength and modifies model confidence.

Core inputs

token usecapture mechanismuser demand

Utility without capture may not support token-level value.

Fundamentals Panel

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

Data completeness 26/100

Method confidence 28/100

Tokenholder capture Unclear

Fundamental evidence score 27/100

classificationliquidity persistenceutility review

Method Rating Panel

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

Low confidence

32/100

Classification confidence

These assets need classification before a serious model set can be assigned.

Low confidence

35/100

Liquidity persistence

Persistence screens determine whether deeper valuation work is warranted.

Scenario Simulator

A local assumption shell for scenario sensitivity.

Scenario sensitivity

Classification scenario

Model-implied FDV $6.0B

liquidity score 38 utility score 35 persistence score 32 class mapping confidence 30

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.