Objective
Publish a standardized value score built from fundamental, technical, and
sentiment inputs without turning that score into a fair-value price target.
Implementation
The public app reads a 17-input workbook, computes the arithmetic mean of the
published z-scores, and compares it with the workbook’s composite.
Categories
Seven fundamental inputs, seven technical inputs, and three sentiment
inputs.
Primary Scale
The score is oriented so positive values mean greater modeled value in the
current workbook. The inverse lens multiplies that score by `-1`.
FundamentalBTC: Supply in Profit Market Bands; Short-Term Holder MVRV Indicator; True Market Mean Price + AVIV Ratio; NUPL; Adjusted MVRV; Puell Multiple; MVRV Pricing Bands.
Technical52-Week BTC Sharpe Ratio; BTC RSI; The Mayer Multiple; BTC SOPR Z-Score; BTC Short-Term Holder Supply P/L Ratio; BTC STH Cost Basis Delta; Bitcoin Macro Oscillator (BMO).
SentimentCrypto Fear & Greed Index; Google Trends (BTC - 5 Years); Sentix BTC Sentiment.
Normalization
Each input is expressed as a Z-score: its distance from the relevant
historical mean in standard deviations. The app publishes the composite on
the workbook’s declared scale.
Historical Series
Forward-testing history appears only when the workbook contains dated score
observations. The app does not backfill missing history.
Classification
The workbook publishes the current state label. The public application does
not hard-code expensive, neutral, and cheap thresholds beyond reading the
workbook output.
Update Frequency
The valuation workbook is re-read every five minutes by default.
Methodology change log
Changes to valuation inputs, normalization windows, classifications, or composite construction are versioned in the public methodology register before publication.
Disclaimer
Valuation is educational market research, not investment advice, a price target, or a recommendation to buy, sell, or hold Bitcoin. Z-scores can remain elevated or depressed and past readings do not predict future outcomes.