Methodology
How BTC Tools builds its calculators, historical models, valuation tools, treasury models, comparisons and security models, including assumptions, uncertainty ranges and versioning.
Principles applied across every tool
- Stated assumptions. Each tool lists its formulas, variables and data sources on the same page.
- Reproducible inputs. Tool settings are kept in the page address, so a shared link reproduces the same result.
- Ranges where uncertainty is material. Optional 95% ranges use bootstrap resampling of historical returns or model residuals; the simple point estimate remains the default view.
- Provenance on exports. Downloaded charts carry the source page address and a UTC timestamp.
- Labelled judgement. Where a coefficient is a modelling choice rather than a fitted value, the tool says so.
Calculators
Calculators apply stated formulas to the inputs you provide. They do not forecast; they show the arithmetic consequence of your assumptions, and every input can be changed.
Retirement / FIRE calculator
Solves for the BTC stack required to fund annual expenses indefinitely at a chosen safe withdrawal rate, projected forward on the power-law trend.
Treasury allocation modeler
Stress-tests a {cash, BTC} treasury across bull, base, and bear BTC scenarios and reports risk-adjusted metrics for each allocation.
Balance-sheet impact model
Models the income-statement and balance-sheet impact of corporate BTC holdings under FASB ASU 2023-08 fair-value accounting.
Historical models
Historical models replay what would have happened using recorded closing prices. Results depend on the chosen start and end dates, so we show ranges of outcomes where a single path could mislead.
DCA backtester
Simulates dollar-cost averaging by buying a fixed dollar amount on a repeating schedule and accumulating units at each scheduled close price.
Cycle-position suite
Combines four independent indicators, normalizes each to a 0–100 heat reading, and averages them into a composite cycle temperature.
Valuation tools
Bitcoin has no cash flows, so valuation tools use statistical trend fits to price history. These describe the past relationship between price and time and are shown with uncertainty ranges, not as targets.
Power-law corridor
Fits a log-log linear regression of BTC price against days since the Bitcoin genesis block (3 Jan 2009), then derives three views from the same fit: a corridor around the trend, a price-÷-fair ratio, and a years-ahead-of-trend time-shift.
Price prediction model
Starts from the power-law trend drift over the chosen horizon, adds a transparent tilt to expected return for each technical, sentiment and macro condition, then converts the result into a lognormal price distribution and reports its quantiles. The output is a range, never a single target.
Treasury models
Treasury models combine company disclosures with market data to estimate metrics such as mNAV, dilution and forced-selling thresholds. They are only as current as the latest filings.
mNAV premium stress test
Stress-tests a BTC treasury company's equity by varying spot price while letting the market premium to NAV compress or expand independently.
Treasury drawdown survival
Solves for the BTC drawdown depth at which reserves can no longer cover the policy-mandated cash floor and the treasury becomes a forced seller.
Treasury company comparison
MSTR, Metaplanet & more, side by side
Comparisons
Comparisons put assets or companies on the same basis — the same dates, currency and return definition — so differences reflect the assets rather than the measurement.
Bitcoin vs. Everything
Bitcoin vs. Everything indexes Bitcoin and any selected combination of comparison assets (gold, S&P 500, NASDAQ, AAPL, NVDA, META, MSFT, GOOGL, ORCL, TSM) to 100 at the user-chosen start month, then computes return, risk, and risk-adjusted statistics from monthly closes over the same window.
Treasury company comparison
MSTR, Metaplanet & more, side by side
Security models
Security models classify on-chain exposure from public blockchain data and combine it with published research on quantum computing timelines. Timeline estimates are scenarios, not predictions.
Quantum exposure checker
Classifies a Bitcoin address by whether its public key is visible on chain, and estimates the quantum resources required to break it.
Harvest-now-decrypt-later timeline
Applies Mosca's Inequality to decide whether data being collected today is at risk of being decrypted once a cryptographically relevant quantum computer (CRQC) exists.
Migration-readiness checker
Scores custodian post-quantum readiness across four weighted dimensions and returns a 0–100 composite with a readiness band.
Quantum readiness score
Self-assessment across five Q-Risk pillars producing a 0–100 composite, with ceiling gates that cap the score when evidence is absent.
Treasury quantum exposure
Per-company quantum-exposure estimate
Versioning
This page describes methodology version 1.0. When a site-wide convention changes — for example the data window used for a fit or the way ranges are calculated — the version number is increased and the change is noted here. Analytical pages show the version they follow.
General limitations
- Past price behaviour does not guarantee future results.
- Model outputs depend on data quality; early Bitcoin history is thin.
- Ranges describe statistical uncertainty within the model, not every real-world risk.
- Company metrics can lag new filings or announcements.
Results are educational and are not individualised financial advice. See the methodology and editorial policy.
See also: data sources and editorial policy.