Bitcoin adoption follows a power law whose volatility is decreasing, revealing a rising floor you can build your financial life on.

This is the research behind that claim. Seventeen papers. 5,700+ daily data points. Every conclusion earned by the data before it. Every claim falsifiable.

5,719 daily closes
0 model breaks
R² = 0.956 model fit
16 published papers
162 pages of research
Yesterday
Floor-- Trend--
Power Law Floor --
BTC Price
--
Trend Value
--
Price / Trend
--
Floor Yield / BTC
--
Floor Growth
--
Tomorrow
Floor-- Trend--
The Argument
The Past
The Power Law

Bitcoin's price follows a power law. 15 years of daily data. R² above 0.95. The observed signature of network adoption spanning six orders of magnitude. Not a prediction. An observation.

Data: 5,719 daily closes Fit: R² = 0.956
The Process
Volatility Decay

The distribution compresses every halving cycle. Five metrics, all significant. The ceiling collapses 2.2x faster than the floor rises. The wild swings are structurally dying.

Compression: ~20% per cycle Z-scores: −5.3 to −21.1
The Residual
The Floor

When the noise dies, what remains is the floor. Dipped below on about 2.4% of days, recovered above every time. Rising every day. The mathematical signature of cumulative adoption. The attractor the entire distribution converges onto.

Structural breaks: 0 in 15 years Floor rate: --
The Conclusion
Derisk: Live Off the Floor Growth

When stack times floor growth exceeds expenses, ruin probability approaches zero. All remaining volatility is upside. Risk has an expiration date. Build your financial life on the floor.

Efficiency: 5x vs S&P 500 Tested: 20 families
The Power Law

15 years of daily closes. Price has closed below the floor on about 2.4% of days (135 of 5,713 closes) and recovered above it every time. The dashed line shows where it's going.

Scale
Range
Projection
BTC Price Trend ±1σ Floor (−2σ) Ceiling (+2σ) Live
Floor Today
--
Floor 2027
--
Floor 2031
--
Annual Floor Growth
--
Floor Hits $1M
--
Published Research · 162 pages
Passive vs Active Retirement
v1.0
+50pp playbook coverage uplift @ 99%
The Bitcoin Safe Withdrawal Rate
v1.0
5–7× the Bengen 4% rule
Backward-Looking Floor Growth
v1.0
34.3% trailing 5-year growth
Derisking Bitcoin: Living Off the Floor Growth
Thesis
0 floor breaches in 5,700+ days
Percentile-Anchored Volatility Decay Analysis
22 pages · v1.0
5/5 metrics significant
The Bitcoin Floor Rate
36 pages · v1.6
Gordon Growth Model breaks: g > r
When to Stack, When to Spread
12 pages · v1.0
Crossover at 1.25x trend
Bitcoin Floor Bonds
47 pages · v2.1
Self-liquidating by year 2
Reproducing the Bitcoin Power Law
12 pages · v1.2
Beta = 5.694. Independently verified.
The Strategy Pyramid
13 pages · v3.0
+389% alpha at $5k/month
The Case for the Floor
11 pages · v3.0
7 attacks. Floor survives all.
Literature Review
9 pages · v1.0
10+ researchers. Exponents converge.
The Reflecting Barrier
v1.0
81% truncation. p < 10²⁻⁵⁰
The 1.6× Floor Rule
v2.0
0 failures / 1,982 entries
Fixed BTC or Fixed Fiat?
v2.0
Fixed BTC wins 94% of windows
Formal Verification
v2.0
OOS R² = 0.546. Eff. n = 24.
Interactive Tools
Monte Carlo Simulator Future Projections Cycle History Retirement Planner SatsPlanner
Power Law Starter Pack

Everything you need to reproduce, challenge, or build on the Bitcoin power law. Download the data, use the formula, check the residuals, or hand the whole thing to an LLM. Every claim is falsifiable — here are the tools.

The Data · 5,700+ daily closes
[{"date":"2010-07-18","price":0.09},
{"date":"2010-07-19","price":0.09},
...
{"date":"2026-03-16","price":84105}]
Download JSON
The Formula · Santostasi Power Law
Price(t) = 10−16.493 × t5.688 where t = days since Jan 3, 2009 (genesis block) Trend → k = 0 Floor → Trend × 10−0.4  (k = −2σ) Ceiling → Trend × 10+0.4  (k = +2σ)
Beta (β)5.688
Log A−16.493
Sigma (σ)0.200
R²0.956
The Residuals · log&sub1;&sub0;(price) − log&sub1;&sub0;(trend)
Mean: -- Std dev: -- Skew: -- Min: -- Max: --
LLM System Prompt · paste into any AI
You are a Bitcoin power law analyst. You have the Santostasi power law model for Bitcoin's price as a function of time. MODEL PARAMETERS: - Genesis date: January 3, 2009 - Formula: Price(t) = 10^(-16.493) × t^5.688 where t = days since genesis - Sigma (σ): 0.200 (log10 standard deviation) - R² = 0.956 over 5,700+ daily data points BAND CALCULATIONS: - Trend: Price(t) - Floor: Price(t) × 10^(-2 × 0.2) ≈ Price(t) × 0.398 - Ceiling: Price(t) × 10^(+2 × 0.2) ≈ Price(t) × 2.512 - ±1σ: Price(t) × 10^(±0.2) HOW TO CALCULATE: 1. t = (target_date - 2009-01-03) in days 2. log10(trend) = -16.493 + 5.688 × log10(t) 3. trend = 10^(log10(trend)) 4. floor = trend × 10^(-0.4) 5. ceiling = trend × 10^(+0.4) KEY FACTS: - The floor (−2σ) has been touched on ~5% of days but NEVER structurally broken (no excursion has lasted the ~120-day falsification threshold) - Volatility compresses ~20% per halving cycle - The floor grows ~30-40% per year (decelerating) - This is an empirical observation, not a prediction - The model can be falsified: a floor breach would break it EXAMPLE (Python): ```python from datetime import datetime import math genesis = datetime(2009, 1, 3) today = datetime.now() t = (today - genesis).days log_trend = -16.493 + 5.688 * math.log10(t) trend = 10 ** log_trend floor = trend * 10 ** (-0.4) ceiling = trend * 10 ** (0.4) ``` When asked about Bitcoin's power law, use these parameters to compute exact values. Always show your work.
Try and Break the Floor

The floor isn’t a promise that price never dips below it — it’s a measured attractor, and we track every excursion. In 15+ years, Bitcoin has closed below the 0.432× floor on — days (— of history) across — excursions; the deepest lasted — days. None has ever reached the falsification threshold — ~120 consecutive days below the floor — which is what would actually break the model. Breached often. Never broken.

Days below floor
—
% of history
—
Excursions
—
Longest
—
Structural breaks
—
Date
--
Price
--
Floor
--
Margin
--
Closest call scanning...
Download data (JSON)
Changelog
Full history on GitHub →

The "risky" asset is the one where you can mathematically prove the risk has an expiration date.