An Excel formula from 2013: why it “promises” Bitcoin $251,000 in 2030 and $1.19 million in 2036—and why this isn’t a forecast
DVA ANALYTICS • FACT -> MECHANISM -> ECONOMICS -> RISK -> SCENARIOS -> DECISION
A single trend line plotted in Excel more than 13 years ago still attracts the attention of Bitcoin enthusiasts. If extended into the future, it gives us reference points of about $251,000 in 2030 and $1.19 million in 2036.
Can a simple mathematical formula predict the price of an asset ten years from now? Why does it still look convincing? And where is the line between a mathematical model and an investment forecast?
To answer these questions, let’s examine the formula’s history, how it works, its statistical limitations, and possible scenarios for a long-term BTC holder.
FACT — a chance discovery, not a prophecy
On February 13, 2013, a Bitcointalk forum user under the pseudonym dacoinminster published a chart titled “This is not a bubble.”
At the time, Bitcoin was worth approximately $25, and its market price history covered only a few years.
The author was not creating a comprehensive economic theory. He was trying to show that after sharp fluctuations, Bitcoin could remain within a long-term trend rather than existing solely inside a speculative bubble.
To do this, he used a standard Excel function—a trendline. The program suggested a power-law relationship that later became known as one of the early versions of the Bitcoin Power Law.
The formula looks like this:
P(t) = 4,41877086 × 10⁻¹⁷ × t⁵·⁵⁹⁸⁰⁶⁹²
Here, P(t) is the calculated price of BTC in US dollars, and t is the number of days since January 3, 2009, the date the first Bitcoin block was created. The coefficient and exponent determine the shape of the mathematical curve.
The model’s key feature is its simplicity. It uses only the age of the network. It has no separate variables for halvings, institutional demand, capital inflows, regulation, or macroeconomic conditions.
It is precisely the fact that the original formula has remained unchanged that makes it interesting for historical analysis: its calculated trajectory can be compared with the price that took shape after 2013.
But an unchanged equation does not mean an unchanged forecast accuracy.
MECHANISM — how the power-law model works
In simplified terms, the model says that Bitcoin’s long-term price is related to the age of the network by a power-law relationship.
Unlike a linear model, in which the price increases by the same absolute amount for each unit of time, a power function allows for a nonlinear trajectory. With an exponent of approximately 5.6, its calculated value increases at an ever-faster rate in absolute terms.
However, this does not mean that BTC’s actual price must rise according to the same law. The equation describes a mathematical curve, not a mechanism for determining the market price.
The model does not answer questions such as how much capital will flow into Bitcoin, how demand from retail and institutional investors will change, what the effects of regulatory decisions will be, whether demand for BTC as a store of value will persist, or how global liquidity, interest rates, and competition from other assets will affect it.
The formula contains none of these variables.
That is why it is important to distinguish between two statements. First: the formula calculates the value that corresponds to a given date on its mathematical curve. Second: Bitcoin’s market price will actually reach that level on that date.
The first can be verified mathematically. The second is a hypothesis about the future that requires separate justification.
ECONOMICS — where $251,000 and $1.19 million come from
If the original power-law curve is extended into the future, it gives two reference points: approximately $251,000 in January 2030 and $1.19 million in September 2036.
The difference between these values is approximately 4.74 times. This is the result of extending the curve, not an estimate of guaranteed returns on Bitcoin.
Model versus actual price
According to published calculations, at the end of October 2026 the model’s reference value was approximately $98,300, while the actual price of BTC was around $80,800.
Thus, the market price was approximately 18% below the calculated level. In other words, the model indicated a higher price than the one at which the asset was trading.
This proves neither that the formula is right nor that it is wrong. The price can deviate from a historical trend for a long time. But this example clearly shows why the curve’s value should not be equated with the actual market price.
These figures refer to the end of October 2026 and are not current quotes for any other date.
Derived scenarios — separate from the original formula
Some scenarios derived from the power-law model suggest a possible peak of around $510,000 in late 2029, a low of around $175,000 in 2030–2031, and a peak of around $1.14 million in 2033.
These figures should be treated separately from the original formula. Calculating future peaks and lows requires additional assumptions about price fluctuations around the trend. The power function itself does not determine the dates of market highs and lows.
So, $251,000 and $1.19 million are calculated values from extending the curve, while peak-and-trough scenarios depend on additional methodology.
Why the formula still attracts attention
The model’s main appeal is its ability to describe part of BTC’s historical dynamics with a single, simple curve.
Reconstructions of the Bitcoin Power Law often compare the distance between market peaks and the calculated line. These comparisons cite the curve being exceeded by approximately 16 times at the 2013 peak, nine times in 2017, four times in 2021, and around 1.8 times in 2025.
These ratios depend on how the peak date is defined, which price source is used, and which version of the model is chosen for comparison. Such figures should therefore be checked using a consistent methodology before publication.
Supporters of the model also point to the behavior of market lows. In some historical comparisons, these were near 0.55–0.7 of the calculated level.
This gave rise to the idea of “volatility compression” around a long-term power-law backbone. According to this interpretation, as market capitalization grows and the market matures, Bitcoin’s relative fluctuations may decrease.
However, even if the amplitude of fluctuations has historically decreased, that does not prove the trend will necessarily continue. The results are affected by the choice of historical periods, the measurement methodology, and the shape of the curve itself.
Volatility compression is a hypothesis that can be tested, not a law that guarantees BTC’s future behavior.
RISK — the trap of a beautiful curve
The most important methodological problem is that a model may describe the past well but prove unreliable for forecasting the future.
1. Overfitting
The equation’s parameters were fitted to a specific historical dataset. A good fit to that data does not necessarily mean the model will be just as accurate on new observations.
It is particularly risky to evaluate a model only on the period on which it was built. A more reliable test requires using data that were not included when fitting the parameters, as well as comparing the model with simpler alternatives.
2. Spurious regression
Two variables can show a strong statistical relationship without a proven causal mechanism.
Bitcoin’s price and the age of its network changed over the same period. But the existence of a relationship does not prove that the network’s age causes the price to rise or that the relationship will persist.
With financial time series, particular attention should be paid to non-stationarity, autocorrelation, and the properties of regression residuals. Without the appropriate tests, a curve’s close fit to historical data may create a false sense of reliability.
3. R² is not the probability of success
Different accounts of this historical model report different values for the coefficient of determination, R². The result depends on the data used, the observation period, and the way the regression is constructed.
R² describes how well a model fits a particular dataset under a specific methodology. It does not indicate the probability that BTC will reach $251,000 in 2030, nor does it guarantee accuracy over a ten-year horizon.
4. No fundamental variables
The Bitcoin market depends on supply and demand, liquidity, regulatory decisions, technological changes, investor behavior, and competition from other assets.
The dacoinminster formula does not model these factors. It cannot explain why the price will rise, slow down, or fall. It only calculates a value according to a given relationship.
5. Aggressive long-term extrapolation
With an exponent of around 5.6, the function continues to grow nonlinearly. Over a distant time horizon, small changes in assumptions or in the model itself can have a significant effect on how the results are interpreted.
Calculating a value for 2036 is mathematically straightforward. It is much harder to prove that the historical relationship will still hold by then.
That is why a forecast for 2036 calls for greater caution than using the curve as one of the tools for analyzing the current market.
SCENARIOS — three possible outcomes
Rather than treating the formula’s future values as a promise, it is more useful to consider three scenarios.
Scenario A — the historical trend continues. The price of BTC continues to fluctuate around the power-law curve. Its values may remain long-term reference points for comparison, but they do not guarantee that specific levels will be reached on specific dates.
Scenario B — growth slows. As market capitalization increases, the structure of demand changes and relative growth rates decline. The price may remain below the curve for a long time, and the model’s accuracy may gradually deteriorate.
Scenario C — a structural break. Regulatory changes, technological risks, shifts in demand, or increased competition change market conditions. The historical relationship ceases to be a useful description of future prices.
These are not forecasts with assigned probabilities. They are analytical frameworks that help avoid reducing an uncertain future to a single number.
DECISION — how to use the model in an HODL strategy
For a long-term BTC holder, the power-law model can be a useful supplementary tool. It allows them to compare the market price with the historical trajectory and assess whether the previous pattern still holds.
However, turning it into a standalone trading strategy is risky.
A rational approach means comparing BTC’s actual price with the curve without equating the two; testing the model on new data and comparing it with alternative methods; assessing demand, liquidity, macroeconomic conditions, and regulatory risks; not treating 2030 or 2036 target levels as a guarantee of the portfolio’s future value; and sizing the position according to one’s investment horizon and ability to withstand a significant decline.
Likewise, it is not wise to borrow money just because a mathematical model indicates a higher future price.
HODL is not faith in a single curve. It is a strategy that should account both for the long-term hypothesis about an asset’s value and for the possibility that the future will differ from the past.
Conclusion — mathematics makes no promises
The 2013 Excel formula remains an interesting example of how a simple mathematical model can describe the long-term trajectory of a complex financial asset.
Its value lies in the ability to test a historical hypothesis against new data, compare the market price with the calculated line, and ask questions about changes in BTC’s behavior.
But $251,000 in 2030 and $1.19 million in 2036 are the results of extrapolation, not a promise from the market. The formula does not account for future economic conditions, does not prove a causal relationship between time and price, and does not guarantee that the historical pattern will persist.
Mathematics helps formulate a hypothesis. Statistics tests whether it is justified. The market determines the actual price.
DVA ANALYTICS — FACT -> MECHANISM -> ECONOMICS -> RISK -> SCENARIOS -> DECISION.
DVA — facts without hype.
Not financial advice. Preserving value and time.
#DVA #HODL #BTC☀️
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ECONOMICS — where do $251,000 and $1.19 million come from?