Power Law Model Allows Bitcoin to Reach $1 Million by 2033

The Bitcoin Power Law model suggests that the long-term trend price of Bitcoin could approach $1 million by 2033. However, this calculation is based on the historical dynamics of the cryptocurrency and does not guarantee reaching the specified mark.

How the Power Model Works

Physicist Giovanni Santostasi proposed describing the change in Bitcoin's price through the age of the network. In the model, the value is related to time by a power law: as the asset matures, the price continues to grow along the calculated curve, but the relative annual increase gradually slows down.

With a power index of about 5.7, doubling Bitcoin's age corresponds to an increase in the calculated trend price by approximately 52 times. However, each subsequent doubling requires more calendar years.

Santostasi and researcher Stephen Perrinod published a paper in October 2026 in the journal Nonlinear Science. The authors analyzed 5,696 daily observations from July 2010 to February 2026. The resulting model explained about 96% of the variations in the logarithm of Bitcoin's historical price.

The researchers also linked the observed trajectory to the network effect: the growth in the number of addresses and the spread of Bitcoin usage can influence its market valuation. But statistical alignment with past data does not mean that the future rate can be predicted with 96% accuracy.

Why the Forecast Remains Controversial

An independent study by Carlos Bacao and Raquel Menezes showed that the power model outperformed alternative forecasting methods in certain tests over a 12–24 month horizon. However, the authors found that the parameters of the dependency are sensitive to the choice of the initial date and do not prove the existence of an immutable economic law.

Bitcoin's historical price also significantly deviated from the calculated trend during market cycles. Even if the model continues to describe overall growth, the actual value in a specific year could be significantly higher or lower than its line.

Therefore, $1 million by 2033 should be considered a conditional result of extrapolation. Its realization would require the preservation of the long-term pattern on which the model relies. Future demand, liquidity availability, and changes in market participant behavior could lead to different dynamics.