There’s a new, ultra-bullish Bitcoin price model that is making the rounds online—and its creator claims his forecasts are based on math and science.
Envisioned as early as 2019, the “Bitcoin Power Law” attempts to map Bitcoin’s long-term price appreciation on a log-log scale, meaning that both price and time scale exponentially along its y-axis and x-axis respectively.
The result? A chart that rises up and to the right in a roughly straight line, capturing the range of Bitcoin’s highs and lows with what proponents call “amazing” accuracy.
“When we try to understand data, we always like it when data is linear,” said Giovanni Santostasi, a former physics professor at McNeese State University, regarding his model during an interview with YouTuber Andrei Jikh last month.
This graph is simply amazing. When you plot Price and Time both in log scale, it’s clear Bitcoin is just on a relentless power law. HT/ @moneyordebt pic.twitter.com/9josXLiyZH
— Fred Krueger (@dotkrueger) February 2, 2024
According to the Oxford Dictionary, a Power Law is “a relationship between two quantities such that one is proportional to a fixed power of the other.” The relationship should occur irrespective of the initial size of those quantities, meaning it scales indefinitely in a straight line.
“In nature, there are many of these relationships, which are straight lines,” added the astrophysicist, providing Kepler’s laws of planetary motion as an example. The law identifies a power law relationship that uses every planet’s distance from the sun to calculate the time it takes for that planet to orbit around the sun—without fail.
Power laws have been discovered in a vast number of seemingly independent places. They can even appear in the financial realm, predicting returns on risky venture capital investments, the average waiting time of a stock’s directional change, and now apparently the price of Bitcoin.
“Many didn’t believe me and said the past doesn’t predict the future,” wrote Santostasi in a Reddit post last month, revisiting his years-old model. “Well, after five years, it turns out that BTC continues its power law behavior with a similar exponent.”
Algebraically, the BTC power law is expressed as such: Estimated Price=A * (days from GB)^n.
GB refers to Bitcoin’s Genesis Block, which was mined on January 3, 2009. A is equal to 10^-17, and n equals 5.8.
When calculated based on today’s date, the model says Bitcoin’s price should be $64,564—not a far cry from where short-term analysts think it could be in just a few months.
Santostasi says his model predicts that BTC will touch its cycle “peak” at $210,000 in January 2026, before crashing to its “bottom” later that year at $60,000. In the short term, he says, the price of Bitcoin should go no lower than $35,000, and by 2033, should be at $1 million.
To be sure, there’s no guarantee that Bitcoin’s price will follow this or any projection model. Naturally, some have expressed fear that the model could give investors unreasonable expectations for BTC, and will eventually be broken—much like PlanB’s now widely criticized stock-to-flow model that was popularized in 2021.
While Santostasi respects certain elements of the stock-to-flow model, he largely criticizes it for projecting indefinite, exponential growth in Bitcoin’s price. Instead, the physicist likens Bitcoin’s growth to that of a city, echoing Bitcoin billionaire Michael Saylor’s description of Bitcoin as “a shining city in cyberspace.”
#BTC @saylor analogy that BTC is a “shining city in cyberspace” is not just metaphorical bullshit.
It is true (not sure he is aware of the math behind it but he has great math and science intuition).
The math of cities (how they grow, what they produce, how people interact in… pic.twitter.com/bLrlHISCQY— BTC_POWER_LAW (@Giovann35084111) February 1, 2024
“There is no S adoption curve in BTC,” he wrote to Twitter on Tuesday, adding that “power laws govern the growth of cities.”
“I find it fascinating that it grows like a city and a more stable and reliable model and asset than a get-rich-quick scheme,” he added.
Edited by Andrew Hayward
