Bitcoin's Price Comes From Two Power Laws
#bitcoin #powerlaw #mathematics
Original timestamp: 00:48:32
Bitcoin's Price Comes From Two Power Laws
#bitcoin #powerlaw #mathematics
Original timestamp: 00:48:32
I looked at a historical price of bitcoin recently on a semi log plot and was surprised that it's long term growth rate seems to be slowing in a predictable way. I looked into it and it turns out there is a power law relationship between bitcoin price and time. Here is a chart showing the relationship https://charts.bitbo.io/long-term-power-law/
I am curious what economics are behind this relationship. I looked into it a little but there was lots of crypto hype articles to wade through...I am not interested in "investing" in bitcoin and think this pattern could easily end if conditions change. Still it is pretty cool that the pattern has held since 2009. I would like to know what has driven this behavior.

VCs Aren’t Just Funding AI Startups—They’re Picking the Kings
New playbook in AI: mega‑funds pour huge checks, exclusive compute access, and distribution deals into a tiny set of startups—before the market is even formed. It’s not “may the best product win,” it’s “may the best‑connected company start 20 laps ahead.”
If you’re outside those capital + GPU networks, you’re not competing in the same race.

Glad to be granted a patent on prediction & control of blowout in combustion systems by United States Patent and Trademark Office. Our invention predicts the exact blowout time significantly earlier using a log periodic power law & performs control action to prevent the blowout.
#USPatents #IntellectualProperty #Blowout #IITMadras #Aviation #Innovation #JetEngine #STEM #Aerospace #Statisticalphysics #powerlaw #Complexsystems #Sustainability #scaleinvariance #Logperiodicity #Combustion
@skewray True!
1/f distributions --- one of my advisors told me not to study that because it would destroy my career. His name was Per Bak. I ignored him. He was right tho
Lévy distributions are a nice example of a convolutionally stable power law with non-Gaussian behavior. Cauchy distributions, despite having no finite mean or variance are also stable. α-stable.
You do need infinite data to know the true asymptotic shape of a distribution ...
It is possible to measure the fatness of the tails of a distribution ... But I've been told that "α-stable laws are both beautiful and frustrating: they’re mathematically neat, but empirically very hard to confirm.", so yeah, what Bak said