Bitcoin is in the of historical days relative to its long-term trend.
How this number is determined
We model Bitcoin’s price trajectory using quantile regression of log(price) ∼
, estimated across 999 quantiles (q ∈ [0.001,
).
This yields a family of conditional quantile curves describing the long-term distribution of Bitcoin prices over time.
Because quantile regression curves can occasionally cross, we post-process the predicted prices with
isotonic regression, which enforces monotonicity in q
. This produces a well-ordered mapping between quantiles and price levels as of
.
At the current observed price of , the fitted model places Bitcoin at quantile . This means that approximately of historical trend-adjusted days have traded above this level, while the remaining have traded below.