Correlations
A matrix of Pearson correlations between the metrics that matter most, computed on daily values over a trailing window you choose. Two extra columns correlate each metric with the price 30 and 90 days later, which is the honest way to ask whether anything on-chain runs ahead of the market. Click any cell to see the scatter behind the number.
r runs from −1 to +1 and describes how tightly two series trace a straight line together. +1 means they rise and fall in lockstep, −1 means one rises exactly when the other falls, and 0 means there is no linear relationship. r² is the share of one series' variance the other “explains” linearly: an r of 0.5 is only 25% of the story.
It is computed here on raw daily values, not on returns. Two series that both trend upward over a year will correlate strongly even if their day-to-day moves are unrelated; that is a property of the window, not a discovery.
These columns pair today's value of each metric with the price one or three months later. A metric that correlates with future price more strongly than with today's price is a candidate leading indicator. Compare it against the price's own forward correlation, shown in the KPI row: anything that cannot beat “price predicts price” is not adding information.
Because the shifted price runs out at the end of the window, the last 30 or 90 days contribute nothing to those columns.