This restates the distribution as a running total: pick any price on the axis and it reports what share of supply would be showing a gain with spot sitting there. It converts a photograph of today into an answer about anywhere.

That is the question the histogram cannot address. Knowing where the walls are is one thing; knowing what a move through them would do to the market’s holders is what this view supplies.

What it actually measures

The steep stretches are where the leverage sits. A small move through one of them flips a great many holders between profit and loss, while the same move through a flat stretch changes almost nothing.

Drawing the two cohorts separately shows the gap between them. That gap answers who breaks first, which is a more useful question than how much supply is underwater in total.

Long-term holders being the stressed side is the unusual reading. They are normally furthest from loss, so the rare occasions when they are not have been worth paying attention to.

Behavioural leverage is concentrated in a few narrow stretches

Price is usually thought of as continuous, with each percentage move worth roughly the same as the last. In terms of how many people it affects, it is not remotely continuous.

A few percent through a steep stretch of this curve changes more holders’ positions than a much larger move through a flat one. Knowing where those stretches are is knowing where a modest move would do disproportionate work.

Break Level: the distance to a change matters as much as its size

The highlighted buckets are the only ones whose status the move would alter. Everything else keeps the side it is already on, and so the highlight is a much smaller set than the whole chart.

A large cluster far from spot and a modest one just beneath it are usually read the same way, as supply that would come under pressure in a decline. They are not equivalent at all.

The near one needs almost no movement to become relevant and the distant one needs a great deal. Ranking clusters by how far price would have to travel to reach them is what turns a static picture into an assessment of risk.

What it does not tell you

Whether anybody acts is outside its scope entirely. Flipping into loss is a change in position, not a decision, and most holders do nothing about it beyond noticing that the number went red.

It assumes the distribution stays still while price moves. In practice coins change hands during any real move, which reshapes the curve as it is being traversed, so a deep test is less reliable than a shallow one.

The cohort split inherits its boundary from a convention. Coins either side of the age threshold are treated as different populations despite sitting next to each other, so a curve that separates cleanly may be separating two halves of one crowd.

How to read it

STH Stressed. Recent buyers are closer to loss than patient holders at the price being tested.

LTH Stressed. The patient cohort sits nearer to loss than the recent one, an inversion that shows up seldom.

Even Stress. The two cohorts sit at much the same distance from breakeven.

The URPD dashboard draws Supply Stress Curve alongside Break Level, Cohort Split and Profit / Loss.

Common questions

What does the curve show?

Pick a price and it tells you what fraction of supply would be showing a gain with spot there. Where the line turns steep, very little movement changes a great many positions.

Why do the steep sections matter?

Because those are the stretches where price does the most work on people. A few percent through one shifts more holders than a far larger move through a flat section.

What does the gap between cohorts say?

Which group is nearer the pain. Patient holders are normally furthest from loss, so the occasions when they are the stressed side are rare and have been worth noticing.

Does flipping into loss mean selling?

No, and the distinction matters. A holder crossing into loss has changed position, not made a decision, and most of them do nothing at all about it.

Why drag a handle rather than read the chart?

Because it answers one specific question directly. Setting a price and reading what happens there is more useful than inferring it from a shape.

What does the highlight mark?

The buckets whose side would change at the price being tested. Everything else keeps the status it already has, so the highlight is the whole of what the move would touch.

Does the reference layer change?

It is the distribution as it stands, kept behind the hypothetical one so the difference is visible rather than only the result. A real move would reshape it, which this deliberately does not attempt to model.