"Deferred, stated on the dashboard as deferred. No synthetic CAPE." — the gauge spec, stating an intention this lesson will end up checking
When the data genuinely is not there
The previous lessons were about approximations that are honest and available. This one is about the case where no honest approximation exists at all.
The long-window valuation gauge needs ten years of real earnings at index level. For the US, an academic assembled that series. For the Korean and Japanese markets, no equivalent public series exists. Not hard to obtain — absent.
The options are the familiar three, and the middle one is the trap.
Ship it with worse data. Assemble something from partial inputs and call it by the same name. Now the dashboard has a gauge that is not comparable to its US sibling, sitting right next to it, under an identical label. This is worse than not shipping and worse than saying nothing.
Ship nothing and say nothing. The card is absent. A reader notices the asymmetry and cannot tell whether it is a bug, a loading state, a permissions issue, or a deliberate choice.
Ship the absence. A surface that says the gauge is deferred, why, and what to look at instead.
Which of those this product actually does depends on which deferral you look at, and the split is worth more than the tidy version would be. The sector deferral is genuinely shipped: the dashboard carries it in prose, names all three probed paths, and dates the decision. The long-window gauge deferral is not — it is stated in the gauge spec, in exactly the words "deferred, stated on the dashboard as deferred," and the dashboard says nothing of the kind. There is no card, no reason, no named substitute in the interface at all.
So the model case here is the sector one, and the other is this lesson's own moral pointed back at the product: a deferral that lives only in a design document is the gap, not the design. Two deferrals, one team, one week apart, and only one of them made it to the reader — which is roughly the hit rate you should expect from a rule that lives in prose rather than in a check.
The substitute matters as much as the deferral
The third option is only strong because of what comes with it. The deferral names a substitute: the index price-to-earnings ratio, in percentile against its own accumulated history.
Notice what that substitution preserves and what it gives up. It gives up the smoothing — the long-window metric exists precisely to average out the earnings cycle, and the substitute does not do that. It preserves the question: expensive relative to its own history? That is what a reader actually wants to know, and it can be answered with data that exists.
So the deferral is not a hole. It is a downgrade, named, with the reader pointed at the best available answer to their underlying question rather than to the unavailable answer to their literal one.
Deferrals that were measured, not assumed
The same discipline appears in the sector-aggregate deferral for one market, and there the record is even more useful: three specific paths were probed and each was closed for a stated reason — one source required a session, one sat behind a bot wall, one carried no usable fundamentals on the available library.
That is a deferral you can act on. A future reader knows exactly which three doors were tried, which means they neither repeat the work nor assume it was never done. And the reopening condition is named: revisit if that source publishes a real interface.