The scorecard's sector view breaks performance down by crypto sector, and the module names the buckets it uses: DeFi, L1, L2, Gaming, AI and others. That is a perfectly reasonable set of labels. It is also, like every sector taxonomy that has ever existed, a set of opinions about what things are, and opinions get revised.
In equities the revision problem is old and largely solved by convention. In crypto it is neither old nor solved, and the revisions are more frequent because the underlying assets change what they are faster than an equity issuer does. A chain ships an inference marketplace and the AI label starts to fit. An L1 launches its own rollup and the L1 and L2 buckets both have a claim. A lending protocol becomes infrastructure that other protocols route through. None of these are errors being corrected. They are the world moving under a label.
The damage is not that the label is wrong. It is that a relabel propagates backwards through every return series computed from it, and nobody notices until a client asks why a number changed.
What one reclassification does to a series you already published
Here is the mechanism, with a constructed example so the arithmetic is visible. These are numbers I made up to show the shape of the problem, not readings from any panel.
Suppose a sector contains eight names and you report an equal-weighted sector return for the quarter of plus 14 percent. One of those eight returned plus 62 percent, and the other seven averaged plus 7.1 percent. Now the taxonomy is updated and that one name is moved to a different sector. Re-run the same query today and the sector's quarterly return is plus 7.1 percent, not plus 14. The trades did not change. The prices did not change. The quarter did not change. The membership function changed, and it changed retroactively for every historical period the query covers.
Two consequences follow, and the second is the expensive one. Your published attribution for that quarter is now unreproducible from your own systems, because the query that produced it returns something else. And your active return against a sector benchmark computed from the same taxonomy has moved without you trading, which means the attribution report you send this quarter contradicts the one you sent two quarters ago on a period that is closed.
Reclassifications also arrive in batches rather than singly, since a taxonomy update usually touches several names at once, so the effect on a diversified sector series is rarely the clean single-name case above.
The mapping table you have to own yourself
If your attribution has to be reproducible across quarters, you cannot store an asset's sector as a property of the asset. You have to store it as a fact with a validity period, in a table you control, populated from whatever your source of labels is.
The minimum schema is five fields. An asset identifier that is stable across ticker changes and chain migrations, since the ticker is not that identifier. A sector identifier. A valid_from date. A valid_to date, open-ended for the current row. And a provenance field recording where the label came from and which version of that source it was.
Two rules govern how it gets used. Every attribution query joins on the mapping table with an as-of date, so the sector applied to a return in March is the sector the asset carried in March. And rows are never updated in place. A reclassification closes the existing row with a valid_to and inserts a new one. The moment somebody runs an UPDATE on a sector column to fix a label, every historical report derived from that table has silently changed and there is no record that it did.
There is a third rule that is less obvious and catches people out. Store the taxonomy itself with a version, not just the assignments. Sectors get added, merged and renamed, and an assignment row pointing at a sector identifier that has since been merged into another one will resolve to the wrong bucket unless the sector definitions are versioned alongside the mappings.
Two tests that find drift before a client does
The first is a reproduction test and it runs monthly. Take a closed quarter for which you have an archived attribution report, re-run the attribution from the vintage as it stood at publication, and diff the sector-level returns against the published figures. They should match to the cent. Then re-run the same quarter using the current taxonomy and diff again. That second diff is your drift, quantified, and it belongs in an operations log with a threshold above which somebody has to explain it.
The second is a membership diff, also monthly, and it is cheap. Count, per sector, how many assets were added, how many dropped, and how many moved in from another sector. A month with three moves is normal maintenance. A month with thirty is a taxonomy revision that arrived without an announcement, and you want to know that before it appears in a quarterly review rather than during one.
Set the threshold on the second test in terms of weight rather than count. Ten small names moving matters less than one name that represents a fifth of the sector's capitalisation, and a count-based alert treats those identically.
Adopting a better taxonomy without breaking the record
Sometimes the new classification is genuinely an improvement, and refusing to adopt it to protect a series is its own kind of failure. The requirement is not that the taxonomy never changes. The requirement is that the change is visible.
The procedure is a dual run. Compute attribution under both the old and the new taxonomy for at least one full reporting period. Publish the primary under the old scheme, show the new one alongside it, and state the changeover date explicitly. On the changeover, the series carries a documented break, and every chart that spans it is annotated at that point.
What you never do is restate history under the new scheme without saying so. A restated series is not more accurate, it is a different measurement wearing the old label, and it destroys the only property that made the historical attribution useful, which is that it describes decisions made with the information available at the time. A portfolio manager who overweighted a sector in March did so under March's definition of that sector. Judging that decision against a definition invented in September is not an evaluation of the decision.
The awkward part of this is that it makes drift visible in a document people read. That is the point. An attribution report that has never once shown a taxonomy break, over several years in a market where assets change what they are every quarter, is not a report describing a stable classification. It is a report that has been quietly restating itself.