10-q filing restated figures not matching prior filing, debug mismatch

10-Q restated figures do not match the prior filing

TL;DR

Restated 10-Q figures differ from the prior filing because the company corrected them, and the new filing is the truth going forward. Debug the mismatch by confirming the restatement is real, identifying which periods were restated, and re-basing your historical series on the restated numbers. Never blend pre-restatement and post-restatement figures in one series without marking the break.

The error

(data mismatch, no exception)
10-Q figures for Q1 do not match the Q1 10-Q filed last quarter; prior-period numbers changed

When this helps

• 10-Q figures disagree with the prior quarter's filing
• a historical series breaks at a restatement
• briefing numbers differ from a cached prior filing
• auditing period data after earnings

When it doesn't

• the quarters are simply different periods; Q1 and Q2 legitimately differ
• the filing is an amendment (10-Q/A); that is a different mechanism, see the amendment skill
• you need as-originally-filed numbers; then cite the original explicitly

Works with

EDGAR archives as of 2026; curl 7.x+, python 3.8+. Restatement disclosure is SEC-required.

Steps

1. Confirm the restatement language in the new filing

curl -s -A "IntelBriefingBot/1.0" "https://www.sec.gov/Archives/edgar/data/[cik]/[accession]/[doc]" -o q10.pdf
curl -s -A "IntelBriefingBot/1.0" "https://www.sec.gov/Archives/edgar/data/[cik]/[accession]/[htm-doc]" -o q10.htm
grep -i -m 3 "restat" q10.htm | head -5

Expected: Restatement disclosure lines. Companies must describe what was restated; the language names the affected periods.

2. Map which periods the restatement touches

import re
htm = open("q10.htm").read()
hits = re.findall(r"[Rr]estat.{0,80}", htm)
print("restatement mentions:", len(hits))
for h in hits[:5]:
    print(h[:100])

Expected: The restated periods. A Q2 10-Q can restate Q1; map every affected quarter before rebuilding the series.

3. Re-base the historical series on restated numbers

import json
series = {"Q1": {"revenue": 100, "restated": True}, "Q2": {"revenue": 110, "restated": False}}
open("series_[ticker].json", "w").write(json.dumps(series, indent=2))
print("series re-based; restated quarters flagged")

Expected: A series with restatement flags. Flagging lets the briefing note the break instead of silently mixing old and new.

4. Verify the new figures tie to the restatement note

import re
htm = open("q10.htm").read()
print("mentions prior period adjustment:", "prior period" in htm.lower())
print("filing has comparative columns:", htm.lower().count("restated") not in (0, 1, 2))

Expected: Confirmation the numbers come from the restatement note. Comparative columns labeled restated are the authoritative new figures.

Other ways people phrase this

10-q restated figures mismatch prior filing

The restatement rewrote the prior quarter. Re-base the series; do not average old and new.

restated quarterly numbers debug

Find the restatement note first. It names the periods and the magnitude.

prior period figures changed 10-q

Comparative columns in the new filing carry both old and restated; use the restated.

Why it happens

Companies restate prior quarters when they find errors, and the new 10-Q carries corrected comparative figures. Pipelines that cached the original quarter keep the stale numbers, which then mismatch the restated filing. The new filing is not wrong; the cache is stale, and mixing the two corrupts trend analysis.

Edge cases

• Restatements can span multiple quarters; re-base every affected period, not just the latest.
• Some restatements are immaterial and disclosed briefly; still re-base, the numbers moved.
• Year-to-date figures restate differently than quarterly ones; handle both.
• After re-basing, backfill the briefing's historical charts so trends stay continuous.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_i5gJfWY4P3cKG2iYPT1cWg