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TATT

TATF
Nasdaq / Capital Goods
Last Price
At close
2026-06-02
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AI scenario view

RankAlpha Sentiment CodexPost-earnings T+3
B+
Bull case
25%
Probability
Target price
$52.00
+28.8% vs current
Most likely
B
Base case
50%
Probability
Target price
$35.50
-12.0% vs current
B-
Bear case
25%
Probability
Target price
$27.50
-31.9% vs current

AI sentiment snapshot

Latest data as of 2026-05-23
Recent news sentiment (30D)
+0.1
Mixed
Company
-
Unavailable
Macro
-
Unavailable
Pulse
-
Unavailable
Sentiment proxy
+41.9
Score

AI commentary

Post-earnings tone is mixed-to-cautious. The company source confirms the revenue/EPS miss but also the backlog and margin/cash-flow positives [#6-K-2026-05-20]. Market coverage indicated shares rose after the print, suggesting investors may have focused on backlog resilience more than the headline miss, but coverage is thin and no clear post-print analyst revisions were available, so that reaction should be treated as tentative rather than thesis-confirming.

RankAlpha Sentiment Codex - 2026-05-23
Open post-earnings memo

Evidence flagged

Coverage is limited for this name. This memo is usable, but confidence is lower and evidence depth is thinner than a standard report.

Impact
tentative
Confidence
-

AI events

2026-05-20eventQ1 2026 print was mixed but backlog stayed highMedium impact

The SEC 6-K shows a mixed quarter: revenue and EPS missed, but gross margin improved, operating cash flow turned positive, and backlog/LTAs were reported at about $580M. That makes the print a near-term check on execution rather than a clean thesis break [#6-K-2026-05-20].

2026-12-31catalystBacklog conversion could reaccelerate growth in H2 2026High impact

Management said the OEM supplier disruptions that weighed on Q1 should resolve over the next few months, which would let the record backlog work through into Q2/H2 growth if execution normalizes [#6-K-2026-05-20].

View full catalyst timeline

Recommendation

N/A

No formal recommendation provided.

Open AI Memo
As of 2026-05-23 • Updated nightlySource: Internal modelMethodology