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STRL

Sterling InfrastructureF
Nasdaq / Capital Goods
Last Price
At close
2026-07-20
View Chart
Current thesis
The post-earnings bull read is straightforward: Sterling produced a very large Q1 beat, raised full-year guidance, showed strong cash generation, and expanded both signed and combined backlog with visible data-center and semiconductor work [#8-K-2026-05-04]. If the market gives credit to the enlarged E-Infrastructure runway and CEC cross-sell, current estimates may still need to move higher.
Posture
Defensive
Lead driver
Value
What changed
Value remains the lead driver in the composite, 7D delta +0.2.
What can break
A large part of the upside thesis depends on sustained mission-critical project awards, backlog conversion, and future-phase work that can slip, resize, or convert later than expected.
Momentum
30
Value
48
Sentiment
23
Setup hits (3d)
0 · Net Neutral
AI TargetsBase $500.00 · Bull $620.00 · Bear $420.00
Data freshness
Prices
As of 2026-07-20
Fundamentals
As of 2026-07-21 • Vendor: Data Vendor v1
Scores
As of 2026-07-20 • Model: HYBRID_IC_RP
AI Memo
As of 2026-05-04 • Model: RankAlpha Sentiment Codex
Investment thesis
As of 2026-07-20
Supporting evidence
What
Grade F · Defensive
Confidence Medium · Net Neutral
Target $956.43
Why
Momentum30 · Δ7d -34.6
Value48 · Δ7d +0.2
Sentiment23 · Δ7d +2.7
So what
Weak posture (Net Neutral). Prioritize risk control and patience.
Lead driver: Value · See fundamentals
Momentum
30
26% active weight
Current posture
7d trendFlat
Δ7d
-34.6
Δ21d
-65.6
Value
48
39% active weight
Current posture
7d trendFlat
Δ7d
+0.2
Δ21d
+1.2
Sentiment
23
34% active weight
Current posture
7d trendImproving
Δ7d
+2.7
Δ21d
+14.3
Why this grade

Composite grade F. Momentum 29.7 / Value 48.0 / Sentiment 23.4

Fundamentals (TTM)
As of 2026-07-21
Market Cap
$21.31B
Beta
1.51
Shares Out
30.69M
P/E (TTM)
32.0
P/S (TTM)
4.50
P/FCF (TTM)
27.79
Rev YoY
+91.6%
EPS YoY
+141.9%
Gross Margin
+22.4%
Op Margin
+19.7%
Net Debt
-$40.81M
Current Ratio
1.10
As of 2026-07-20 • Updated nightlySource: Internal modelMethodology