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ENVX

EnovixD
Nasdaq / Capital Goods
Last Price
At close
2026-06-02
View Chart
Current thesis
The bull case is that Q1 showed real operating progress: revenue beat guidance, gross margin improved, smart-eyewear production started, and management described a clearer smartphone qualification path plus 2H26 system-level deployment goals. If qualification closes, the gap between the $6.11 anchor price and the roughly $15.39 median target could narrow quickly.
Posture
Defensive
Lead driver
Momentum
What changed
3 setup hits (3d) with net bullish as of 2026-06-02.
What can break
Balance-sheet leverage is not near-term distress, but Enovix still carries $172.5M of 2028 converts and $360.0M of 2030 converts, making execution setbacks more costly if capital-market access worsens. [#10-Q-2026-05-14]
Momentum
72
Value
33
Sentiment
30
Setup hits (3d)
3 · Net Bullish
AI TargetsBase $6.75 · Bull $10.00 · Bear $4.50
Data freshness
Prices
As of 2026-06-02
Fundamentals
As of 2026-06-01 • Vendor: Data Vendor v1
Scores
As of 2026-06-02 • Model: HYBRID_IC_RP
AI Memo
As of 2026-05-16 • Model: RankAlpha Sentiment Codex
Investment thesis
As of 2026-06-02
Supporting evidence
What
Grade D · Defensive
Confidence Medium · Net Bullish
Target $15.39
Why
Momentum72 · Δ7d +8.1
Value33 · Δ7d -0.0
Sentiment30 · Δ7d -21.1
So what
Weak posture (Net Bullish). Prioritize risk control and patience.
Lead driver: Momentum · See technicals
Momentum
72
34% active weight
Current posture
7d trendImproving
Δ7d
+8.1
Δ21d
+1.7
Value
33
32% active weight
Current posture
7d trendFlat
Δ7d
-0.0
Δ21d
-0.0
Sentiment
30
33% active weight
Current posture
7d trendSoftening
Δ7d
-21.1
Δ21d
-
Why this grade

Composite grade D. Momentum 72.4 / Value 33.4 / Sentiment 29.7

Fundamentals (TTM)
As of 2026-06-01
Market Cap
$1.87B
Beta
2.12
Shares Out
215.82M
P/E (TTM) · Derived
-11.5
P/S (TTM)
62.24
P/FCF (TTM) · Derived
-14.45
Rev YoY
+85.1%
EPS YoY
-104.0%
Gross Margin
+15.4%
Op Margin
-530.6%
Net Debt
-$93.6M
Current Ratio
9.72
As of 2026-06-02 • Updated nightlySource: Internal modelMethodology