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STOK

Stoke TherapeuticsC
Nasdaq / Pharmaceuticals, Biotechnology & Life Sciences
Last Price
At close
2026-06-02
View Chart
Current thesis
The strongest post-earnings read is that management combined new 4-year OLE cognition/behavior and seizure durability data with an EMPEROR enrollment-completion target for June 2026, while ending Q1 with $411.0 million of cash expected to fund operations into 2028. That keeps the lead-asset path intact and preserves optionality to the mid-2027 readout and planned NDA start.
Posture
Mixed
Lead driver
Sentiment
What changed
Sentiment remains the lead driver in the composite, 7D delta -1.2.
What can break
EMPEROR is still the central value driver, and Phase 3 efficacy/readout risk remains unresolved until mid-2027 despite June 2026 enrollment completion guidance. [#8-K-2026-05-07]
Momentum
20
Value
58
Sentiment
69
Setup hits (3d)
0 · Net Neutral
AI TargetsBase $35.00 · Bull $46.00 · Bear $24.00
Data freshness
Prices
As of 2026-06-02
Fundamentals
As of 2026-06-02 • Vendor: Data Vendor v1
Scores
As of 2026-06-02 • Model: HYBRID_IC_RP
AI Memo
As of 2026-05-08 • Model: RankAlpha Sentiment Codex
Investment thesis
As of 2026-06-02
Supporting evidence
What
Grade C · Mixed
Confidence Medium · Net Neutral
Target $41.70
Why
Momentum20 · Δ7d -3.7
Value58 · Δ7d -0.0
Sentiment69 · Δ7d -1.2
So what
Balanced signals (Net Neutral). Wait for confirmation before sizing up.
Lead driver: Sentiment · See AI snapshot
Momentum
20
34% active weight
Current posture
7d trendFlat
Δ7d
-3.7
Δ21d
-37.9
Value
58
32% active weight
Current posture
7d trendFlat
Δ7d
-0.0
Δ21d
+0.5
Sentiment
69
33% active weight
Current posture
7d trendSoftening
Δ7d
-1.2
Δ21d
+15.9
Why this grade

Composite grade C. Momentum 19.8 / Value 58.1 / Sentiment 69.3

Fundamentals (TTM)
As of 2026-06-02
Market Cap
$1.79B
Beta
1.10
Shares Out
57.12M
P/E (TTM)
49.3
P/S (TTM)
9.04
P/FCF (TTM)
35.50
Rev YoY
+117.2%
EPS YoY
-39.5%
Gross Margin
-
Op Margin
+13.2%
Net Debt
-$216.9M
Current Ratio
6.53
As of 2026-06-02 • Updated nightlySource: Internal modelMethodology