Back to Rankings

DGII

Digi InternationalB
Nasdaq / Technology Hardware & Equipment
Last Price
At close
2026-07-20
View Chart
Current thesis
The post-earnings bull read is that Digi delivered a beat versus the AP/Zacks consensus frame, set records for revenue, ARR, and operating cash flow, and raised full-year guidance while both segments posted growth [#8-K-2026-05-06]. That supports the deterministic positive prior, especially if investors reward the recurring-revenue mix rather than treating the quarter as acquisition-assisted only.
Posture
Constructive
Lead driver
Value
What changed
Value remains the lead driver in the composite, 7D delta +0.0.
What can break
Execution risk if Particle and Jolt integration lifts ARR but fails to deliver enough organic cross-sell, margin expansion, or debt paydown.
Momentum
83
Value
57
Sentiment
37
Setup hits (3d)
0 · Net Neutral
AI TargetsBase $58.00 · Bull $68.00 · Bear $47.00
Data freshness
Prices
As of 2026-07-20
Fundamentals
As of 2026-07-17 • Vendor: Data Vendor v1
Scores
As of 2026-07-20 • Model: HYBRID_IC_RP
AI Memo
As of 2026-05-08 • Model: RankAlpha Sentiment Codex
Investment thesis
As of 2026-07-20
Supporting evidence
What
Grade B · Constructive
Confidence Medium · Net Neutral
Target $72.20
Why
Momentum83 · Δ7d +5.8
Value57 · Δ7d +0.0
Sentiment37 · Δ7d +2.1
So what
Strength-led posture (Net Neutral). Favor watchlist adds and disciplined entries.
Lead driver: Value · See fundamentals
Momentum
83
26% active weight
Current posture
7d trendFlat
Δ7d
+5.8
Δ21d
-0.7
Value
57
39% active weight
Current posture
7d trendFlat
Δ7d
+0.0
Δ21d
+1.4
Sentiment
37
34% active weight
Current posture
7d trendImproving
Δ7d
+2.1
Δ21d
+6.6
Why this grade

Composite grade B. Momentum 83.0 / Value 57.0 / Sentiment 36.9

Fundamentals (TTM)
As of 2026-07-17
Market Cap
$2.41B
Beta
0.85
Shares Out
37.7M
P/E (TTM)
40.8
P/S (TTM)
3.86
P/FCF (TTM)
15.75
Rev YoY
+25.1%
EPS YoY
+5.0%
Gross Margin
+60.3%
Op Margin
+13.1%
Net Debt
$149.28M
Current Ratio
1.11
As of 2026-07-20 • Updated nightlySource: Internal modelMethodology