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ONIT

Onity GroupD
NYSE / Financial Services
Last Price
At close
2026-06-03
View Chart
Current thesis
Primary company evidence shows real operating momentum beneath the weak quarter: revenue and servicing/origination volumes grew double digits, book value per share was about $74.81 in the Q1 filing, and the FAR transaction could simplify the model and add $70-$80 million of net proceeds if approved. The packet's median analyst target of $60.0 versus the $38.31 anchor price implies substantial upside if guidance proves conservative.
Posture
Defensive
Lead driver
Value
What changed
Value remains the lead driver in the composite, 7D delta -0.6.
What can break
Elevated FHA delinquencies remain a live issue; the 10-Q notes higher Ginnie Mae delinquencies affecting contingent loan repurchase exposure [#10-Q-2026-05-05].
Momentum
6
Value
63
Sentiment
60
Setup hits (3d)
0 · Net Neutral
AI TargetsBase $41.00 · Bull $55.00 · Bear $27.00
Data freshness
Prices
As of 2026-06-03
Fundamentals
As of 2026-06-02 • Vendor: Data Vendor v1
Scores
As of 2026-06-03 • Model: HYBRID_IC_RP
AI Memo
As of 2026-05-08 • Model: RankAlpha Sentiment Codex
Investment thesis
As of 2026-06-03
Supporting evidence
What
Grade D · Defensive
Confidence Medium · Net Neutral
Target $60.00
Why
Momentum6 · Δ7d +0.5
Value63 · Δ7d -0.6
Sentiment60 · Δ7d -2.1
So what
Weak posture (Net Neutral). Prioritize risk control and patience.
Lead driver: Value · See fundamentals
Momentum
6
34% active weight
Current posture
7d trendFlat
Δ7d
+0.5
Δ21d
-32.5
Value
63
32% active weight
Current posture
7d trendFlat
Δ7d
-0.6
Δ21d
-0.5
Sentiment
60
33% active weight
Current posture
7d trendSoftening
Δ7d
-2.1
Δ21d
+9.1
Why this grade

Composite grade D. Momentum 5.6 / Value 63.1 / Sentiment 59.9

Fundamentals (TTM)
As of 2026-06-02
Market Cap
$308.36M
Beta
1.57
Shares Out
8.06M
P/E (TTM)
13.4
P/S (TTM)
0.36
P/FCF (TTM) · Derived
-0.29
Rev YoY
+5.5%
EPS YoY
-23.6%
Gross Margin
+94.6%
Op Margin
+34.7%
Net Debt
$14.92B
Current Ratio
-
As of 2026-06-03 • Updated nightlySource: Internal modelMethodology