PHIN vs REE

PHINIA Inc. vs REE Automotive Ltd. — Valuation Comparison 2026

PHIN

Auto Parts
PHINIA Inc.
Quality
8.9
out of 10
Value Trap
Price
$77.42
Last close
Models
12/13
Active
VS

REE

Auto Parts
REE Automotive Ltd.
Quality
1.5
out of 10
Value Trap
12
SAFE
Price
$0.44
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType PHIN Fair ValuePHIN Upside REE Fair ValueREE Upside
Bayesian DCF Intrinsic $82.17 +6.1% $0.11 -73.8%
Earnings Power Value Intrinsic $14.61 -81.1%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $102.73 +32.7% $0.53 +22.9%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for PHIN vs REE — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PHIN vs REE — Which Stock Is More Undervalued?

PHIN scores higher with a 8.9/10 quality rating vs REE's 1.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing PHINIA Inc. (PHIN) and REE Automotive Ltd. (REE) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

PHIN currently trades at $77.42 with a QOC of 8.9/10, while REE trades at $0.44 with a QOC of 1.5/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).