MVST vs REE

Microvast Holdings, Inc. vs REE Automotive Ltd. — Valuation Comparison 2026

MVST

Auto Parts
Microvast Holdings, Inc.
Quality
7.4
out of 10
Value Trap
24
SAFE
Price
$1.60
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 MVST Fair ValueMVST Upside REE Fair ValueREE Upside
Bayesian DCF Intrinsic $2.15 +34.4% $0.11 -73.8%
Earnings Power Value Intrinsic $0.15 -90.5%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $2.61 +62.8% $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 MVST vs REE — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MVST vs REE — Which Stock Is More Undervalued?

MVST scores higher with a 7.4/10 quality rating vs REE's 1.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Microvast Holdings, Inc. (MVST) 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.

MVST currently trades at $1.60 with a QOC of 7.4/10, 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).