BWA vs CVGI

BorgWarner Inc. vs Commercial Vehicle Group, Inc. — Valuation Comparison 2026

BWA

Motor Vehicle Parts & Accessories
BorgWarner Inc.
Quality
8.4
out of 10
Value Trap
Price
$71.82
Last close
Models
13/13
Active
VS

CVGI

Motor Vehicle Parts & Accessories
Commercial Vehicle Group, Inc.
Quality
6.9
out of 10
Value Trap
24
SAFE
Price
$5.15
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType BWA Fair ValueBWA Upside CVGI Fair ValueCVGI Upside
Bayesian DCF Intrinsic $83.80 +16.7% $11.28 +119.0%
Earnings Power Value Intrinsic $89.03 +24.0% $2.28 -45.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
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 BWA vs CVGI — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

BWA vs CVGI — Which Stock Is More Undervalued?

BWA scores higher with a 8.4/10 quality rating vs CVGI's 6.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing BorgWarner Inc. (BWA) and Commercial Vehicle Group, Inc. (CVGI) 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.

BWA currently trades at $71.82 with a QOC of 8.4/10, while CVGI trades at $5.15 with a QOC of 6.9/10.

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).