GVA vs KBR

Granite Construction Incorporat vs KBR, Inc. — Valuation Comparison 2026

GVA

Heavy Construction Other Than Bldg Const - Contractors
Granite Construction Incorporat
Quality
9.5
out of 10
Value Trap
15
SAFE
Price
$136.84
Last close
Models
13/13
Active
VS

KBR

Heavy Construction Other Than Bldg Const - Contractors
KBR, Inc.
Quality
9.1
out of 10
Value Trap
17
SAFE
Price
$34.95
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType GVA Fair ValueGVA Upside KBR Fair ValueKBR Upside
Bayesian DCF Intrinsic $10.34 -92.0% $62.22 +78.0%
Earnings Power Value Intrinsic $25.45 -81.4% $24.14 -30.9%
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 GVA vs KBR — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

GVA vs KBR — Which Stock Is More Undervalued?

GVA scores higher with a 9.5/10 quality rating vs KBR's 9.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Granite Construction Incorporat (GVA) and KBR, Inc. (KBR) 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.

GVA currently trades at $136.84 with a QOC of 9.5/10, while KBR trades at $34.95 with a QOC of 9.1/10.

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).