DCO vs KRMN

Ducommun Incorporated vs Karman Holdings Inc. — Valuation Comparison 2026

DCO

Aircraft Parts & Auxiliary Equipment, NEC
Ducommun Incorporated
Quality
6.8
out of 10
Value Trap
26
LOW
Price
$152.22
Last close
Models
13/13
Active
VS

KRMN

Aircraft Parts & Auxiliary Equipment, NEC
Karman Holdings Inc.
Quality
7.7
out of 10
Value Trap
6
SAFE
Price
$57.50
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType DCO Fair ValueDCO Upside KRMN Fair ValueKRMN Upside
Bayesian DCF Intrinsic $22.67 -85.1%
Earnings Power Value Intrinsic $9.17 -93.5% $1.53 -97.5%
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 $75.29 -46.6% $1.50 -97.4%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

DCO vs KRMN — Which Stock Is More Undervalued?

KRMN scores higher with a 7.7/10 quality rating vs DCO's 6.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Ducommun Incorporated (DCO) and Karman Holdings Inc. (KRMN) 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.

DCO currently trades at $152.22 with a QOC of 6.8/10, while KRMN trades at $57.50 with a QOC of 7.7/10.

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).