ROAD vs SKK

Construction Partners, Inc. vs SKK Holdings Limited — Valuation Comparison 2026

ROAD

Engineering & Construction
Construction Partners, Inc.
Quality
8.8
out of 10
Value Trap
29
LOW
Price
$120.13
Last close
Models
11/13
Active
VS

SKK

Engineering & Construction
SKK Holdings Limited
Quality
2.3
out of 10
Value Trap
Price
$3.98
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType ROAD Fair ValueROAD Upside SKK Fair ValueSKK Upside
Bayesian DCF Intrinsic $6.70 -94.4% $1.12 -71.8%
Earnings Power Value Intrinsic $0.81 -53.8%
EROIC Spread Intrinsic $10.90 -90.9% $0.71 -59.6%
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 ROAD vs SKK — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

ROAD vs SKK — Which Stock Is More Undervalued?

ROAD scores higher with a 8.8/10 quality rating vs SKK's 2.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Construction Partners, Inc. (ROAD) and SKK Holdings Limited (SKK) 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.

ROAD currently trades at $120.13 with a QOC of 8.8/10, while SKK trades at $3.98 with a QOC of 2.3/10.

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).