MTRX vs PHOE

Matrix Service Company vs Phoenix Asia Holdings Limited — Valuation Comparison 2026

MTRX

Construction - Special Trade Contractors
Matrix Service Company
Quality
7.3
out of 10
Value Trap
18
SAFE
Price
$13.13
Last close
Models
12/13
Active
VS

PHOE

Construction - Special Trade Contractors
Phoenix Asia Holdings Limited
Quality
2.3
out of 10
Value Trap
Price
$15.59
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType MTRX Fair ValueMTRX Upside PHOE Fair ValuePHOE Upside
Bayesian DCF Intrinsic $6.77 -48.4% $4.16 -73.3%
Earnings Power Value Intrinsic $12.20 -7.1% $0.67 -96.2%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
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 MTRX vs PHOE — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MTRX vs PHOE — Which Stock Is More Undervalued?

MTRX scores higher with a 7.3/10 quality rating vs PHOE's 2.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Matrix Service Company (MTRX) and Phoenix Asia Holdings Limited (PHOE) 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.

MTRX currently trades at $13.13 with a QOC of 7.3/10, while PHOE trades at $15.59 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).