AIRJ vs APT

AirJoule Technologies Corporati vs Alpha Pro Tech, Ltd. — Valuation Comparison 2026

AIRJ

Building Products & Equipment
AirJoule Technologies Corporati
Quality
4.6
out of 10
Value Trap
6
SAFE
Price
$4.79
Last close
Models
12/13
Active
VS

APT

Building Products & Equipment
Alpha Pro Tech, Ltd.
Quality
7.4
out of 10
Value Trap
19
SAFE
Price
$5.73
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType AIRJ Fair ValueAIRJ Upside APT Fair ValueAPT Upside
Bayesian DCF Intrinsic $1.53 -68.0% $4.17 -27.2%
Earnings Power Value Intrinsic $1.69 -46.3% $2.45 -57.3%
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 AIRJ vs APT — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

AIRJ vs APT — Which Stock Is More Undervalued?

APT scores higher with a 7.4/10 quality rating vs AIRJ's 4.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing AirJoule Technologies Corporati (AIRJ) and Alpha Pro Tech, Ltd. (APT) 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.

AIRJ currently trades at $4.79 with a QOC of 4.6/10, while APT trades at $5.73 with a QOC of 7.4/10.

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).