EML vs SNA

Eastern Company (The) vs Snap-On Incorporated — Valuation Comparison 2026

EML

Cutlery, Handtools & General Hardware
Eastern Company (The)
Quality
7.4
out of 10
Value Trap
12
SAFE
Price
$21.53
Last close
Models
13/13
Active
VS

SNA

Cutlery, Handtools & General Hardware
Snap-On Incorporated
Quality
9.7
out of 10
Value Trap
6
SAFE
Price
$371.21
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType EML Fair ValueEML Upside SNA Fair ValueSNA Upside
Bayesian DCF Intrinsic $13.48 -37.4% $347.34 -6.4%
Earnings Power Value Intrinsic $10.52 -51.1% $180.12 -51.5%
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 $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

EML vs SNA — Which Stock Is More Undervalued?

SNA scores higher with a 9.7/10 quality rating vs EML's 7.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Eastern Company (The) (EML) and Snap-On Incorporated (SNA) 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.

EML currently trades at $21.53 with a QOC of 7.4/10, while SNA trades at $371.21 with a QOC of 9.7/10.

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).