DSS vs SW

DSS, Inc. vs Smurfit WestRock plc — Valuation Comparison 2026

DSS

Paperboard Containers & Boxes
DSS, Inc.
Quality
4.3
out of 10
Value Trap
24
SAFE
Price
$0.48
Last close
Models
3/13
Active
VS

SW

Paperboard Containers & Boxes
Smurfit WestRock plc
Quality
7.7
out of 10
Value Trap
6
SAFE
Price
$41.15
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType DSS Fair ValueDSS Upside SW Fair ValueSW Upside
Bayesian DCF Intrinsic $39.54 -3.9%
Earnings Power Value Intrinsic $2.16 -94.5%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $0.03 -95.5% $39.52 -4.0%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $0.01 -97.9% $6.41 -84.4%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

DSS vs SW — Which Stock Is More Undervalued?

SW scores higher with a 7.7/10 quality rating vs DSS's 4.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing DSS, Inc. (DSS) and Smurfit WestRock plc (SW) 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.

DSS currently trades at $0.48 with a QOC of 4.3/10, while SW trades at $41.15 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).