CPB vs LSF

The Campbell's Company vs Laird Superfood, Inc. — Valuation Comparison 2026

CPB

Food and Kindred Products
The Campbell's Company
Quality
8.5
out of 10
Value Trap
8
SAFE
Price
$21.11
Last close
Models
12/13
Active
VS

LSF

Food and Kindred Products
Laird Superfood, Inc.
Quality
4.8
out of 10
Value Trap
12
SAFE
Price
$3.51
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType CPB Fair ValueCPB Upside LSF Fair ValueLSF Upside
Bayesian DCF Intrinsic $14.01 -33.7% $1.42 -59.5%
Earnings Power Value Intrinsic $6.46 -69.4% $0.80 -73.8%
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 CPB vs LSF — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CPB vs LSF — Which Stock Is More Undervalued?

CPB scores higher with a 8.5/10 quality rating vs LSF's 4.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing The Campbell's Company (CPB) and Laird Superfood, Inc. (LSF) 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.

CPB currently trades at $21.11 with a QOC of 8.5/10, while LSF trades at $3.51 with a QOC of 4.8/10.

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).