BRFH vs LW

Barfresh Food Group Inc. vs Lamb Weston Holdings, Inc. — Valuation Comparison 2026

BRFH

Canned, Frozen & Preservd Fruit, Veg & Food Specialties
Barfresh Food Group Inc.
Quality
5.4
out of 10
Value Trap
24
SAFE
Price
$2.29
Last close
Models
11/13
Active
VS

LW

Canned, Frozen & Preservd Fruit, Veg & Food Specialties
Lamb Weston Holdings, Inc.
Quality
8.4
out of 10
Value Trap
28
LOW
Price
$43.18
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType BRFH Fair ValueBRFH Upside LW Fair ValueLW Upside
Bayesian DCF Intrinsic $0.57 -75.2% $11.81 -73.0%
Earnings Power Value Intrinsic $0.50 -80.1% $5.19 -88.0%
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 $•••.•• ••.•% $•••.•• ••.•%
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BRFH vs LW — Which Stock Is More Undervalued?

LW scores higher with a 8.4/10 quality rating vs BRFH's 5.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Barfresh Food Group Inc. (BRFH) and Lamb Weston Holdings, Inc. (LW) 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.

BRFH currently trades at $2.29 with a QOC of 5.4/10, while LW trades at $43.18 with a QOC of 8.4/10.

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).