BRCC vs COCO

BRC Inc. vs The Vita Coco Company, Inc. — Valuation Comparison 2026

BRCC

Beverages
BRC Inc.
Quality
5.9
out of 10
Value Trap
24
SAFE
Price
$1.64
Last close
Models
12/13
Active
VS

COCO

Beverages
The Vita Coco Company, Inc.
Quality
10.0
out of 10
Value Trap
28
LOW
Price
$75.13
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType BRCC Fair ValueBRCC Upside COCO Fair ValueCOCO Upside
Bayesian DCF Intrinsic $0.11 -93.3% $16.08 -78.6%
Earnings Power Value Intrinsic $2.62 +140.1% $14.74 -80.4%
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 BRCC vs COCO — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

BRCC vs COCO — Which Stock Is More Undervalued?

COCO scores higher with a 10.0/10 quality rating vs BRCC's 5.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing BRC Inc. (BRCC) and The Vita Coco Company, Inc. (COCO) 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.

BRCC currently trades at $1.64 with a QOC of 5.9/10, while COCO trades at $75.13 with a QOC of 10.0/10.

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).