YCBD vs ZTS

cbdMD, Inc. vs Zoetis Inc. — Valuation Comparison 2026

YCBD

Drug Manufacturers - Specialty & Generic
cbdMD, Inc.
Quality
5.3
out of 10
Value Trap
32
LOW
Price
$0.83
Last close
Models
11/13
Active
VS

ZTS

Drug Manufacturers - Specialty & Generic
Zoetis Inc.
Quality
10.0
out of 10
Value Trap
6
SAFE
Price
$78.27
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType YCBD Fair ValueYCBD Upside ZTS Fair ValueZTS Upside
Bayesian DCF Intrinsic $0.31 -62.7% $80.33 +2.6%
Earnings Power Value Intrinsic $2.68 +208.3% $55.66 -28.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
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 YCBD vs ZTS — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

YCBD vs ZTS — Which Stock Is More Undervalued?

ZTS scores higher with a 10.0/10 quality rating vs YCBD's 5.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing cbdMD, Inc. (YCBD) and Zoetis Inc. (ZTS) 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.

YCBD currently trades at $0.83 with a QOC of 5.3/10, while ZTS trades at $78.27 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).