TAK vs UPC

Takeda Pharmaceutical Company L vs Universe Pharmaceuticals Inc — Valuation Comparison 2026

TAK

Drug Manufacturers - Specialty & Generic
Takeda Pharmaceutical Company L
Quality
7.4
out of 10
Value Trap
39
LOW
Price
$16.15
Last close
Models
12/13
Active
VS

UPC

Drug Manufacturers - Specialty & Generic
Universe Pharmaceuticals Inc
Quality
1.5
out of 10
Value Trap
15
SAFE
Price
$2.85
Last close
Models
6/13
Active

Model-by-Model Comparison

ModelType TAK Fair ValueTAK Upside UPC Fair ValueUPC Upside
Bayesian DCF Intrinsic $36.28 +124.6% $0.56 -80.2%
Earnings Power Value Intrinsic $21.75 +34.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $8.27 -48.8% $9.06 +235.7%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

TAK vs UPC — Which Stock Is More Undervalued?

TAK scores higher with a 7.4/10 quality rating vs UPC's 1.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Takeda Pharmaceutical Company L (TAK) and Universe Pharmaceuticals Inc (UPC) 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.

TAK currently trades at $16.15 with a QOC of 7.4/10, while UPC trades at $2.85 with a QOC of 1.5/10.

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).