SIGA vs TAK

SIGA Technologies Inc. vs Takeda Pharmaceutical Company L — Valuation Comparison 2026

SIGA

Drug Manufacturers - Specialty & Generic
SIGA Technologies Inc.
Quality
10.0
out of 10
Value Trap
33
LOW
Price
$4.76
Last close
Models
12/13
Active
VS

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

Model-by-Model Comparison

ModelType SIGA Fair ValueSIGA Upside TAK Fair ValueTAK Upside
Bayesian DCF Intrinsic $9.98 +109.7% $36.28 +124.6%
Earnings Power Value Intrinsic $4.97 +4.3% $21.75 +34.7%
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 SIGA vs TAK — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

SIGA vs TAK — Which Stock Is More Undervalued?

SIGA scores higher with a 10.0/10 quality rating vs TAK's 7.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing SIGA Technologies Inc. (SIGA) and Takeda Pharmaceutical Company L (TAK) 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.

SIGA currently trades at $4.76 with a QOC of 10.0/10, while TAK trades at $16.15 with a QOC of 7.4/10.

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).