EVO vs HCM

Evotec SE vs HUTCHMED (China) Limited — Valuation Comparison 2026

EVO

Drug Manufacturers - Specialty & Generic
Evotec SE
Quality
6.2
out of 10
Value Trap
15
SAFE
Price
$2.96
Last close
Models
10/13
Active
VS

HCM

Drug Manufacturers - Specialty & Generic
HUTCHMED (China) Limited
Quality
2.5
out of 10
Value Trap
Price
$11.23
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType EVO Fair ValueEVO Upside HCM Fair ValueHCM Upside
Bayesian DCF Intrinsic $0.22 -92.8% $2.96 -73.7%
Earnings Power Value Intrinsic $2.92 -78.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $1.12 -62.0% $19.57 +74.3%
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 EVO vs HCM — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

EVO vs HCM — Which Stock Is More Undervalued?

EVO scores higher with a 6.2/10 quality rating vs HCM's 2.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Evotec SE (EVO) and HUTCHMED (China) Limited (HCM) 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.

EVO currently trades at $2.96 with a QOC of 6.2/10, while HCM trades at $11.23 with a QOC of 2.5/10.

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).