EXEL vs FENC

Exelixis, Inc. vs Fennec Pharmaceuticals Inc. — Valuation Comparison 2026

EXEL

Biological Products, (No Diagnostic Substances)
Exelixis, Inc.
Quality
10.0
out of 10
Value Trap
6
SAFE
Price
$50.48
Last close
Models
12/13
Active
VS

FENC

Biological Products, (No Diagnostic Substances)
Fennec Pharmaceuticals Inc.
Quality
6.3
out of 10
Value Trap
6
SAFE
Price
$9.93
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType EXEL Fair ValueEXEL Upside FENC Fair ValueFENC Upside
Bayesian DCF Intrinsic $27.56 -45.4% $1.69 -83.0%
Earnings Power Value Intrinsic $29.37 -41.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $71.55 +41.7% $3.02 -69.6%
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 EXEL vs FENC — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

EXEL vs FENC — Which Stock Is More Undervalued?

EXEL scores higher with a 10.0/10 quality rating vs FENC's 6.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Exelixis, Inc. (EXEL) and Fennec Pharmaceuticals Inc. (FENC) 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.

EXEL currently trades at $50.48 with a QOC of 10.0/10, while FENC trades at $9.93 with a QOC of 6.3/10.

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).