LGND vs LONA

Ligand Pharmaceuticals Incorpor vs LeonaBio, Inc. — Valuation Comparison 2026

LGND

Biotechnology
Ligand Pharmaceuticals Incorpor
Quality
7.8
out of 10
Value Trap
26
LOW
Price
$234.66
Last close
Models
13/13
Active
VS

LONA

Biotechnology
LeonaBio, Inc.
Quality
4.7
out of 10
Value Trap
18
SAFE
Price
$9.64
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType LGND Fair ValueLGND Upside LONA Fair ValueLONA Upside
Bayesian DCF Intrinsic $66.47 -71.7% $4.47 -53.6%
Earnings Power Value Intrinsic $57.08 -75.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $169.84 -27.6% $13.60 +41.1%
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 LGND vs LONA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

LGND vs LONA — Which Stock Is More Undervalued?

LGND scores higher with a 7.8/10 quality rating vs LONA's 4.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Ligand Pharmaceuticals Incorpor (LGND) and LeonaBio, Inc. (LONA) 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.

LGND currently trades at $234.66 with a QOC of 7.8/10, while LONA trades at $9.64 with a QOC of 4.7/10.

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).