MDGL vs MGNX

Madrigal Pharmaceuticals, Inc. vs MacroGenics, Inc. — Valuation Comparison 2026

MDGL

Biotechnology
Madrigal Pharmaceuticals, Inc.
Quality
6.9
out of 10
Value Trap
18
SAFE
Price
$515.96
Last close
Models
12/13
Active
VS

MGNX

Biotechnology
MacroGenics, Inc.
Quality
6.2
out of 10
Value Trap
24
SAFE
Price
$4.21
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType MDGL Fair ValueMDGL Upside MGNX Fair ValueMGNX Upside
Bayesian DCF Intrinsic $174.43 -66.2% $1.10 -73.9%
Earnings Power Value Intrinsic $237.47 -53.7% $9.04 +188.9%
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 MDGL vs MGNX — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MDGL vs MGNX — Which Stock Is More Undervalued?

MDGL scores higher with a 6.9/10 quality rating vs MGNX's 6.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Madrigal Pharmaceuticals, Inc. (MDGL) and MacroGenics, Inc. (MGNX) 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.

MDGL currently trades at $515.96 with a QOC of 6.9/10, while MGNX trades at $4.21 with a QOC of 6.2/10.

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).