EWTX vs FHTX

Edgewise Therapeutics, Inc. vs Foghorn Therapeutics Inc. — Valuation Comparison 2026

EWTX

Pharmaceutical Preparations
Edgewise Therapeutics, Inc.
Quality
4.1
out of 10
Value Trap
18
SAFE
Price
$34.16
Last close
Models
10/13
Active
VS

FHTX

Pharmaceutical Preparations
Foghorn Therapeutics Inc.
Quality
6.3
out of 10
Value Trap
24
SAFE
Price
$4.28
Last close
Models
7/13
Active

Model-by-Model Comparison

ModelType EWTX Fair ValueEWTX Upside FHTX Fair ValueFHTX Upside
Bayesian DCF Intrinsic $10.07 -70.5% $1.29 -69.8%
Earnings Power Value Intrinsic $13.97 -55.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $30.80 -9.8% $8.04 +87.9%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for EWTX vs FHTX — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

EWTX vs FHTX — Which Stock Is More Undervalued?

FHTX scores higher with a 6.3/10 quality rating vs EWTX's 4.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Edgewise Therapeutics, Inc. (EWTX) and Foghorn Therapeutics Inc. (FHTX) 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.

EWTX currently trades at $34.16 with a QOC of 4.1/10, while FHTX trades at $4.28 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).