COGT vs COYA

Cogent Biosciences, Inc. vs Coya Therapeutics, Inc. — Valuation Comparison 2026

COGT

Pharmaceutical Preparations
Cogent Biosciences, Inc.
Quality
4.5
out of 10
Value Trap
24
SAFE
Price
$34.96
Last close
Models
10/13
Active
VS

COYA

Pharmaceutical Preparations
Coya Therapeutics, Inc.
Quality
5.5
out of 10
Value Trap
30
LOW
Price
$4.82
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType COGT Fair ValueCOGT Upside COYA Fair ValueCOYA Upside
Bayesian DCF Intrinsic $9.82 -71.9% $2.39 -50.4%
Earnings Power Value Intrinsic $16.18 -56.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $0.15 -99.6% $0.11 -97.5%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

COGT vs COYA — Which Stock Is More Undervalued?

COYA scores higher with a 5.5/10 quality rating vs COGT's 4.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Cogent Biosciences, Inc. (COGT) and Coya Therapeutics, Inc. (COYA) 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.

COGT currently trades at $34.96 with a QOC of 4.5/10, while COYA trades at $4.82 with a QOC of 5.5/10.

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).