SLNO vs SNGX

Soleno Therapeutics, Inc. vs Soligenix, Inc. — Valuation Comparison 2026

SLNO

Biotechnology
Soleno Therapeutics, Inc.
Quality
7.1
out of 10
Value Trap
18
SAFE
Price
$53.01
Last close
Models
13/13
Active
VS

SNGX

Biotechnology
Soligenix, Inc.
Quality
5.0
out of 10
Value Trap
35
LOW
Price
$0.97
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType SLNO Fair ValueSLNO Upside SNGX Fair ValueSNGX Upside
Bayesian DCF Intrinsic $13.39 -74.7% $0.46 -52.8%
Earnings Power Value Intrinsic $2.73 -94.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $6.44 -87.8% $1.74 +78.5%
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 SLNO vs SNGX — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

SLNO vs SNGX — Which Stock Is More Undervalued?

SLNO scores higher with a 7.1/10 quality rating vs SNGX's 5.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Soleno Therapeutics, Inc. (SLNO) and Soligenix, Inc. (SNGX) 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.

SLNO currently trades at $53.01 with a QOC of 7.1/10, while SNGX trades at $0.97 with a QOC of 5.0/10.

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).