SLDB vs SRRK

Solid Biosciences Inc. vs Scholar Rock Holding Corporatio — Valuation Comparison 2026

SLDB

Biological Products, (No Diagnostic Substances)
Solid Biosciences Inc.
Quality
4.4
out of 10
Value Trap
18
SAFE
Price
$7.34
Last close
Models
7/13
Active
VS

SRRK

Biological Products, (No Diagnostic Substances)
Scholar Rock Holding Corporatio
Quality
5.1
out of 10
Value Trap
30
LOW
Price
$49.30
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType SLDB Fair ValueSLDB Upside SRRK Fair ValueSRRK Upside
Bayesian DCF Intrinsic $3.30 -55.1% $15.50 -68.6%
Earnings Power Value Intrinsic $21.36 -54.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $4.75 -35.3% $4.25 -91.4%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

SLDB vs SRRK — Which Stock Is More Undervalued?

SRRK scores higher with a 5.1/10 quality rating vs SLDB's 4.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Solid Biosciences Inc. (SLDB) and Scholar Rock Holding Corporatio (SRRK) 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.

SLDB currently trades at $7.34 with a QOC of 4.4/10, while SRRK trades at $49.30 with a QOC of 5.1/10.

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).