CNCK vs DOMH

Coincheck Group N.V. vs Dominari Holdings Inc. — Valuation Comparison 2026

CNCK

Capital Markets
Coincheck Group N.V.
Quality
5.2
out of 10
Value Trap
Price
$1.97
Last close
Models
12/13
Active
VS

DOMH

Capital Markets
Dominari Holdings Inc.
Quality
5.6
out of 10
Value Trap
12
SAFE
Price
$3.45
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType CNCK Fair ValueCNCK Upside DOMH Fair ValueDOMH Upside
Bayesian DCF Intrinsic $1.30 -33.9% $13.67 +296.2%
Earnings Power Value Intrinsic $0.93 -52.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $1.22 -64.7%
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 CNCK vs DOMH — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CNCK vs DOMH — Which Stock Is More Undervalued?

DOMH scores higher with a 5.6/10 quality rating vs CNCK's 5.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Coincheck Group N.V. (CNCK) and Dominari Holdings Inc. (DOMH) 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.

CNCK currently trades at $1.97 with a QOC of 5.2/10, while DOMH trades at $3.45 with a QOC of 5.6/10.

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).