FLD vs GLXY

Fold Holdings, Inc. vs Galaxy Digital Inc. — Valuation Comparison 2026

FLD

Capital Markets
Fold Holdings, Inc.
Quality
4.1
out of 10
Value Trap
22
SAFE
Price
$1.00
Last close
Models
9/13
Active
VS

GLXY

Capital Markets
Galaxy Digital Inc.
Quality
6.4
out of 10
Value Trap
Price
$30.13
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType FLD Fair ValueFLD Upside GLXY Fair ValueGLXY Upside
Bayesian DCF Intrinsic $0.31 -69.4% $31.72 +5.3%
Earnings Power Value Intrinsic $26.00 -13.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $0.02 -98.0%
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 FLD vs GLXY — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

FLD vs GLXY — Which Stock Is More Undervalued?

GLXY scores higher with a 6.4/10 quality rating vs FLD's 4.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Fold Holdings, Inc. (FLD) and Galaxy Digital Inc. (GLXY) 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.

FLD currently trades at $1.00 with a QOC of 4.1/10, while GLXY trades at $30.13 with a QOC of 6.4/10.

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).