CMCSA vs GLIBA

Comcast Corporation vs GCI Liberty, Inc. - Series A GC — Valuation Comparison 2026

CMCSA

Cable & Other Pay Television Services
Comcast Corporation
Quality
8.6
out of 10
Value Trap
Price
$24.87
Last close
Models
12/13
Active
VS

GLIBA

Cable & Other Pay Television Services
GCI Liberty, Inc. - Series A GC
Quality
5.5
out of 10
Value Trap
Price
$22.31
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType CMCSA Fair ValueCMCSA Upside GLIBA Fair ValueGLIBA Upside
Bayesian DCF Intrinsic $60.82 +144.5% $34.95 +56.7%
Earnings Power Value Intrinsic $52.17 +109.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $58.90 +136.8% $32.86 +47.3%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
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 CMCSA vs GLIBA — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CMCSA vs GLIBA — Which Stock Is More Undervalued?

CMCSA scores higher with a 8.6/10 quality rating vs GLIBA's 5.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Comcast Corporation (CMCSA) and GCI Liberty, Inc. - Series A GC (GLIBA) 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.

CMCSA currently trades at $24.87 with a QOC of 8.6/10, while GLIBA trades at $22.31 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).