TKO vs ZNB

TKO Group Holdings, Inc. vs Zeta Network Group — Valuation Comparison 2026

TKO

Entertainment
TKO Group Holdings, Inc.
Quality
6.4
out of 10
Value Trap
37
LOW
Price
$200.54
Last close
Models
12/13
Active
VS

ZNB

Entertainment
Zeta Network Group
Quality
2.0
out of 10
Value Trap
15
SAFE
Price
$1.71
Last close
Models
8/13
Active

Model-by-Model Comparison

ModelType TKO Fair ValueTKO Upside ZNB Fair ValueZNB Upside
Bayesian DCF Intrinsic $92.03 -54.1% $0.45 -73.5%
Earnings Power Value Intrinsic $99.45 -50.4%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $230.09 +14.7% $3.26 +88.5%
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 TKO vs ZNB — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

TKO vs ZNB — Which Stock Is More Undervalued?

TKO scores higher with a 6.4/10 quality rating vs ZNB's 2.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing TKO Group Holdings, Inc. (TKO) and Zeta Network Group (ZNB) 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.

TKO currently trades at $200.54 with a QOC of 6.4/10, while ZNB trades at $1.71 with a QOC of 2.0/10.

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).