ET vs NGG

Energy Transfer LP vs National Grid Transco, PLC Nati — Valuation Comparison 2026

ET

Natural Gas Transmission
Energy Transfer LP
Quality
7.2
out of 10
Value Trap
6
SAFE
Price
$19.17
Last close
Models
13/13
Active
VS

NGG

Natural Gas Transmission
National Grid Transco, PLC Nati
Quality
7.1
out of 10
Value Trap
18
SAFE
Price
$81.53
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType ET Fair ValueET Upside NGG Fair ValueNGG Upside
Bayesian DCF Intrinsic $7.04 -63.3% $8.51 -89.6%
Earnings Power Value Intrinsic $2.86 -85.7% $55.50 -31.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 ET vs NGG — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

ET vs NGG — Which Stock Is More Undervalued?

ET scores higher with a 7.2/10 quality rating vs NGG's 7.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Energy Transfer LP (ET) and National Grid Transco, PLC Nati (NGG) 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.

ET currently trades at $19.17 with a QOC of 7.2/10, while NGG trades at $81.53 with a QOC of 7.1/10.

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).