LYG vs NWG

Lloyds Banking Group Plc vs NatWest Group plc — Valuation Comparison 2026

LYG

Commercial Banks, NEC
Lloyds Banking Group Plc
Quality
1.9
out of 10
Value Trap
Price
$5.47
Last close
Models
11/13
Active
VS

NWG

Commercial Banks, NEC
NatWest Group plc
Quality
7.6
out of 10
Value Trap
22
SAFE
Price
$16.04
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType LYG Fair ValueLYG Upside NWG Fair ValueNWG Upside
Bayesian DCF Intrinsic $1.79 -67.2% $68.48 +326.9%
Earnings Power Value Intrinsic $2.42 -54.7% $76.02 +374.0%
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 LYG vs NWG — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

LYG vs NWG — Which Stock Is More Undervalued?

NWG scores higher with a 7.6/10 quality rating vs LYG's 1.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Lloyds Banking Group Plc (LYG) and NatWest Group plc (NWG) 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.

LYG currently trades at $5.47 with a QOC of 1.9/10, while NWG trades at $16.04 with a QOC of 7.6/10.

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).