LTBR vs NVT

Lightbridge Corporation vs nVent Electric plc — Valuation Comparison 2026

LTBR

Electrical Equipment & Parts
Lightbridge Corporation
Quality
4.5
out of 10
Value Trap
12
SAFE
Price
$11.59
Last close
Models
7/13
Active
VS

NVT

Electrical Equipment & Parts
nVent Electric plc
Quality
9.6
out of 10
Value Trap
6
SAFE
Price
$164.87
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType LTBR Fair ValueLTBR Upside NVT Fair ValueNVT Upside
Bayesian DCF Intrinsic $6.70 -42.2% $30.37 -81.6%
Earnings Power Value Intrinsic $8.91 -94.4%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $6.94 -40.2%
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 LTBR vs NVT — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

LTBR vs NVT — Which Stock Is More Undervalued?

NVT scores higher with a 9.6/10 quality rating vs LTBR's 4.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Lightbridge Corporation (LTBR) and nVent Electric plc (NVT) 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.

LTBR currently trades at $11.59 with a QOC of 4.5/10, while NVT trades at $164.87 with a QOC of 9.6/10.

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).