NE vs PDS

Noble Corporation plc A vs Precision Drilling Corporation — Valuation Comparison 2026

NE

Drilling Oil & Gas Wells
Noble Corporation plc A
Quality
8.7
out of 10
Value Trap
Price
$46.48
Last close
Models
13/13
Active
VS

PDS

Drilling Oil & Gas Wells
Precision Drilling Corporation
Quality
1.7
out of 10
Value Trap
Price
$89.40
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType NE Fair ValueNE Upside PDS Fair ValuePDS Upside
Bayesian DCF Intrinsic $12.38 -73.4% $25.98 -70.9%
Earnings Power Value Intrinsic $12.92 -72.2%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $208.12 +347.8% $127.08 +29.5%
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 NE vs PDS — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

NE vs PDS — Which Stock Is More Undervalued?

NE scores higher with a 8.7/10 quality rating vs PDS's 1.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Noble Corporation plc A (NE) and Precision Drilling Corporation (PDS) 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.

NE currently trades at $46.48 with a QOC of 8.7/10, while PDS trades at $89.40 with a QOC of 1.7/10.

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).