PNRG vs PR

PrimeEnergy Resources Corporati vs Permian Resources Corporation — Valuation Comparison 2026

PNRG

Crude Petroleum & Natural Gas
PrimeEnergy Resources Corporati
Quality
8.8
out of 10
Value Trap
27
LOW
Price
$164.62
Last close
Models
13/13
Active
VS

PR

Crude Petroleum & Natural Gas
Permian Resources Corporation
Quality
9.1
out of 10
Value Trap
18
SAFE
Price
$19.23
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType PNRG Fair ValuePNRG Upside PR Fair ValuePR Upside
Bayesian DCF Intrinsic $558.68 +239.4% $62.53 +225.2%
Earnings Power Value Intrinsic $378.77 +130.1% $5.59 -70.9%
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 PNRG vs PR — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PNRG vs PR — Which Stock Is More Undervalued?

PR scores higher with a 9.1/10 quality rating vs PNRG's 8.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing PrimeEnergy Resources Corporati (PNRG) and Permian Resources Corporation (PR) 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.

PNRG currently trades at $164.62 with a QOC of 8.8/10, while PR trades at $19.23 with a QOC of 9.1/10.

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).