PZG vs RGLD

Paramount Gold Nevada Corp. vs Royal Gold, Inc. — Valuation Comparison 2026

PZG

Gold
Paramount Gold Nevada Corp.
Quality
4.1
out of 10
Value Trap
38
LOW
Price
$1.39
Last close
Models
5/13
Active
VS

RGLD

Gold
Royal Gold, Inc.
Quality
10.0
out of 10
Value Trap
18
SAFE
Price
$222.68
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType PZG Fair ValuePZG Upside RGLD Fair ValueRGLD Upside
Bayesian DCF Intrinsic $0.33 -76.0% $116.00 -47.9%
Earnings Power Value Intrinsic $70.50 -68.3%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $0.04 -97.4% $35.66 -84.0%
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 PZG vs RGLD — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PZG vs RGLD — Which Stock Is More Undervalued?

RGLD scores higher with a 10.0/10 quality rating vs PZG's 4.1/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Paramount Gold Nevada Corp. (PZG) and Royal Gold, Inc. (RGLD) 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.

PZG currently trades at $1.39 with a QOC of 4.1/10, while RGLD trades at $222.68 with a QOC of 10.0/10.

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).