PZG vs TMC

Paramount Gold Nevada Corp. vs TMC the metals company Inc. — Valuation Comparison 2026

PZG

Metal Mining
Paramount Gold Nevada Corp.
Quality
4.1
out of 10
Value Trap
38
LOW
Price
$1.38
Last close
Models
5/13
Active
VS

TMC

Metal Mining
TMC the metals company Inc.
Quality
3.6
out of 10
Value Trap
18
SAFE
Price
$6.05
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType PZG Fair ValuePZG Upside TMC Fair ValueTMC Upside
Bayesian DCF Intrinsic $0.32 -76.7% $1.67 -72.4%
Earnings Power Value Intrinsic $0.34 -93.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $0.04 -97.4%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for PZG vs TMC — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

PZG vs TMC — Which Stock Is More Undervalued?

PZG scores higher with a 4.1/10 quality rating vs TMC's 3.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Paramount Gold Nevada Corp. (PZG) and TMC the metals company Inc. (TMC) 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 $1.38 with a QOC of 4.1/10, while TMC trades at $6.05 with a QOC of 3.6/10.

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).