NEXM vs SCCO

NexMetals Mining Corp. vs Southern Copper Corporation — Valuation Comparison 2026

NEXM

Metal Mining
NexMetals Mining Corp.
Quality
4.8
out of 10
Value Trap
Price
$2.85
Last close
Models
8/13
Active
VS

SCCO

Metal Mining
Southern Copper Corporation
Quality
10.0
out of 10
Value Trap
Price
$191.30
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType NEXM Fair ValueNEXM Upside SCCO Fair ValueSCCO Upside
Bayesian DCF Intrinsic $1.14 -60.0% $81.84 -57.2%
Earnings Power Value Intrinsic $55.52 -71.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $1.57 -45.0% $10.92 -94.3%
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 NEXM vs SCCO — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

NEXM vs SCCO — Which Stock Is More Undervalued?

SCCO scores higher with a 10.0/10 quality rating vs NEXM's 4.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing NexMetals Mining Corp. (NEXM) and Southern Copper Corporation (SCCO) 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.

NEXM currently trades at $2.85 with a QOC of 4.8/10, while SCCO trades at $191.30 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).