NEXA vs NEXM

Nexa Resources S.A. vs NexMetals Mining Corp. — Valuation Comparison 2026

NEXA

Metal Mining
Nexa Resources S.A.
Quality
7.0
out of 10
Value Trap
22
SAFE
Price
$15.14
Last close
Models
12/13
Active
VS

NEXM

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

Model-by-Model Comparison

ModelType NEXA Fair ValueNEXA Upside NEXM Fair ValueNEXM Upside
Bayesian DCF Intrinsic $0.74 -95.1% $1.14 -60.0%
Earnings Power Value Intrinsic $49.93 +229.8%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $1.57 -45.0%
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 NEXA vs NEXM — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

NEXA vs NEXM — Which Stock Is More Undervalued?

NEXA scores higher with a 7.0/10 quality rating vs NEXM's 4.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Nexa Resources S.A. (NEXA) and NexMetals Mining Corp. (NEXM) 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.

NEXA currently trades at $15.14 with a QOC of 7.0/10, while NEXM trades at $2.85 with a QOC of 4.8/10.

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).