ELBM vs ELVR

Electra Battery Materials Corpo vs Elevra Lithium Limited - Americ — Valuation Comparison 2026

ELBM

Mining & Quarrying of Nonmetallic Minerals (No Fuels)
Electra Battery Materials Corpo
Quality
3.8
out of 10
Value Trap
12
SAFE
Price
$0.65
Last close
Models
8/13
Active
VS

ELVR

Mining & Quarrying of Nonmetallic Minerals (No Fuels)
Elevra Lithium Limited - Americ
Quality
4.0
out of 10
Value Trap
Price
$92.64
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType ELBM Fair ValueELBM Upside ELVR Fair ValueELVR Upside
Bayesian DCF Intrinsic $0.31 -53.0% $9.69 -89.5%
Earnings Power Value Intrinsic $40.75 -52.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $0.03 -95.0% $3.81 -95.1%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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ELBM vs ELVR — Which Stock Is More Undervalued?

ELVR scores higher with a 4.0/10 quality rating vs ELBM's 3.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Electra Battery Materials Corpo (ELBM) and Elevra Lithium Limited - Americ (ELVR) 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.

ELBM currently trades at $0.65 with a QOC of 3.8/10, while ELVR trades at $92.64 with a QOC of 4.0/10.

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).