USLM vs UUUU

United States Lime & Minerals, vs Energy Fuels Inc — Valuation Comparison 2026

USLM

Mining & Quarrying of Nonmetallic Minerals (No Fuels)
United States Lime & Minerals,
Quality
10.0
out of 10
Value Trap
18
SAFE
Price
$113.99
Last close
Models
13/13
Active
VS

UUUU

Mining & Quarrying of Nonmetallic Minerals (No Fuels)
Energy Fuels Inc
Quality
6.3
out of 10
Value Trap
24
SAFE
Price
$18.22
Last close
Models
9/13
Active

Model-by-Model Comparison

ModelType USLM Fair ValueUSLM Upside UUUU Fair ValueUUUU Upside
Bayesian DCF Intrinsic $60.90 -46.6% $4.21 -76.9%
Earnings Power Value Intrinsic $50.47 -55.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $109.27 -4.1% $4.20 -79.3%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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USLM vs UUUU — Which Stock Is More Undervalued?

USLM scores higher with a 10.0/10 quality rating vs UUUU's 6.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing United States Lime & Minerals, (USLM) and Energy Fuels Inc (UUUU) 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.

USLM currently trades at $113.99 with a QOC of 10.0/10, while UUUU trades at $18.22 with a QOC of 6.3/10.

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).