FMC vs LOOP

FMC Corporation vs Loop Industries, Inc. — Valuation Comparison 2026

FMC

Chemicals & Allied Products
FMC Corporation
Quality
6.3
out of 10
Value Trap
20
SAFE
Price
$13.66
Last close
Models
13/13
Active
VS

LOOP

Chemicals & Allied Products
Loop Industries, Inc.
Quality
5.5
out of 10
Value Trap
18
SAFE
Price
$1.39
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType FMC Fair ValueFMC Upside LOOP Fair ValueLOOP Upside
Bayesian DCF Intrinsic $22.01 +61.1% $0.27 -80.4%
Earnings Power Value Intrinsic $62.27 +355.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $4.14 -69.7% $0.12 -91.1%
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 FMC vs LOOP — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

FMC vs LOOP — Which Stock Is More Undervalued?

FMC scores higher with a 6.3/10 quality rating vs LOOP's 5.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing FMC Corporation (FMC) and Loop Industries, Inc. (LOOP) 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.

FMC currently trades at $13.66 with a QOC of 6.3/10, while LOOP trades at $1.39 with a QOC of 5.5/10.

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).