IMCC vs INDV

IM Cannabis Corp. vs Indivior Pharmaceuticals, Inc. — Valuation Comparison 2026

IMCC

Drug Manufacturers - Specialty & Generic
IM Cannabis Corp.
Quality
5.4
out of 10
Value Trap
12
SAFE
Price
$0.29
Last close
Models
4/13
Active
VS

INDV

Drug Manufacturers - Specialty & Generic
Indivior Pharmaceuticals, Inc.
Quality
5.9
out of 10
Value Trap
6
SAFE
Price
$36.61
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType IMCC Fair ValueIMCC Upside INDV Fair ValueINDV Upside
Bayesian DCF Intrinsic $8.36 -77.2%
Earnings Power Value Intrinsic $1.11 +282.0% $18.45 -49.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $0.29 -2.1% $76.44 +108.8%
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 IMCC vs INDV — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

IMCC vs INDV — Which Stock Is More Undervalued?

INDV scores higher with a 5.9/10 quality rating vs IMCC's 5.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing IM Cannabis Corp. (IMCC) and Indivior Pharmaceuticals, Inc. (INDV) 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.

IMCC currently trades at $0.29 with a QOC of 5.4/10, while INDV trades at $36.61 with a QOC of 5.9/10.

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).