IMTE vs KOPN

Integrated Media Technology Lim vs Kopin Corporation — Valuation Comparison 2026

IMTE

Electronic Components
Integrated Media Technology Lim
Quality
1.7
out of 10
Value Trap
Price
$0.52
Last close
Models
6/13
Active
VS

KOPN

Electronic Components
Kopin Corporation
Quality
7.1
out of 10
Value Trap
12
SAFE
Price
$6.05
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType IMTE Fair ValueIMTE Upside KOPN Fair ValueKOPN Upside
Bayesian DCF Intrinsic $0.14 -73.5% $0.20 -96.7%
Earnings Power Value Intrinsic $0.35 -91.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $2.48 +377.6% $0.08 -98.6%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
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 IMTE vs KOPN — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

IMTE vs KOPN — Which Stock Is More Undervalued?

KOPN scores higher with a 7.1/10 quality rating vs IMTE's 1.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Integrated Media Technology Lim (IMTE) and Kopin Corporation (KOPN) 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.

IMTE currently trades at $0.52 with a QOC of 1.7/10, while KOPN trades at $6.05 with a QOC of 7.1/10.

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).