MPTI vs OLED

M-tron Industries, Inc. vs Universal Display Corporation — Valuation Comparison 2026

MPTI

Electronic Components
M-tron Industries, Inc.
Quality
10.0
out of 10
Value Trap
6
SAFE
Price
$87.68
Last close
Models
12/13
Active
VS

OLED

Electronic Components
Universal Display Corporation
Quality
6.3
out of 10
Value Trap
12
SAFE
Price
$94.15
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType MPTI Fair ValueMPTI Upside OLED Fair ValueOLED Upside
Bayesian DCF Intrinsic $19.16 -78.1% $28.61 -69.6%
Earnings Power Value Intrinsic $23.01 -73.8% $56.13 -40.4%
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 $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for MPTI vs OLED — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MPTI vs OLED — Which Stock Is More Undervalued?

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

Comparing M-tron Industries, Inc. (MPTI) and Universal Display Corporation (OLED) 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.

MPTI currently trades at $87.68 with a QOC of 10.0/10, while OLED trades at $94.15 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).