FEIM vs INSG

Frequency Electronics, Inc. vs Inseego Corp. — Valuation Comparison 2026

FEIM

Communication Equipment
Frequency Electronics, Inc.
Quality
7.6
out of 10
Value Trap
26
LOW
Price
$75.60
Last close
Models
12/13
Active
VS

INSG

Communication Equipment
Inseego Corp.
Quality
5.6
out of 10
Value Trap
28
LOW
Price
$13.15
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType FEIM Fair ValueFEIM Upside INSG Fair ValueINSG Upside
Bayesian DCF Intrinsic $0.72 -98.9% $3.61 -72.6%
Earnings Power Value Intrinsic $1.70 -97.8% $6.86 -47.9%
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 FEIM vs INSG — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

FEIM vs INSG — Which Stock Is More Undervalued?

FEIM scores higher with a 7.6/10 quality rating vs INSG's 5.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Frequency Electronics, Inc. (FEIM) and Inseego Corp. (INSG) 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.

FEIM currently trades at $75.60 with a QOC of 7.6/10, while INSG trades at $13.15 with a QOC of 5.6/10.

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).