Is UONE or UONEK more undervalued in 2026?

CirclFi compares Urban One, Inc. (UONE) and Urban One, Inc. (UONEK) using 13 institutional-grade valuation models. UONE has a Quality of Company score of 2.9/10 while UONEK scores 5.0/10.

Which is a better buy — UONE or UONEK?

Compare intrinsic values from 13 independent models against current market prices. CirclFi also calculates Value Trap scores. This is not financial advice — conduct your own analysis.

How do UONE and UONEK valuations compare?

UONE at $6.59 and UONEK at $5.25 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

UONE vs UONEK Valuation Comparison 2026 — Intrinsic Value Analysis

UONE

Radio Broadcasting Stations

Urban One, Inc.

Quality

2.9

out of 10

Value Trap

SAFE

Price

$6.59

Last close

Models

2/13

Active

UONEK

Radio Broadcasting Stations

Urban One, Inc.

Quality

5.0

out of 10

Value Trap

LOW

Price

$5.25

Last close

Models

4/13

Active

Model-by-Model Comparison

Model	Type	UONE Fair Value	UONE Upside	UONEK Fair Value	UONEK Upside
Markov DDM	Intrinsic	—	—	$5.65	+7.7%
Dynamic NAV	Asset-Based	$•••.••	••.•%	$•••.••	••.•%
Regime Cross-Sectional	Relative	$14.42	+155.7%	—	—
Sentiment SOTP	Hybrid	$2.26	-59.9%	—	—
FTNN Topology	Relative	$•••.••	••.•%	$•••.••	••.•%
RCMH-DCF	Intrinsic	—	—	$30.81	+440.5%

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UONE vs UONEK — Which Stock Is More Undervalued?

UONEK scores higher with a 5.0/10 quality rating vs UONE's 2.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Urban One, Inc. (UONE) and Urban One, Inc. (UONEK) 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.

UONE currently trades at $6.59 with a QOC of 2.9/10, while UONEK trades at $5.25 with a QOC of 5.0/10.

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).