CCOI vs ELWT

Cogent Communications Holdings, vs Elauwit Connection, Inc. — Valuation Comparison 2026

CCOI

Communications Services, NEC
Cogent Communications Holdings,
Quality
5.8
out of 10
Value Trap
32
LOW
Price
$17.76
Last close
Models
10/13
Active
VS

ELWT

Communications Services, NEC
Elauwit Connection, Inc.
Quality
6.0
out of 10
Value Trap
Price
$7.51
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType CCOI Fair ValueCCOI Upside ELWT Fair ValueELWT Upside
Bayesian DCF Intrinsic $4.28 -81.5% $2.22 -70.5%
Earnings Power Value Intrinsic $0.70 -90.1%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $25.98 +46.3% $7.08 -7.0%
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 $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

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

Access Full Analysis — From $27/mo →

CCOI vs ELWT — Which Stock Is More Undervalued?

ELWT scores higher with a 6.0/10 quality rating vs CCOI's 5.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Cogent Communications Holdings, (CCOI) and Elauwit Connection, Inc. (ELWT) 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.

CCOI currently trades at $17.76 with a QOC of 5.8/10, while ELWT trades at $7.51 with a QOC of 6.0/10.

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).