CSCO vs HUBC

Cisco Systems, Inc. vs Hub Cyber Security Ltd. — Valuation Comparison 2026

CSCO

Computer Communications Equipment
Cisco Systems, Inc.
Quality
9.2
out of 10
Value Trap
19
SAFE
Price
$120.42
Last close
Models
12/13
Active
VS

HUBC

Computer Communications Equipment
Hub Cyber Security Ltd.
Quality
2.0
out of 10
Value Trap
Price
$0.26
Last close
Models
2/13
Active

Model-by-Model Comparison

ModelType CSCO Fair ValueCSCO Upside HUBC Fair ValueHUBC Upside
Bayesian DCF Intrinsic $48.69 -59.6%
Earnings Power Value Intrinsic $23.42 -80.5%
EROIC Spread Intrinsic $23.30 -80.7% $0.25 -24.7%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $39.54 -67.2% $0.09 -67.0%
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 CSCO vs HUBC — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CSCO vs HUBC — Which Stock Is More Undervalued?

CSCO scores higher with a 9.2/10 quality rating vs HUBC's 2.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Cisco Systems, Inc. (CSCO) and Hub Cyber Security Ltd. (HUBC) 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.

CSCO currently trades at $120.42 with a QOC of 9.2/10, while HUBC trades at $0.26 with a QOC of 2.0/10.

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).