MBAI vs NEO

Check-Cap Ltd. vs NeoGenomics, Inc. — Valuation Comparison 2026

MBAI

Diagnostics & Research
Check-Cap Ltd.
Quality
2.5
out of 10
Value Trap
Price
$1.74
Last close
Models
12/13
Active
VS

NEO

Diagnostics & Research
NeoGenomics, Inc.
Quality
6.8
out of 10
Value Trap
25
LOW
Price
$10.19
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType MBAI Fair ValueMBAI Upside NEO Fair ValueNEO Upside
Bayesian DCF Intrinsic $0.46 -73.5% $0.46 -95.5%
Earnings Power Value Intrinsic $5.91 +307.8% $5.57 -41.0%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
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 MBAI vs NEO — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MBAI vs NEO — Which Stock Is More Undervalued?

NEO scores higher with a 6.8/10 quality rating vs MBAI's 2.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Check-Cap Ltd. (MBAI) and NeoGenomics, Inc. (NEO) 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.

MBAI currently trades at $1.74 with a QOC of 2.5/10, while NEO trades at $10.19 with a QOC of 6.8/10.

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).