NNNN vs TRIB

Anbio Biotechnology vs Trinity Biotech plc — Valuation Comparison 2026

NNNN

In Vitro & In Vivo Diagnostic Substances
Anbio Biotechnology
Quality
2.0
out of 10
Value Trap
12
SAFE
Price
$34.41
Last close
Models
13/13
Active
VS

TRIB

In Vitro & In Vivo Diagnostic Substances
Trinity Biotech plc
Quality
4.0
out of 10
Value Trap
18
SAFE
Price
$0.70
Last close
Models
5/13
Active

Model-by-Model Comparison

ModelType NNNN Fair ValueNNNN Upside TRIB Fair ValueTRIB Upside
Bayesian DCF Intrinsic $6.12 -82.2% $3.89 +453.3%
Earnings Power Value Intrinsic $1.40 -95.2% $0.40 -33.4%
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 NNNN vs TRIB — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

NNNN vs TRIB — Which Stock Is More Undervalued?

TRIB scores higher with a 4.0/10 quality rating vs NNNN's 2.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Anbio Biotechnology (NNNN) and Trinity Biotech plc (TRIB) 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.

NNNN currently trades at $34.41 with a QOC of 2.0/10, while TRIB trades at $0.70 with a QOC of 4.0/10.

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).