ATRO vs ESLT

Astronics Corporation vs Elbit Systems Ltd. — Valuation Comparison 2026

ATRO

Aircraft Parts & Auxiliary Equipment, NEC
Astronics Corporation
Quality
8.9
out of 10
Value Trap
18
SAFE
Price
$87.00
Last close
Models
12/13
Active
VS

ESLT

Aircraft Parts & Auxiliary Equipment, NEC
Elbit Systems Ltd.
Quality
2.2
out of 10
Value Trap
Price
$880.89
Last close
Models
13/13
Active

Model-by-Model Comparison

ModelType ATRO Fair ValueATRO Upside ESLT Fair ValueESLT Upside
Bayesian DCF Intrinsic $4.69 -94.2% $332.09 -62.3%
Earnings Power Value Intrinsic $0.82 -99.0% $47.96 -94.2%
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 ATRO vs ESLT — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

ATRO vs ESLT — Which Stock Is More Undervalued?

ATRO scores higher with a 8.9/10 quality rating vs ESLT's 2.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Astronics Corporation (ATRO) and Elbit Systems Ltd. (ESLT) 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.

ATRO currently trades at $87.00 with a QOC of 8.9/10, while ESLT trades at $880.89 with a QOC of 2.2/10.

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).