AON vs EHTH

Aon plc vs eHealth, Inc. — Valuation Comparison 2026

AON

Insurance Brokers
Aon plc
Quality
9.3
out of 10
Value Trap
17
SAFE
Price
$318.30
Last close
Models
12/13
Active
VS

EHTH

Insurance Brokers
eHealth, Inc.
Quality
7.2
out of 10
Value Trap
36
LOW
Price
$1.59
Last close
Models
7/13
Active

Model-by-Model Comparison

ModelType AON Fair ValueAON Upside EHTH Fair ValueEHTH Upside
Bayesian DCF Intrinsic $259.72 -18.4%
Earnings Power Value Intrinsic $37.84 -88.1% $2.80 +37.2%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $260.57 -18.1% $5.36 +229.9%
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 AON vs EHTH — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

AON vs EHTH — Which Stock Is More Undervalued?

AON scores higher with a 9.3/10 quality rating vs EHTH's 7.2/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Aon plc (AON) and eHealth, Inc. (EHTH) 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.

AON currently trades at $318.30 with a QOC of 9.3/10, while EHTH trades at $1.59 with a QOC of 7.2/10.

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).