DTE vs EDN

DTE Energy Company vs Empresa Distribuidora Y Comerci — Valuation Comparison 2026

DTE

Electric Services
DTE Energy Company
Quality
8.1
out of 10
Value Trap
18
SAFE
Price
$142.87
Last close
Models
13/13
Active
VS

EDN

Electric Services
Empresa Distribuidora Y Comerci
Quality
1.9
out of 10
Value Trap
Price
$27.64
Last close
Models
7/13
Active

Model-by-Model Comparison

ModelType DTE Fair ValueDTE Upside EDN Fair ValueEDN Upside
Bayesian DCF Intrinsic $151.56 +6.1% $6.61 -76.1%
Earnings Power Value Intrinsic $16.77 -88.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $461.14 +222.8% $5.20 -79.2%
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 DTE vs EDN — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

DTE vs EDN — Which Stock Is More Undervalued?

DTE scores higher with a 8.1/10 quality rating vs EDN's 1.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing DTE Energy Company (DTE) and Empresa Distribuidora Y Comerci (EDN) 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.

DTE currently trades at $142.87 with a QOC of 8.1/10, while EDN trades at $27.64 with a QOC of 1.9/10.

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).