FCEL vs HAYW

FuelCell Energy, Inc. vs Hayward Holdings, Inc. — Valuation Comparison 2026

FCEL

Electrical Equipment & Parts
FuelCell Energy, Inc.
Quality
6.4
out of 10
Value Trap
39
LOW
Price
$24.39
Last close
Models
9/13
Active
VS

HAYW

Electrical Equipment & Parts
Hayward Holdings, Inc.
Quality
9.6
out of 10
Value Trap
20
SAFE
Price
$14.11
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType FCEL Fair ValueFCEL Upside HAYW Fair ValueHAYW Upside
Bayesian DCF Intrinsic $7.82 -68.0% $9.04 -35.9%
Earnings Power Value Intrinsic $1.94 -86.2%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $8.80 -63.9%
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 FCEL vs HAYW — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

FCEL vs HAYW — Which Stock Is More Undervalued?

HAYW scores higher with a 9.6/10 quality rating vs FCEL's 6.4/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing FuelCell Energy, Inc. (FCEL) and Hayward Holdings, Inc. (HAYW) 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.

FCEL currently trades at $24.39 with a QOC of 6.4/10, while HAYW trades at $14.11 with a QOC of 9.6/10.

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).