GENC vs HY

Gencor Industries, Inc. vs Hyster-Yale, Inc. — Valuation Comparison 2026

GENC

Farm & Heavy Construction Machinery
Gencor Industries, Inc.
Quality
9.8
out of 10
Value Trap
6
SAFE
Price
$14.46
Last close
Models
12/13
Active
VS

HY

Farm & Heavy Construction Machinery
Hyster-Yale, Inc.
Quality
6.3
out of 10
Value Trap
12
SAFE
Price
$36.30
Last close
Models
11/13
Active

Model-by-Model Comparison

ModelType GENC Fair ValueGENC Upside HY Fair ValueHY Upside
Bayesian DCF Intrinsic $4.78 -67.0%
Earnings Power Value Intrinsic $9.31 -35.6% $6.72 -83.1%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $17.05 +17.9% $72.22 +99.5%
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 GENC vs HY — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

GENC vs HY — Which Stock Is More Undervalued?

GENC scores higher with a 9.8/10 quality rating vs HY's 6.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Gencor Industries, Inc. (GENC) and Hyster-Yale, Inc. (HY) 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.

GENC currently trades at $14.46 with a QOC of 9.8/10, while HY trades at $36.30 with a QOC of 6.3/10.

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).