GP vs MTW

GreenPower Motor Company Inc. vs Manitowoc Company, Inc. (The) — Valuation Comparison 2026

GP

Farm & Heavy Construction Machinery
GreenPower Motor Company Inc.
Quality
2.0
out of 10
Value Trap
Price
$1.05
Last close
Models
11/13
Active
VS

MTW

Farm & Heavy Construction Machinery
Manitowoc Company, Inc. (The)
Quality
6.8
out of 10
Value Trap
16
SAFE
Price
$12.06
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType GP Fair ValueGP Upside MTW Fair ValueMTW Upside
Bayesian DCF Intrinsic $0.28 -73.5% $0.76 -93.4%
Earnings Power Value Intrinsic $1.79 +75.9%
EROIC Spread Intrinsic $2.92 +186.7% $16.16 +34.0%
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 GP vs MTW — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

GP vs MTW — Which Stock Is More Undervalued?

MTW scores higher with a 6.8/10 quality rating vs GP's 2.0/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing GreenPower Motor Company Inc. (GP) and Manitowoc Company, Inc. (The) (MTW) 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.

GP currently trades at $1.05 with a QOC of 2.0/10, while MTW trades at $12.06 with a QOC of 6.8/10.

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).