BLDP vs FPS

Ballard Power Systems, Inc. vs Forgent Power Solutions, Inc. — Valuation Comparison 2026

BLDP

Electrical Industrial Apparatus
Ballard Power Systems, Inc.
Quality
2.0
out of 10
Value Trap
Price
$6.29
Last close
Models
11/13
Active
VS

FPS

Electrical Industrial Apparatus
Forgent Power Solutions, Inc.
Quality
1.6
out of 10
Value Trap
Price
$54.66
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType BLDP Fair ValueBLDP Upside FPS Fair ValueFPS Upside
Bayesian DCF Intrinsic $1.28 -79.6% $15.43 -71.8%
Earnings Power Value Intrinsic $1.31 -61.3% $10.64 -69.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for BLDP vs FPS — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

BLDP vs FPS — Which Stock Is More Undervalued?

BLDP scores higher with a 2.0/10 quality rating vs FPS's 1.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Ballard Power Systems, Inc. (BLDP) and Forgent Power Solutions, Inc. (FPS) 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.

BLDP currently trades at $6.29 with a QOC of 2.0/10, while FPS trades at $54.66 with a QOC of 1.6/10.

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).