FOA vs RKT

Finance of America Companies In vs Rocket Companies, Inc. — Valuation Comparison 2026

FOA

Mortgage Bankers & Loan Correspondents
Finance of America Companies In
Quality
6.6
out of 10
Value Trap
32
LOW
Price
$19.92
Last close
Models
6/13
Active
VS

RKT

Mortgage Bankers & Loan Correspondents
Rocket Companies, Inc.
Quality
4.7
out of 10
Value Trap
35
LOW
Price
$14.51
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType FOA Fair ValueFOA Upside RKT Fair ValueRKT Upside
Bayesian DCF Intrinsic $25.76 +77.6%
Earnings Power Value Intrinsic $109.79 +451.2% $10.63 -31.6%
EROIC Spread Intrinsic $49.00 +146.0% $0.80 -94.5%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 FOA vs RKT — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

FOA vs RKT — Which Stock Is More Undervalued?

FOA scores higher with a 6.6/10 quality rating vs RKT's 4.7/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Finance of America Companies In (FOA) and Rocket Companies, Inc. (RKT) 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.

FOA currently trades at $19.92 with a QOC of 6.6/10, while RKT trades at $14.51 with a QOC of 4.7/10.

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).