ARR vs BHM

ARMOUR Residential REIT, Inc. vs Bluerock Homes Trust, Inc. — Valuation Comparison 2026

ARR

Real Estate Investment Trusts
ARMOUR Residential REIT, Inc.
Quality
6.8
out of 10
Value Trap
6
SAFE
Price
$17.15
Last close
Models
10/13
Active
VS

BHM

Real Estate Investment Trusts
Bluerock Homes Trust, Inc.
Quality
6.5
out of 10
Value Trap
24
SAFE
Price
$9.96
Last close
Models
7/13
Active

Model-by-Model Comparison

ModelType ARR Fair ValueARR Upside BHM Fair ValueBHM Upside
Bayesian DCF Intrinsic $17.23 +0.5% $3.46 -67.2%
Earnings Power Value Intrinsic $2.45 -85.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $5.19 -69.7% $54.74 +426.9%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-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 ARR vs BHM — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

ARR vs BHM — Which Stock Is More Undervalued?

ARR scores higher with a 6.8/10 quality rating vs BHM's 6.5/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing ARMOUR Residential REIT, Inc. (ARR) and Bluerock Homes Trust, Inc. (BHM) 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.

ARR currently trades at $17.15 with a QOC of 6.8/10, while BHM trades at $9.96 with a QOC of 6.5/10.

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).