BPYPM vs CBRE

Brookfield Property Partners L. vs CBRE Group Inc — Valuation Comparison 2026

BPYPM

Real Estate
Brookfield Property Partners L.
Quality
4.8
out of 10
Value Trap
10
SAFE
Price
$17.45
Last close
Models
4/13
Active
VS

CBRE

Real Estate
CBRE Group Inc
Quality
7.0
out of 10
Value Trap
38
LOW
Price
$125.04
Last close
Models
12/13
Active

Model-by-Model Comparison

ModelType BPYPM Fair ValueBPYPM Upside CBRE Fair ValueCBRE Upside
Bayesian DCF Intrinsic $56.57 -54.8%
Earnings Power Value Intrinsic $19.31 -84.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $44.08 +152.6% $350.42 +180.2%
ML-RIV Intrinsic $26.11 +49.6% $86.50 -30.8%
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 BPYPM vs CBRE — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

BPYPM vs CBRE — Which Stock Is More Undervalued?

CBRE scores higher with a 7.0/10 quality rating vs BPYPM's 4.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Brookfield Property Partners L. (BPYPM) and CBRE Group Inc (CBRE) 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.

BPYPM currently trades at $17.45 with a QOC of 4.8/10, while CBRE trades at $125.04 with a QOC of 7.0/10.

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).