BPYPP vs CBRE

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

BPYPP

Real Estate
Brookfield Property Partners L.
Quality
4.8
out of 10
Value Trap
10
SAFE
Price
$15.53
Last close
Models
12/13
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 BPYPP Fair ValueBPYPP Upside CBRE Fair ValueCBRE Upside
Bayesian DCF Intrinsic $13.89 -13.2% $56.57 -54.8%
Earnings Power Value Intrinsic $6.36 -60.3% $19.31 -84.6%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
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 BPYPP vs CBRE — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

BPYPP vs CBRE — Which Stock Is More Undervalued?

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

Comparing Brookfield Property Partners L. (BPYPP) 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.

BPYPP currently trades at $15.53 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).