CHCI vs CMTG

Comstock Holding Companies, Inc vs Claros Mortgage Trust, Inc. — Valuation Comparison 2026

CHCI

Real Estate
Comstock Holding Companies, Inc
Quality
8.3
out of 10
Value Trap
12
SAFE
Price
$15.24
Last close
Models
12/13
Active
VS

CMTG

Real Estate
Claros Mortgage Trust, Inc.
Quality
4.9
out of 10
Value Trap
16
SAFE
Price
$2.43
Last close
Models
3/13
Active

Model-by-Model Comparison

ModelType CHCI Fair ValueCHCI Upside CMTG Fair ValueCMTG Upside
Bayesian DCF Intrinsic $5.62 -63.1%
Earnings Power Value Intrinsic $3.82 -74.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $23.79 +56.1% $0.09 -95.5%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $15.53 +1.9% $4.82 +98.2%
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 CHCI vs CMTG — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CHCI vs CMTG — Which Stock Is More Undervalued?

CHCI scores higher with a 8.3/10 quality rating vs CMTG's 4.9/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Comstock Holding Companies, Inc (CHCI) and Claros Mortgage Trust, Inc. (CMTG) 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.

CHCI currently trades at $15.24 with a QOC of 8.3/10, while CMTG trades at $2.43 with a QOC of 4.9/10.

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).