MAR vs MRNO

Marriott International vs Murano Global Investments PLC — Valuation Comparison 2026

MAR

Hotels & Motels
Marriott International
Quality
8.6
out of 10
Value Trap
Price
$375.60
Last close
Models
13/13
Active
VS

MRNO

Hotels & Motels
Murano Global Investments PLC
Quality
4.8
out of 10
Value Trap
6
SAFE
Price
$0.35
Last close
Models
3/13
Active

Model-by-Model Comparison

ModelType MAR Fair ValueMAR Upside MRNO Fair ValueMRNO Upside
Bayesian DCF Intrinsic $175.34 -53.3% $0.08 -76.5%
Earnings Power Value Intrinsic $136.34 -63.7%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
Markov DDM Intrinsic $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
Dynamic NAV Asset-Based $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $•••.•• ••.•% $•••.•• ••.•%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $278.85 -25.8% $0.94 +168.1%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
RCMH-DCF Intrinsic $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for MAR vs MRNO — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

MAR vs MRNO — Which Stock Is More Undervalued?

MAR scores higher with a 8.6/10 quality rating vs MRNO's 4.8/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Marriott International (MAR) and Murano Global Investments PLC (MRNO) 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.

MAR currently trades at $375.60 with a QOC of 8.6/10, while MRNO trades at $0.35 with a QOC of 4.8/10.

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).